main
jack
2 weeks ago
parent
6ba7e59cc2
commit
cf56e4e9dc
@ -0,0 +1,249 @@ |
||||
rank(software_services_exposure_score) |
||||
|
||||
ts_rank(mdl77_400_rdsale, 252) |
||||
|
||||
group_zscore(mdl77_400_rdsale, technology_pca_factor1_grouping5) |
||||
|
||||
if_else(mdl77_400_rdsale > ts_mean(mdl77_400_rdsale, 252), rank(software_services_exposure_score), 0) |
||||
|
||||
add(rank(mdl77_400_rdsale), rank(software_services_exposure_score)) |
||||
|
||||
ts_delay(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_delay(software_services_exposure_score, 252)) |
||||
|
||||
multiply(rank(mdl77_400_rdsale), rank(software_services_exposure_score)) |
||||
|
||||
ts_zscore(mdl77_400_rdsale, 126) |
||||
|
||||
group_rank(mdl77_400_rdsale, technology_pca_factor1_grouping5) |
||||
|
||||
ts_mean(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_mean(mdl77_400_rdsale, 252)) |
||||
|
||||
group_neutralize(mdl77_400_rdsale, technology_pca_factor1_grouping5) |
||||
|
||||
if_else(ts_delay(mdl77_400_rdsale, 252) > 0, rank(software_services_exposure_score), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_sum(mdl77_400_rdsale, 252) |
||||
|
||||
rank(ts_sum(mdl77_400_rdsale, 126)) |
||||
|
||||
subtract(rank(software_services_exposure_score), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_scale(mdl77_400_rdsale, 252) |
||||
|
||||
group_zscore(software_services_exposure_score, oth455_customer_n2v_p10_q50_w1_pca_fact3_cluster_10) |
||||
|
||||
ts_delta(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_delta(mdl77_400_rdsale, 252)) |
||||
|
||||
if_else(mdl77_400_rdsale > group_mean(mdl77_400_rdsale, technology_pca_factor1_grouping5), rank(software_services_exposure_score), 0) |
||||
|
||||
multiply(ts_delay(mdl77_400_rdsale, 252), rank(software_services_exposure_score)) |
||||
|
||||
ts_av_diff(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_av_diff(mdl77_400_rdsale, 252)) |
||||
|
||||
add(ts_mean(mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
group_scale(mdl77_400_rdsale, technology_pca_factor1_grouping5) |
||||
|
||||
ts_product(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_product(mdl77_400_rdsale, 252)) |
||||
|
||||
if_else(ts_rank(mdl77_400_rdsale, 252) > 0.5, rank(software_services_exposure_score), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_corr(mdl77_400_rdsale, software_services_exposure_score, 126) |
||||
|
||||
rank(ts_corr(mdl77_400_rdsale, software_services_exposure_score, 252)) |
||||
|
||||
subtract(ts_delay(mdl77_400_rdsale, 252), rank(software_services_exposure_score)) |
||||
|
||||
ts_std_dev(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_std_dev(mdl77_400_rdsale, 252)) |
||||
|
||||
group_zscore(ts_mean(mdl77_400_rdsale, 126), oth455_customer_n2v_p10_q50_w1_pca_fact3_cluster_10) |
||||
|
||||
ts_backfill(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_backfill(mdl77_400_rdsale, 252)) |
||||
|
||||
if_else(group_rank(mdl77_400_rdsale, technology_pca_factor1_grouping5) > 0.5, rank(software_services_exposure_score), 0) |
||||
|
||||
multiply(ts_zscore(mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
ts_decay_linear(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_decay_linear(mdl77_400_rdsale, 252)) |
||||
|
||||
add(ts_delta(mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
group_neutralize(ts_delay(mdl77_400_rdsale, 252), technology_pca_factor1_grouping5) |
||||
|
||||
ts_count_nans(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_count_nans(mdl77_400_rdsale, 252) |
||||
|
||||
if_else(ts_sum(mdl77_400_rdsale, 252) > ts_mean(mdl77_400_rdsale, 252), rank(software_services_exposure_score), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_covariance(mdl77_400_rdsale, software_services_exposure_score, 126) |
||||
|
||||
rank(ts_covariance(mdl77_400_rdsale, software_services_exposure_score, 252)) |
||||
|
||||
subtract(ts_scale(mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
ts_arg_max(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_arg_max(mdl77_400_rdsale, 252)) |
||||
|
||||
group_zscore(ts_delay(mdl77_400_rdsale, 126), oth455_partner_n2v_p50_q200_w2_kmeans_cluster_10) |
||||
|
||||
ts_regression(mdl77_400_rdsale, software_services_exposure_score, 126, 0, 0) |
||||
|
||||
rank(ts_regression(mdl77_400_rdsale, software_services_exposure_score, 252, 0, 0)) |
||||
|
||||
if_else(ts_av_diff(mdl77_400_rdsale, 252) > 0, rank(software_services_exposure_score), 0) |
||||
|
||||
multiply(ts_std_dev(mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
ts_quantile(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_quantile(mdl77_400_rdsale, 252)) |
||||
|
||||
add(ts_product(mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
group_rank(ts_mean(mdl77_400_rdsale, 126), technology_pca_factor1_grouping5) |
||||
|
||||
ts_arg_min(mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_arg_min(mdl77_400_rdsale, 252)) |
||||
|
||||
if_else(ts_corr(mdl77_400_rdsale, software_services_exposure_score, 252) > 0, rank(software_services_exposure_score), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_delay(software_services_exposure_score, 252) |
||||
|
||||
rank(ts_delay(software_services_exposure_score, 126)) |
||||
|
||||
subtract(ts_decay_linear(mdl77_400_rdsale, 252), rank(software_services_exposure_score)) |
||||
|
||||
group_zscore(ts_sum(mdl77_400_rdsale, 126), oth455_customer_n2v_p10_q200_w5_pca_fact2_cluster_20) |
||||
|
||||
ts_mean(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_mean(software_services_exposure_score, 252)) |
||||
|
||||
if_else(ts_backfill(mdl77_400_rdsale, 252) > 0, rank(software_services_exposure_score), 0) |
||||
|
||||
multiply(ts_count_nans(mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
ts_delta(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_delta(software_services_exposure_score, 252)) |
||||
|
||||
add(ts_covariance(mdl77_400_rdsale, software_services_exposure_score, 126), rank(software_services_exposure_score)) |
||||
|
||||
group_neutralize(ts_scale(mdl77_400_rdsale, 126), technology_pca_factor1_grouping5) |
||||
|
||||
ts_std_dev(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_std_dev(software_services_exposure_score, 252)) |
||||
|
||||
if_else(ts_arg_max(mdl77_400_rdsale, 252) == 0, rank(software_services_exposure_score), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_zscore(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_zscore(software_services_exposure_score, 252)) |
||||
|
||||
subtract(ts_regression(mdl77_400_rdsale, software_services_exposure_score, 252, 0, 0), rank(software_services_exposure_score)) |
||||
|
||||
group_zscore(ts_delay(software_services_exposure_score, 126), oth455_partner_n2v_p10_q200_w3_pca_fact3_cluster_5) |
||||
|
||||
ts_av_diff(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_av_diff(software_services_exposure_score, 252)) |
||||
|
||||
if_else(ts_quantile(mdl77_400_rdsale, 252) > 0.5, rank(software_services_exposure_score), 0) |
||||
|
||||
multiply(ts_arg_min(mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
ts_sum(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_sum(software_services_exposure_score, 252)) |
||||
|
||||
add(ts_delay(software_services_exposure_score, 126), rank(mdl77_400_rdsale)) |
||||
|
||||
group_rank(ts_delta(software_services_exposure_score, 126), technology_pca_factor1_grouping5) |
||||
|
||||
ts_product(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_product(software_services_exposure_score, 252)) |
||||
|
||||
if_else(ts_mean(software_services_exposure_score, 252) > 0, rank(software_services_exposure_score), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_corr(software_services_exposure_score, mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_corr(software_services_exposure_score, mdl77_400_rdsale, 252)) |
||||
|
||||
subtract(ts_std_dev(software_services_exposure_score, 126), rank(mdl77_400_rdsale)) |
||||
|
||||
group_zscore(ts_sum(software_services_exposure_score, 126), oth455_customer_n2v_p50_q50_w1_pca_fact3_cluster_10) |
||||
|
||||
ts_backfill(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_backfill(software_services_exposure_score, 252)) |
||||
|
||||
if_else(ts_zscore(software_services_exposure_score, 252) > 0, rank(software_services_exposure_score), 0) |
||||
|
||||
multiply(ts_av_diff(software_services_exposure_score, 126), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_decay_linear(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_decay_linear(software_services_exposure_score, 252)) |
||||
|
||||
add(ts_corr(software_services_exposure_score, mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
group_neutralize(ts_product(software_services_exposure_score, 126), technology_pca_factor1_grouping5) |
||||
|
||||
ts_count_nans(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_count_nans(software_services_exposure_score, 252)) |
||||
|
||||
if_else(ts_sum(software_services_exposure_score, 252) > ts_mean(software_services_exposure_score, 252), rank(software_services_exposure_score), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_covariance(software_services_exposure_score, mdl77_400_rdsale, 126) |
||||
|
||||
rank(ts_covariance(software_services_exposure_score, mdl77_400_rdsale, 252)) |
||||
|
||||
subtract(ts_backfill(software_services_exposure_score, 126), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_arg_max(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_arg_max(software_services_exposure_score, 252)) |
||||
|
||||
group_zscore(ts_decay_linear(software_services_exposure_score, 126), oth455_partner_n2v_p50_q50_w3_kmeans_cluster_5) |
||||
|
||||
ts_regression(software_services_exposure_score, mdl77_400_rdsale, 126, 0, 0) |
||||
|
||||
rank(ts_regression(software_services_exposure_score, mdl77_400_rdsale, 252, 0, 0)) |
||||
|
||||
if_else(ts_count_nans(software_services_exposure_score, 252) == 0, rank(software_services_exposure_score), 0) |
||||
|
||||
multiply(ts_arg_max(software_services_exposure_score, 126), rank(mdl77_400_rdsale)) |
||||
|
||||
ts_quantile(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_quantile(software_services_exposure_score, 252)) |
||||
|
||||
add(ts_covariance(software_services_exposure_score, mdl77_400_rdsale, 126), rank(software_services_exposure_score)) |
||||
|
||||
group_rank(ts_backfill(software_services_exposure_score, 126), technology_pca_factor1_grouping5) |
||||
|
||||
ts_arg_min(software_services_exposure_score, 126) |
||||
|
||||
rank(ts_arg_min(software_services_exposure_score, 252)) |
||||
@ -0,0 +1,81 @@ |
||||
ts_delay(oth455_customer_n2v_p10_q50_w1_pca_fact3_cluster_10, 6) |
||||
ts_delay(oth455_partner_n2v_p50_q200_w2_kmeans_cluster_10, 9) |
||||
ts_delay(oth455_customer_roam_w1_pca_fact3_cluster_5, 12) |
||||
ts_delay(oth455_partner_roam_w5_pca_fact3_cluster_20, 6) |
||||
ts_delay(oth455_customer_n2v_p50_q50_w4_kmeans_cluster_5, 9) |
||||
ts_delay(oth455_partner_n2v_p10_q200_w2_pca_fact2_cluster_20, 12) |
||||
ts_delay(oth455_customer_n2v_p10_q200_w5_pca_fact3_cluster_5, 6) |
||||
ts_delay(oth455_partner_n2v_p50_q50_w3_kmeans_cluster_20, 9) |
||||
ts_delay(oth455_customer_roam_w4_kmeans_cluster_10, 12) |
||||
ts_delay(oth455_partner_roam_w4_kmeans_cluster_10, 6) |
||||
ts_delay(oth455_customer_n2v_p50_q50_w1_pca_fact3_cluster_10, 9) |
||||
ts_delay(oth455_partner_n2v_p50_q200_w1_kmeans_cluster_10, 12) |
||||
ts_delay(oth455_customer_n2v_p10_q50_w2_pca_fact2_cluster_10, 6) |
||||
ts_delay(oth455_partner_n2v_p10_q50_w3_pca_fact1_cluster_5, 9) |
||||
ts_delay(oth455_customer_n2v_p10_q200_w3_pca_fact1_cluster_10, 12) |
||||
ts_delay(oth455_partner_n2v_p10_q200_w3_pca_fact3_cluster_5, 6) |
||||
ts_delay(oth455_customer_n2v_p50_q50_w3_kmeans_cluster_5, 9) |
||||
ts_delay(oth455_customer_n2v_p10_q200_w3_pca_fact3_cluster_20, 12) |
||||
ts_delay(oth455_customer_roam_w3_pca_fact2_cluster_5, 6) |
||||
ts_delay(oth455_partner_n2v_p10_q50_w5_pca_fact2_cluster_10, 9) |
||||
ts_delay(oth455_customer_n2v_p10_q50_w2_pca_fact2_cluster_10, 12) |
||||
ts_delay(oth455_partner_n2v_p50_q200_w2_kmeans_cluster_10, 6) |
||||
ts_delay(oth455_customer_n2v_p50_q200_w1_pca_fact2_cluster_20, 9) |
||||
ts_delay(oth455_partner_roam_w3_kmeans_cluster_5, 12) |
||||
ts_delay(oth455_customer_roam_w4_kmeans_cluster_10, 6) |
||||
ts_delay(oth455_partner_n2v_p10_q200_w5_pca_fact2_cluster_10, 9) |
||||
ts_delay(oth455_customer_n2v_p10_q200_w3_pca_fact1_cluster_10, 12) |
||||
ts_delay(oth455_partner_n2v_p10_q50_w2_kmeans_cluster_5, 6) |
||||
ts_delay(oth455_customer_n2v_p50_q50_w3_pca_fact3_cluster_20, 9) |
||||
ts_delay(oth455_partner_roam_w5_pca_fact3_cluster_20, 12) |
||||
ts_delay(oth455_customer_n2v_p10_q50_w3_pca_fact3_cluster_20, 6) |
||||
ts_delay(oth455_partner_n2v_p50_q50_w4_kmeans_cluster_5, 9) |
||||
ts_delay(oth455_customer_n2v_p50_q200_w5_pca_fact3_cluster_5, 12) |
||||
ts_delay(oth455_partner_n2v_p10_q50_w3_pca_fact1_cluster_5, 6) |
||||
ts_delay(oth455_customer_n2v_p10_q200_w5_pca_fact3_cluster_10, 9) |
||||
ts_delay(oth455_partner_n2v_p50_q200_w1_kmeans_cluster_10, 12) |
||||
ts_delay(oth455_customer_roam_w3_pca_fact2_cluster_5, 6) |
||||
ts_delay(oth455_partner_n2v_p10_q200_w3_pca_fact3_cluster_5, 9) |
||||
ts_delay(oth455_customer_n2v_p50_q50_w1_pca_fact3_cluster_10, 12) |
||||
ts_delay(oth455_partner_roam_w4_kmeans_cluster_10, 6) |
||||
ts_delay(oth455_customer_n2v_p10_q50_w2_pca_fact2_cluster_10, 9) |
||||
ts_delay(oth455_partner_n2v_p50_q200_w2_kmeans_cluster_10, 12) |
||||
ts_delay(oth455_customer_n2v_p50_q50_w3_kmeans_cluster_5, 6) |
||||
ts_delay(oth455_partner_n2v_p10_q50_w5_pca_fact2_cluster_10, 9) |
||||
ts_delay(oth455_customer_n2v_p10_q200_w3_pca_fact1_cluster_10, 12) |
||||
ts_delay(oth455_partner_n2v_p10_q200_w5_pca_fact2_cluster_10, 6) |
||||
ts_delay(oth455_customer_n2v_p50_q200_w1_pca_fact2_cluster_20, 9) |
||||
ts_delay(oth455_partner_roam_w3_kmeans_cluster_5, 12) |
||||
ts_delay(oth455_customer_roam_w4_kmeans_cluster_10, 6) |
||||
ts_delay(oth455_partner_n2v_p50_q50_w3_kmeans_cluster_20, 9) |
||||
ts_delay(oth455_customer_n2v_p10_q50_w3_pca_fact3_cluster_20, 12) |
||||
ts_delay(oth455_partner_n2v_p10_q200_w3_pca_fact1_cluster_5, 6) |
||||
ts_delay(oth455_customer_n2v_p50_q50_w4_kmeans_cluster_5, 9) |
||||
ts_delay(oth455_partner_n2v_p50_q200_w5_pca_fact3_cluster_5, 12) |
||||
ts_delay(oth455_customer_n2v_p10_q200_w5_pca_fact3_cluster_10, 6) |
||||
ts_delay(oth455_partner_n2v_p10_q50_w2_kmeans_cluster_5, 9) |
||||
ts_delay(oth455_customer_n2v_p50_q200_w1_kmeans_cluster_10, 12) |
||||
ts_delay(oth455_partner_roam_w5_pca_fact3_cluster_20, 6) |
||||
ts_delay(oth455_customer_n2v_p10_q50_w3_pca_fact1_cluster_5, 9) |
||||
ts_delay(oth455_partner_n2v_p50_q50_w1_pca_fact3_cluster_10, 12) |
||||
ts_delay(oth455_customer_n2v_p50_q200_w5_pca_fact3_cluster_5, 6) |
||||
ts_delay(oth455_partner_n2v_p10_q200_w3_pca_fact3_cluster_5, 9) |
||||
ts_delay(oth455_customer_roam_w3_pca_fact2_cluster_5, 12) |
||||
ts_delay(oth455_partner_n2v_p50_q50_w3_kmeans_cluster_5, 6) |
||||
ts_delay(oth455_customer_n2v_p10_q50_w2_pca_fact2_cluster_10, 9) |
||||
ts_delay(oth455_partner_n2v_p10_q50_w5_pca_fact2_cluster_10, 12) |
||||
ts_delay(oth455_customer_n2v_p50_q50_w3_pca_fact3_cluster_20, 6) |
||||
ts_delay(oth455_partner_n2v_p50_q200_w1_kmeans_cluster_10, 9) |
||||
ts_delay(oth455_customer_n2v_p10_q200_w3_pca_fact1_cluster_10, 12) |
||||
ts_delay(oth455_partner_n2v_p10_q200_w5_pca_fact2_cluster_10, 6) |
||||
ts_delay(oth455_customer_n2v_p50_q200_w1_pca_fact2_cluster_20, 9) |
||||
ts_delay(oth455_partner_roam_w3_kmeans_cluster_5, 12) |
||||
ts_delay(oth455_customer_roam_w4_kmeans_cluster_10, 6) |
||||
ts_delay(oth455_partner_n2v_p50_q50_w4_kmeans_cluster_5, 9) |
||||
ts_delay(oth455_customer_n2v_p10_q50_w3_pca_fact3_cluster_20, 12) |
||||
ts_delay(oth455_partner_n2v_p10_q200_w3_pca_fact1_cluster_5, 6) |
||||
ts_delay(oth455_customer_n2v_p50_q50_w1_pca_fact3_cluster_10, 9) |
||||
ts_delay(oth455_partner_n2v_p50_q200_w2_kmeans_cluster_10, 12) |
||||
ts_delay(oth455_customer_n2v_p10_q200_w5_pca_fact3_cluster_10, 6) |
||||
ts_delay(oth455_partner_n2v_p10_q50_w2_kmeans_cluster_5, 9) |
||||
ts_delay(oth455_customer_n2v_p50_q200_w5_pca_fact3_cluster_5, 12) |
||||
@ -0,0 +1,77 @@ |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 18)), 37) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 18)), 37) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 9)), 18) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 18)), 37) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 9)), 18) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 4)), 9) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 18)), 37) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 9)), 18) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 4)), 9) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 4) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 18)), 37) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 9)), 18) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 4)), 9) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 4) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 18)), 37) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 9)), 18) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 4)), 9) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 4) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 18)), 37) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 9)), 18) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 4)), 9) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 4) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 18)), 37) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 9)), 18) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 4)), 9) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 4) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
|
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 180), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 240), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 300), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 120)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 60)), 120) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 30)), 60) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 15)), 30) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 7)), 15) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 3)), 7) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 3) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 360), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 150)), 210) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 75)), 150) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 37)), 75) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 18)), 37) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 9)), 18) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 4)), 9) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 4) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
ts_rank(ts_delay(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 420), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 180)), 240) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 90)), 180) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 45)), 90) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 22)), 45) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 11)), 22) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 5)), 11) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 2)), 5) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 1)), 2) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 1) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) * ts_rank(ts_zscore(ts_mean(mdl77_400_rdsale, 0)), 0) |
||||
@ -0,0 +1,518 @@ |
||||
分红可持续性溢价因子 |
||||
假设 |
||||
分红政策稳定且具备可持续性的公司，相较于分红波动剧烈或盲目高分红的公司，更能体现稳健的现金流管理能力与盈利质量，市场会给予长期估值溢价；而分红能力持续弱化、分红率与盈利水平严重不匹配的公司，可能隐藏现金流压力或盈利虚增风险，应规避或建立空头仓位。 |
||||
实施方案 |
||||
构建“分红可持续性评分体系”，核心维度包括：分红率与净利润增速的匹配度、经营活动现金流净额对分红金额的覆盖倍数、近三年分红率波动率、留存收益占比与分红比例的平衡关系。通过时序分析工具测算各维度过去2-3年的趋势变化，对各维度进行标准化打分后加权求和，得到综合可持续性评分。对评分处于行业前30%且趋势持续向好的公司建立多头仓位，对评分处于后30%或趋势快速恶化的公司建立空头仓位。 |
||||
阿尔法因子优化建议 |
||||
1. 按行业特性差异化设定评分权重，例如金融行业现金流稳定性高，可提高现金流覆盖倍数的权重，而成长型行业可侧重留存收益与分红的平衡关系，消除行业属性偏差。2. 引入盈利质量验证因子（如扣非净利润占比、应收账款周转率）作为调节项，当分红可持续性评分与盈利质量指标背离时，降低信号权重，规避盈利虚增支撑分红的伪信号。3. 结合宏观利率周期动态调整因子敏感度，利率上行周期中，市场对分红稳定性要求更高，可放大该因子权重；利率下行周期中，适当降低权重，兼容成长型公司的低分红策略。 |
||||
Dividend Sustainability Premium Factor |
||||
Hypothesis |
||||
Companies with stable and sustainable dividend policies, compared to those with volatile dividends or blindly high dividends, can better reflect robust cash flow management capabilities and profit quality, and the market will grant them a long-term valuation premium. Conversely, companies with continuously weakening dividend capacity and a serious mismatch between dividend rate and profitability may hide cash flow pressures or false profit growth risks, and short positions should be avoided or established. |
||||
Implementation Plan |
||||
Construct a "dividend sustainability scoring system" with core dimensions including: the matching degree between dividend rate and net profit growth rate, the coverage multiple of operating cash flow net to dividend amount, the volatility of dividend rate in the past three years, and the balance between retained earnings ratio and dividend ratio. Use time-series analysis tools to measure the trend changes of each dimension over the past 2-3 years, standardize and score each dimension, then weight and sum to obtain a comprehensive sustainability score. Establish long positions in companies whose scores are in the top 30% of the industry with a continuously improving trend, and establish short positions in companies whose scores are in the bottom 30% or whose trends are deteriorating rapidly. |
||||
Alpha Factor Optimization Suggestions |
||||
1. Differentiate scoring weights according to industry characteristics. For example, the financial industry has high cash flow stability, so the weight of cash flow coverage multiple can be increased, while growth-oriented industries can focus on the balance between retained earnings and dividends to eliminate industry attribute deviations. 2. Introduce profit quality verification factors (such as the proportion of non-recurring net profit, accounts receivable turnover rate) as adjustment items. When there is a divergence between the dividend sustainability score and profit quality indicators, reduce the signal weight to avoid false signals of dividends supported by false profit growth. 3. Dynamically adjust factor sensitivity in conjunction with the macro interest rate cycle. In the interest rate upward cycle, the market has higher requirements for dividend stability, so the weight of this factor can be amplified; in the interest rate downward cycle, the weight can be appropriately reduced to be compatible with the low-dividend strategy of growth-oriented companies. |
||||
|
||||
*=========================================================================================* |
||||
输出格式： |
||||
输出必须是且仅是纯文本。 |
||||
每一行是一个完整、独立、语法正确的WebSim表达式。 |
||||
严禁任何形式的解释、编号、标点包裹（如引号）、Markdown格式或额外文本。 |
||||
===================== !!! 重点(输出方式) !!! ===================== |
||||
现在，请严格遵守以上所有规则，开始生成可立即在WebSim中运行的复合因子表达式。 |
||||
不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 |
||||
**输出格式**(一行一个表达式, 每个表达式中间需要添加一个空行, 只要表达式本身, 不需要赋值, 不要解释, 不需要序号, 也不要输出多余的东西)： |
||||
表达式 |
||||
表达式 |
||||
表达式 |
||||
... |
||||
表达式 |
||||
================================================================= |
||||
重申：请确保所有表达式都使用WorldQuant WebSim平台函数，不要使用pandas、numpy或其他Python库函数。输出必须是一行有效的WQ表达式。 |
||||
以下是我的账号有权限使用的操作符, 请严格按照操作符, 以及我提供的数据集, 进行生成,组合 100 个 alpha： |
||||
不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 |
||||
================================================================= |
||||
ts_product ts_zscore ts_mean ts_scale add sign subtract ts_delta ts_rank greater ts_av_diff ts_quantile ts_count_nans ts_covariance |
||||
ts_arg_min divide ts_corr multiply if_else ts_sum ts_delay group_zscore ts_arg_max ts_std_de ts_backfill |
||||
以上这些操作符不能传入事件类型的数据集, 只能传入时间序列数据集, 不能传入事件数据,不能传入事件数据,不能传入事件数据 |
||||
|
||||
以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子 |
||||
|
||||
========================= 操作符开始 ======================================= |
||||
注意: Operator: 后面的是操作符(是可以使用的), |
||||
Description: 此字段后面的是操作符对应的描述或使用说明(禁止使用, 仅供参考), Description字段后面的内容是使用说明, 不是操作符 |
||||
特别注意!!!! 必须按照操作符字段Operator的使用说明生成 alphaOperator: abs(x) |
||||
Description: Absolute value of x |
||||
Operator: add(x, y, filter = false) |
||||
Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding |
||||
Operator: densify(x) |
||||
Description: Converts a grouping field of many buckets into lesser number of only available buckets so as to make working with grouping fields computationally efficient |
||||
Operator: divide(x, y) |
||||
Description: x / y |
||||
Operator: inverse(x) |
||||
Description: 1 / x |
||||
Operator: log(x) |
||||
Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights. |
||||
Operator: max(x, y, ..) |
||||
Description: Maximum value of all inputs. At least 2 inputs are required |
||||
Operator: min(x, y ..) |
||||
Description: Minimum value of all inputs. At least 2 inputs are required |
||||
Operator: multiply(x ,y, ... , filter=false) |
||||
Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1 |
||||
Operator: power(x, y) |
||||
Description: x ^ y |
||||
Operator: reverse(x) |
||||
Description: - x |
||||
Operator: sign(x) |
||||
Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN; |
||||
Operator: signed_power(x, y) |
||||
Description: x raised to the power of y such that final result preserves sign of x |
||||
Operator: sqrt(x) |
||||
Description: Square root of x |
||||
Operator: subtract(x, y, filter=false) |
||||
Description: x-y. If filter = true, filter all input NaN to 0 before subtracting |
||||
Operator: and(input1, input2) |
||||
Description: Logical AND operator, returns true if both operands are true and returns false otherwise |
||||
Operator: if_else(input1, input2, input 3) |
||||
Description: If input1 is true then return input2 else return input3. |
||||
Operator: input1 < input2 |
||||
Description: If input1 < input2 return true, else return false |
||||
Operator: input1 <= input2 |
||||
Description: Returns true if input1 <= input2, return false otherwise |
||||
Operator: input1 == input2 |
||||
Description: Returns true if both inputs are same and returns false otherwise |
||||
Operator: input1 > input2 |
||||
Description: Logic comparison operators to compares two inputs |
||||
Operator: input1 >= input2 |
||||
Description: Returns true if input1 >= input2, return false otherwise |
||||
Operator: input1!= input2 |
||||
Description: Returns true if both inputs are NOT the same and returns false otherwise |
||||
Operator: is_nan(input) |
||||
Description: If (input == NaN) return 1 else return 0 |
||||
Operator: not(x) |
||||
Description: Returns the logical negation of x. If x is true (1), it returns false (0), and if input is false (0), it returns true (1). |
||||
Operator: or(input1, input2) |
||||
Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise |
||||
Operator: days_from_last_change(x) |
||||
Description: Amount of days since last change of x |
||||
Operator: hump(x, hump = 0.01) |
||||
Description: Limits amount and magnitude of changes in input (thus reducing turnover) |
||||
Operator: kth_element(x, d, k) |
||||
Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1 |
||||
Operator: last_diff_value(x, d) |
||||
Description: Returns last x value not equal to current x value from last d days |
||||
Operator: ts_arg_max(x, d) |
||||
Description: Returns the relative index of the max value in the time series for the past d days. If the current day has the max value for the past d days, it returns 0. If previous day has the max value for the past d days, it returns 1 |
||||
Operator: ts_arg_min(x, d) |
||||
Description: Returns the relative index of the min value in the time series for the past d days; If the current day has the min value for the past d days, it returns 0; If previous day has the min value for the past d days, it returns 1. |
||||
Operator: ts_av_diff(x, d) |
||||
Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation |
||||
Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN") |
||||
Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value) |
||||
Operator: ts_corr(x, y, d) |
||||
Description: Returns correlation of x and y for the past d days |
||||
Operator: ts_count_nans(x ,d) |
||||
Description: Returns the number of NaN values in x for the past d days |
||||
Operator: ts_covariance(y, x, d) |
||||
Description: Returns covariance of y and x for the past d days |
||||
Operator: ts_decay_linear(x, d, dense = false) |
||||
Description: Returns the linear decay on x for the past d days. Dense parameter=false means operator works in sparse mode and we treat NaN as 0. In dense mode we do not. |
||||
Operator: ts_delay(x, d) |
||||
Description: Returns x value d days ago |
||||
Operator: ts_delta(x, d) |
||||
Description: Returns x - ts_delay(x, d) |
||||
Operator: ts_mean(x, d) |
||||
Description: Returns average value of x for the past d days. |
||||
Operator: ts_product(x, d) |
||||
Description: Returns product of x for the past d days |
||||
Operator: ts_quantile(x,d, driver="gaussian" ) |
||||
Description: It calculates ts_rank and apply to its value an inverse cumulative density function from driver distribution. Possible values of driver (optional ) are "gaussian", "uniform", "cauchy" distribution where "gaussian" is the default. |
||||
Operator: ts_rank(x, d, constant = 0) |
||||
Description: Rank the values of x for each instrument over the past d days, then return the rank of the current value + constant. If not specified, by default, constant = 0. |
||||
Operator: ts_regression(y, x, d, lag = 0, rettype = 0) |
||||
Description: Returns various parameters related to regression function |
||||
Operator: ts_scale(x, d, constant = 0) |
||||
Description: Returns (x - ts_min(x, d)) / (ts_max(x, d) - ts_min(x, d)) + constant. This operator is similar to scale down operator but acts in time series space |
||||
Operator: ts_std_dev(x, d) |
||||
Description: Returns standard deviation of x for the past d days |
||||
Operator: ts_step(1) |
||||
Description: Returns days' counter |
||||
Operator: ts_sum(x, d) |
||||
Description: Sum values of x for the past d days. |
||||
Operator: ts_zscore(x, d) |
||||
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean: (x - tsmean(x,d)) / tsstddev(x,d). This operator may help reduce outliers and drawdown. |
||||
Operator: normalize(x, useStd = false, limit = 0.0) |
||||
Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element |
||||
Operator: quantile(x, driver = gaussian, sigma = 1.0) |
||||
Description: Rank the raw vector, shift the ranked Alpha vector, apply distribution (gaussian, cauchy, uniform). If driver is uniform, it simply subtract each Alpha value with the mean of all Alpha values in the Alpha vector |
||||
Operator: rank(x, rate=2) |
||||
Description: Ranks the input among all the instruments and returns an equally distributed number between 0.0 and 1.0. For precise sort, use the rate as 0 |
||||
Operator: scale(x, scale=1, longscale=1, shortscale=1) |
||||
Description: Scales input to booksize. We can also scale the long positions and short positions to separate scales by mentioning additional parameters to the operator |
||||
Operator: winsorize(x, std=4) |
||||
Description: Winsorizes x to make sure that all values in x are between the lower and upper limits, which are specified as multiple of std. |
||||
Operator: zscore(x) |
||||
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean |
||||
Operator: vec_avg(x) |
||||
Description: Taking mean of the vector field x |
||||
Operator: vec_sum(x) |
||||
Description: Sum of vector field x |
||||
Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10") |
||||
Description: Convert float values into indexes for user-specified buckets. Bucket is useful for creating group values, which can be passed to GROUP as input |
||||
Operator: trade_when(x, y, z) |
||||
Description: Used in order to change Alpha values only under a specified condition and to hold Alpha values in other cases. It also allows to close Alpha positions (assign NaN values) under a specified condition |
||||
Operator: group_backfill(x, group, d, std = 4.0) |
||||
Description: If a certain value for a certain date and instrument is NaN, from the set of same group instruments, calculate winsorized mean of all non-NaN values over last d days |
||||
Operator: group_mean(x, weight, group) |
||||
Description: All elements in group equals to the mean |
||||
Operator: group_neutralize(x, group) |
||||
Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant |
||||
Operator: group_rank(x, group) |
||||
Description: Each elements in a group is assigned the corresponding rank in this group |
||||
Operator: group_scale(x, group) |
||||
Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin) |
||||
Operator: group_zscore(x, group) |
||||
Description: Calculates group Z-score - numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. zscore = (data - mean) / stddev of x for each instrument within its group. |
||||
========================= 操作符结束 ======================================= |
||||
|
||||
========================= 数据字段开始 ======================================= |
||||
注意: data_set_name: 后面的是数据字段(可以使用), description: 此字段后面的是数据字段对应的描述或使用说明(不能使用) |
||||
|
||||
{'data_set_name': '可以使用:oth567_trendrating_work_life_balance_448', 'description': '不可使用,仅供参考:rating of work-life balance (1 to 5'} |
||||
{'data_set_name': '可以使用:mdl264_long_zone_juice_l2', 'description': '不可使用,仅供参考:The probability that the future trend of "The Seasonal Cycle at the End of the Current Long Zone Minus the Seasonal Cycle" will be neutral'} |
||||
{'data_set_name': '可以使用:mdl177_2_industryrrelativevaluefactor_curindfcfp_', 'description': "不可使用,仅供参考:Industry Relative TTM Free Cash Flow-to-Price : It is defined as a stock's trailing 12-month free cash flow-to-price ratio (FCFP) less the average of the FCFPs of all stocks in the same industry deflated by the standard deviation of the FCFPs of all stocks in the same relative universe"} |
||||
{'data_set_name': '可以使用:fnd72_pit_or_is_q_is_net_inc_avail_com_shrhldrs', 'description': '不可使用,仅供参考:Net Income Available To Common Shareholders'} |
||||
{'data_set_name': '可以使用:mdl77_2globaldevnorthamericasensitivityfactor_pi', 'description': '不可使用,仅供参考:Industrial Production Sensitivity: It is defined as the beta coefficient to Change in Industrial Production, which is estimated by a 60-month multiple regression of returns on several macroeconomic factors.'} |
||||
{'data_set_name': '可以使用:rsk62_beta_factor_5_100_growth', 'description': '不可使用,仅供参考:eps growth'} |
||||
{'data_set_name': '可以使用:top500_industry_grouping_method4_50', 'description': '不可使用,仅供参考:Industry grouping for top 500 securities using method 4 with 50 clusters.'} |
||||
{'data_set_name': '可以使用:top_300_equity_513_grouping_50_clusters', 'description': '不可使用,仅供参考:Grouping of top 300 equities (513 variant) using 50 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_buy_notional_sum', 'description': '不可使用,仅供参考:No field description'} |
||||
{'data_set_name': '可以使用:pv87_v2_expavg20_group_event_sentiment_score_earnings', 'description': '不可使用,仅供参考:20-day Exponential average of Event Sentiment Score for group Earnings'} |
||||
{'data_set_name': '可以使用:top1000_pca_factor4_grouping50', 'description': '不可使用,仅供参考:Fourth principal component grouping for top 1000 securities with 50 clusters.'} |
||||
{'data_set_name': '可以使用:fnd6_txndbl', 'description': '不可使用,仅供参考:Net Deferred Tax Liability'} |
||||
{'data_set_name': '可以使用:mdl177_earningmomentumfactor_rev6_alt', 'description': '不可使用,仅供参考:Averaged Last 6-M EPS Revisions for FY1'} |
||||
{'data_set_name': '可以使用:rsk59_short_interest', 'description': '不可使用,仅供参考:Real-time short interest expressed in number of shares'} |
||||
{'data_set_name': '可以使用:industrial_pca_factor3_grouping20', 'description': '不可使用,仅供参考:Third principal component grouping for industrial sector with 20 clusters.'} |
||||
{'data_set_name': '可以使用:parkinson_volatility_180', 'description': "不可使用,仅供参考:Parkinson model's historical volatility over 180 days"} |
||||
{'data_set_name': '可以使用:pv87_neg_earnings_matrix_event_sentiment_score_mean', 'description': '不可使用,仅供参考:Mean of Event Sentiment Score for type Negearnings'} |
||||
{'data_set_name': '可以使用:oth699_usertype_24', 'description': '不可使用,仅供参考:the user subscription level on TipRanks – Basic / Premium or Ultimate. Note that a single user can have different plans at different times based on when their subscription expires or is renewed.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple28d_ew_sent_z_tsrank', 'description': '不可使用,仅供参考:28-day Simple average of End-of-day time series rank of Sentiment'} |
||||
{'data_set_name': '可以使用:opt40_call_volatility_365days', 'description': '不可使用,仅供参考:Volatility for call options with 365 days to expiration.'} |
||||
{'data_set_name': '可以使用:pv20_net_indicator_7_feature7', 'description': '不可使用,仅供参考:[Features heuristically extracted from ibes modules of Pre-tax Profit] [Quarter 2] [Non-trivial feature]'} |
||||
{'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_p1_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Pretax Profit'} |
||||
{'data_set_name': '可以使用:mdl77_2earningmomentumfactor400_qepsferr', 'description': "不可使用,仅供参考:Prior Fiscal Quarter Forecast Error: It is defined as the difference between the actual earnings per share and consensus forecast scaled by the stock's price at the beginning of the quarter."} |
||||
{'data_set_name': '可以使用:mdl77_industryrrelativevaluefactor_curindfcfp_', 'description': "不可使用,仅供参考:Industry Relative TTM Free Cash Flow-to-Price: It is defined as a stock's trailing 12-month free cash flow-to-price ratio (FCFP) less the average of the FCFPs of all stocks in the same industry deflated by the standard deviation of the FCFPs of all stocks in the same relative universe."} |
||||
{'data_set_name': '可以使用:fnd72_a1_cont_inc_growth', 'description': '不可使用,仅供参考:A percentage increase or decrease of income before extraordinary items by comparing current period with the same period prior year'} |
||||
{'data_set_name': '可以使用:mdl77_liquidityriskfactor_pcurlia', 'description': "不可使用,仅供参考:Current Liabilities-to-Price: It is defined as a stock's most recently reported quarterly current liabilities per share divided by its closing price."} |
||||
{'data_set_name': '可以使用:oth567score_diversity_and_inclusion_325', 'description': '不可使用,仅供参考:Score for diversity and inclusion'} |
||||
{'data_set_name': '可以使用:pv87_2_cfps_qf_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:anl14_low_ebit_fp3', 'description': '不可使用,仅供参考:The Lowest Estimation of Earnings Before Interest & Taxes - Upcoming 3 Quarters'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_simple28d_ew_sent_std_range', 'description': '不可使用,仅供参考:28-day Simple average of Range of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:pv87_webweightedavg1_group_ess_dividends', 'description': '不可使用,仅供参考:1-day Weighted average of ESS - Event Sentiment Score for group Dividends'} |
||||
{'data_set_name': '可以使用:anl69_ebit_expected_report_time', 'description': '不可使用,仅供参考:Expected Earnings Report Time'} |
||||
{'data_set_name': '可以使用:est_q_pre_low_3mth_ago', 'description': '不可使用,仅供参考:Lowest analyst estimate of pre-tax profit regarding the next quarter, made in the past 3 months'} |
||||
{'data_set_name': '可以使用:mdl177_earningsqualityfactor_salegpm_alt', 'description': '不可使用,仅供参考:Change in QTR Sales vsGross Margin : It is defined as the difference between the yearly change in most recent reported quarterly sales and the yearly change in the quarterly gross profit margin.'} |
||||
{'data_set_name': '可以使用:avg_culture_values_score', 'description': '不可使用,仅供参考:Average rating for company culture and values.'} |
||||
{'data_set_name': '可以使用:mdl177_earningmomentumfactor_rev1q1_alt', 'description': '不可使用,仅供参考:Revision in Fiscal QTR 1 EPS Forecasts'} |
||||
{'data_set_name': '可以使用:rsk62_industry_5_100_val34', 'description': '不可使用,仅供参考:Industry return'} |
||||
{'data_set_name': '可以使用:fnd72_q2_other_ins_res_to_shrhldr_eqy', 'description': '不可使用,仅供参考:Measure of other operating reserves to total liabilities and equity'} |
||||
{'data_set_name': '可以使用:est_q_prr_low_4wks_ago', 'description': '不可使用,仅供参考:Lowest analyst estimate of pretax profit as reported regarding the next quarter, made in the past 4 weeks'} |
||||
{'data_set_name': '可以使用:pv87_prv2_expavg20_group_css_earnings', 'description': '不可使用,仅供参考:20-day Exponential average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Earnings'} |
||||
{'data_set_name': '可以使用:pv87_v2_expavg60_group_event_sentiment_score_legal', 'description': '不可使用,仅供参考:60-day Exponential average of Event Sentiment Score for group Legal'} |
||||
{'data_set_name': '可以使用:pv13_h_min2_focused_pureplay_3000_sector', 'description': '不可使用,仅供参考:grouping fields'} |
||||
{'data_set_name': '可以使用:mdl177_2_earningmomentumfactor400_salesurp', 'description': '不可使用,仅供参考:Sales Surprise'} |
||||
{'data_set_name': '可以使用:forecast_currency_dividend_per_share', 'description': '不可使用,仅供参考:Currency in which the dividend per share forecast is denominated.'} |
||||
{'data_set_name': '可以使用:pv87_webv2_simpleavg20_group_event_sentiment_score_credit', 'description': '不可使用,仅供参考:20-day Simple average of Event Sentiment Score for group Credit'} |
||||
{'data_set_name': '可以使用:fnd65_allcap_sedol_reinrate', 'description': '不可使用,仅供参考:It is defined as the trailing 12-month earnings per share before extra items minus the trailing 12-month dividends per share by ex-date divided by the average book equity per share in the same period.'} |
||||
{'data_set_name': '可以使用:mdl77_earningmomentumfactor_y3sur', 'description': '不可使用,仅供参考:Volatility-adj 3-yr Projected EPS Growth: It is defined as the consensus earnings forecast for the current quarter minus the actual quarterly earnings 12 quarters ago, deflated by the standard deviation of the actual quarterly earnings.'} |
||||
{'data_set_name': '可以使用:pv87_v2_simpleavg20_group_css_marketing', 'description': '不可使用,仅供参考:20-day Simple average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Marketing'} |
||||
{'data_set_name': '可以使用:oth432_cheq_profitability_profitability1', 'description': '不可使用,仅供参考:1st profitability field of Cash and Short-term Investments'} |
||||
{'data_set_name': '可以使用:mdl262_rasv2splitprofitabilityni_ttm_profitability11', 'description': '不可使用,仅供参考:11th Profitability field of Net Income, Trailing 12 Months'} |
||||
{'data_set_name': '可以使用:pv173_rawratiosmt5yzspreadchgstd20dsbst', 'description': '不可使用,仅供参考:It is defined as the 20-day standard deviation of changeIn 5-year mid z-spreadIn the bond z-spread curve'} |
||||
{'data_set_name': '可以使用:mdl177_earningsqualityfactor_uar', 'description': "不可使用,仅供参考:Unexpected Change in Accounts Receivable : It is defined as the difference between current accounts receivable and the expected level of accounts receivable (multiplying the prior year's closing account balance by the growth in sales in the trailing 12-months) scaled by the total assets."} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_ew_sent_mean_median', 'description': '不可使用,仅供参考:7-day Volume weighted average of Median of Sentiment Average'} |
||||
{'data_set_name': '可以使用:pv87_v2_simpleavg20_topic_nip_society', 'description': '不可使用,仅供参考:20-day Simple average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for topic Society'} |
||||
{'data_set_name': '可以使用:implied_volatility_mean_skew_60', 'description': '不可使用,仅供参考:At-the-money option-implied volatility mean skew for 60 days'} |
||||
{'data_set_name': '可以使用:fnd3_q_goodwill', 'description': '不可使用,仅供参考:Quarterly Goodwill'} |
||||
{'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on delta of annual net income'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_ew_sent_std_daydiff', 'description': '不可使用,仅供参考:14-day Volume weighted average of Daily difference of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:mdl262_rtlr_q_profitability_profitability1', 'description': '不可使用,仅供参考:1st profitability field of Total Revenue'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg20_group_css_revenues', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Revenues'} |
||||
{'data_set_name': '可以使用:mdl177_2_globaldevnorthamerica_v502_chgalpha36m', 'description': "不可使用,仅供参考:6-Month Nominal Change in 36-Month Alpha : It is defined as the 6-month change in a stock's 36-month alpha, which equals the intercept from the regression of a stock price's monthly return against the S&P 500 index monthly return over last 36-month period."} |
||||
{'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_degree_financial_leverage', 'description': "不可使用,仅供参考:Leverage ratio summarizing the effect a particular amount of financial leverage has on a company's earnings"} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_mean_std', 'description': '不可使用,仅供参考:14-day Volume weighted average of Standard deviation of Sentiment Average'} |
||||
{'data_set_name': '可以使用:fnd72_pit_or_is_q_is_inc_tax_exp_other_comp_inc', 'description': '不可使用,仅供参考:Income Tax Expense - Other Comprehensive Income'} |
||||
{'data_set_name': '可以使用:anl10_prrinnovation_score_fy2_2577', 'description': '不可使用,仅供参考:Innovation score for price return ratio FY2 (innovate_increase - innovate_decrease)'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oivegacall3', 'description': '不可使用,仅供参考:vega of out call options'} |
||||
{'data_set_name': '可以使用:anl4_fcfps_low', 'description': '不可使用,仅供参考:Free Cash Flow Per Share - the lowest estimation'} |
||||
{'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv64_dif_dvd_declared_dt', 'description': '不可使用,仅供参考:The date on which a company announces a dividend distribution.'} |
||||
{'data_set_name': '可以使用:est_q_dps_high_3mth_ago', 'description': '不可使用,仅供参考:Highest analyst estimate of dividend per share regarding the next quarter, made in past 3 months'} |
||||
{'data_set_name': '可以使用:historical_volatility_20', 'description': '不可使用,仅供参考:Close-to-close Historical volatility over 20 days'} |
||||
{'data_set_name': '可以使用:short_term_notes_commercial_credit', 'description': '不可使用,仅供参考:Short-term notes and commercial credit outstanding.'} |
||||
{'data_set_name': '可以使用:principal_component_score_6_top3000', 'description': '不可使用,仅供参考:Value of the sixth principal component for the top 3000 securities.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_ew_sent_std_median', 'description': '不可使用,仅供参考:28-day Volume weighted average of Median of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:oth395_other_12_13', 'description': '不可使用,仅供参考:Operating Accruals / Time Series Average Total Assets 2'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volivcallmputs3', 'description': '不可使用,仅供参考:Weighted average Implied volatility for out-of-the-money call options and put options with the same strike prices with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:fnd3_qacctadj_comstk_divpershare_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Common Stock Dividends Per Share'} |
||||
{'data_set_name': '可以使用:mdl262_eibt_a_profitability_profitability7', 'description': '不可使用,仅供参考:7th profitability field of Annual Net Income Before Taxes'} |
||||
{'data_set_name': '可以使用:pv87_eps_gaap_consensus_high', 'description': '不可使用,仅供参考:EPS (GAAP) Consensus High'} |
||||
{'data_set_name': '可以使用:pv87_ann_matrix_book_value_share_estimate_high', 'description': '不可使用,仅供参考:High of Book Value / Share Estimate'} |
||||
{'data_set_name': '可以使用:anl69_ndebt_best_fperiod_override', 'description': '不可使用,仅供参考:Fiscal Period Override'} |
||||
{'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_all_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Net Profit'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_net_income_normalized_consensus_mean_numanalystsunfiltered', 'description': '不可使用,仅供参考:Number of analysts (unfiltered) of Net Income Normalized Consensus Mean'} |
||||
{'data_set_name': '可以使用:last_event_timestamp_info1d0', 'description': '不可使用,仅供参考:Timestamp of the most recent event in the info_1_D0 module.'} |
||||
{'data_set_name': '可以使用:triple_ema_rate_change_3d', 'description': '不可使用,仅供参考:Rate of change of triple-smoothed exponential moving average over 3 days.'} |
||||
{'data_set_name': '可以使用:est_12m_grm_high_3mth_ago', 'description': '不可使用,仅供参考:Highest analyst estimate of gross margin in percent regarding the next 4 quarters, made in the past 3 months'} |
||||
{'data_set_name': '可以使用:pv98_high_11_backfill', 'description': '不可使用,仅供参考:Highest price at 11:00'} |
||||
{'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_b_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_all_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Pretax Profit'} |
||||
{'data_set_name': '可以使用:fnd72_pit_or_cr_a_net_chng_lt_debt', 'description': '不可使用,仅供参考:Year on year change between current and prior year long-term debt'} |
||||
{'data_set_name': '可以使用:shares_outstanding_max_guidance', 'description': '不可使用,仅供参考:Maximum guidance value for Shares'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_cash_flow_share_consensus_mean_numupunfiltered', 'description': '不可使用,仅供参考:Number of up revisions of Cash Flow / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:mdl230_totalcap_cusip_curindcoreepsp_', 'description': "不可使用,仅供参考:It is defined as a stock's trailing 12-month core earnings-to-price ratio (CoreEP) less the average of the CoreEPs of all stocks in the same industry deflated by the standard deviation of the CoreEPs of all stocks in the same relative universe."} |
||||
{'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_p1_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Net Profit'} |
||||
{'data_set_name': '可以使用:principal_component_score_11_top500_513', 'description': '不可使用,仅供参考:Value of the 12th principal component for the top 500 securities in group 513.'} |
||||
{'data_set_name': '可以使用:principal_component2_grouping20_top3000', 'description': '不可使用,仅供参考:Second principal component grouping for top 3000 securities with 20 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volvegaput9', 'description': '不可使用,仅供参考:vega volume of deep in put options'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_interest_expense_estimate_median', 'description': '不可使用,仅供参考:Median of Interest Expense Estimate'} |
||||
{'data_set_name': '可以使用:pv87_prv2_expavg60_group_css_dividends', 'description': '不可使用,仅供参考:60-day Exponential average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Dividends'} |
||||
{'data_set_name': '可以使用:oth567score_diversity_and_inclusion', 'description': '不可使用,仅供参考:Score for diversity and inclusion'} |
||||
{'data_set_name': '可以使用:earnings_before_tax_2', 'description': '不可使用,仅供参考:Earnings before income tax expense is deducted.'} |
||||
{'data_set_name': '可以使用:pv87_weightedavg60_group_ess_revenues', 'description': '不可使用,仅供参考:60-day Weighted average of ESS - Event Sentiment Score for group Revenues'} |
||||
{'data_set_name': '可以使用:accounts_receivable_current', 'description': '不可使用,仅供参考:Current accounts receivable at period end.'} |
||||
{'data_set_name': '可以使用:theoretical_zero_risk_rate', 'description': '不可使用,仅供参考:The theoretical rate of return of a risk-free investment.'} |
||||
{'data_set_name': '可以使用:fnd72_pit_or_cr_a_cash_to_tot_asset', 'description': '不可使用,仅供参考:Ratio to measure the percentage of cash and near cash over total assets'} |
||||
{'data_set_name': '可以使用:pv87_ann_matrix_cash_from_operations_estimate_low', 'description': '不可使用,仅供参考:Low of Cash From Operations Estimate'} |
||||
{'data_set_name': '可以使用:mdl77_oearningmomentumfactor_pelh', 'description': '不可使用,仅供参考:Street Revision Confidence: It is defined as the sum of the 3-month change in the highest and lowest FY1 earnings estimate, scaled by month-end trading price.'} |
||||
{'data_set_name': '可以使用:compustat_liquidity_metric_three', 'description': '不可使用,仅供参考:Third liquidity ratio or metric calculated from Compustat data.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_matrix_sent_ew_sent_z_range', 'description': '不可使用,仅供参考:range of Sentiment'} |
||||
{'data_set_name': '可以使用:mdl77_2deepvaluefactor_curep', 'description': "不可使用,仅供参考:Current Earnings Yield: It is defined as the sum of the most recently reported 3 quarters EPS and analysts' consensus earnings estimate for the current quarter divided by its price."} |
||||
{'data_set_name': '可以使用:oth460_group_short_squeeze_potential_l3', 'description': '不可使用,仅供参考:The probability that the future trend of Group Type 1% and Group Type 3% values added together." will move up"'} |
||||
{'data_set_name': '可以使用:incentive_share_award_value', 'description': '不可使用,仅供参考:Value of shares awarded in the incentive plan.'} |
||||
{'data_set_name': '可以使用:short_term_notes_payable', 'description': '不可使用,仅供参考:Short-term notes payable outstanding at period end.'} |
||||
{'data_set_name': '可以使用:last_event_timestamp_info10_simple_fast_d1', 'description': '不可使用,仅供参考:Timestamp of the most recent event in the info10 module (simple version).'} |
||||
{'data_set_name': '可以使用:mean_polarity_profitability_presentation', 'description': '不可使用,仅供参考:Average polarity score for profitability sentiment in the presentation section.'} |
||||
{'data_set_name': '可以使用:fnd89_jonesother15_d1_length', 'description': '不可使用,仅供参考:How many accruals ratio data is available'} |
||||
{'data_set_name': '可以使用:pv87_free_cash_flow_consensus_median_scale', 'description': '不可使用,仅供参考:Scale of Free Cash Flow Consensus Median'} |
||||
{'data_set_name': '可以使用:oth460_long_zone_juice_l1', 'description': '不可使用,仅供参考:The probability that the future trend of The seasonal cycle at the end of the current long zone minus the seasonal cycle" will fall"'} |
||||
{'data_set_name': '可以使用:other_participant_fre_score_presentation', 'description': '不可使用,仅供参考:Flesch Reading Ease (FRE) for other participants in presentation section.'} |
||||
{'data_set_name': '可以使用:fnd3_Qacctadj_int_ass_ex_gwill', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Intangible Assets Excluding Goodwill'} |
||||
{'data_set_name': '可以使用:opt40_put_volatility_547days', 'description': '不可使用,仅供参考:Volatility for put options with 547 days to expiration.'} |
||||
{'data_set_name': '可以使用:associated_topic_categories', 'description': "不可使用,仅供参考:List of topics or categories relevant to the article's content."} |
||||
{'data_set_name': '可以使用:min_financing_cashflow_guidance_2', 'description': '不可使用,仅供参考:Minimum guidance value for Cash Flow From Financing on an annual basis'} |
||||
{'data_set_name': '可以使用:cash', 'description': '不可使用,仅供参考:Cash'} |
||||
{'data_set_name': '可以使用:fnd31_devnorthamericaadditionalfactor4_rev6fy2', 'description': "不可使用,仅供参考:Averaged Last 6-M EPS Revisions for FY2. It is defined as the average of prior 6-month monthly changes in a stock's consensus analysts' earnings forecasts for fiscal year 2, scaled by previous month-end trading price."} |
||||
{'data_set_name': '可以使用:est_12m_ent_low_3mth_ago', 'description': '不可使用,仅供参考:Lowest analyst estimate of enterprise value regarding the next 4 quarters, made in past 3 months'} |
||||
{'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_px_to_free_cash_flow', 'description': "不可使用,仅供参考:Valuation metric that compares a company's market price to its level of trailing 12-month free cash flow per share"} |
||||
{'data_set_name': '可以使用:fnd72_s_pit_or_is_q_min_noncontrol_interest_credits', 'description': '不可使用,仅供参考:Minority Interests'} |
||||
{'data_set_name': '可以使用:pv87_num_of_analysts_underperform_industry_recommendation_in_consensus_scale', 'description': '不可使用,仅供参考:Scale of # of Analysts Underperform Industry Recommendation - (In-Consensus)'} |
||||
{'data_set_name': '可以使用:pv87_prv2_simpleavg60_topic_nip_business', 'description': '不可使用,仅供参考:60-day Simple average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for topic Business'} |
||||
{'data_set_name': '可以使用:mdl77_2earningsmomemtummodel_gtl', 'description': "不可使用,仅供参考:Long-Term Growth Rate Estimates: It is defined as the consensus long-term growth forecast. It generally represents an expected annual increase in operating earnings over the company's next full business cycle."} |
||||
{'data_set_name': '可以使用:fnd89_jonesother11_d1_current_t', 'description': '不可使用,仅供参考:current t-statistics of accruals ratio, calculated as Current-t = (current accruals ratio-mean)/std'} |
||||
{'data_set_name': '可以使用:financial_pca_factor1_grouping5', 'description': '不可使用,仅供参考:First principal component grouping for financial sector with 5 clusters.'} |
||||
{'data_set_name': '可以使用:est_q_gps_high_4wks_ago', 'description': '不可使用,仅供参考:Highest analyst estimate of GAAP earnings per share regarding the next quarter, made in past 4 weeks'} |
||||
{'data_set_name': '可以使用:mdl177_liquidityriskfactor_altmanz_alt', 'description': '不可使用,仅供参考:Altman Z Score : Altman Z = 1.2* (Current Assets - Current Liabilities)/TA + 1.4*Retained Earnings/TA + 3.3*Earnings before Interest and Taxes/TA+ 0.6*Market Value of Preferred and Common Equity/Book Value of Total Liabilities + 1.0*Sales/TA where TA denotes total assets.'} |
||||
{'data_set_name': '可以使用:fnd3_Aacctadj_sharesauthorized', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Shares Authorized'} |
||||
{'data_set_name': '可以使用:fnd28_annualgrowthq_value_08636q', 'description': '不可使用,仅供参考:value of quarterly field: Net Income Growth'} |
||||
{'data_set_name': '可以使用:external_event_language_score_2', 'description': '不可使用,仅供参考:Score based on language about market or third-party events affecting the company (alternate source).'} |
||||
{'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_chg3yfcfp', 'description': '不可使用,仅供参考:3-yr Change in Price-adj TTM FCF : It is defined as the difference between the most recently reported trailing 12-month free cash flow per share and that of 12-quarters ago for a stock divided by its month-end trading price.'} |
||||
{'data_set_name': '可以使用:pv87_2_roa_af_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Return On Assets *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:other_cfo_singular_plural_pronoun_ratio_presentation', 'description': '不可使用,仅供参考:Ratio of singular to plural pronouns used by other CFOs in the presentation section.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_matrix_vol_vol_dispersion_mean', 'description': '不可使用,仅供参考:Average of Volume Dispersion'} |
||||
{'data_set_name': '可以使用:basicmat_method3_group5_score', 'description': '不可使用,仅供参考:Score from the third method for basic materials sector, grouped into 5 clusters.'} |
||||
{'data_set_name': '可以使用:oth460_long_heat_l3', 'description': '不可使用,仅供参考:The probability that the future trend of Percentage of the time strong periods overlap in prior years. " will be move-up"'} |
||||
{'data_set_name': '可以使用:est_12m_dps_low_3mth_ago', 'description': '不可使用,仅供参考:Lowest analyst estimate of dividend per share regarding the next 4 quarters, made in the past 3 months'} |
||||
{'data_set_name': '可以使用:analyst_ari_score_presentation', 'description': '不可使用,仅供参考:Automated Readability Index (ARI) for analysts in presentation section.'} |
||||
{'data_set_name': '可以使用:pv87_prv2_simpleavg1_group_event_sentiment_score_earnings', 'description': '不可使用,仅供参考:1-day Simple average of Event Sentiment Score for group Earnings'} |
||||
{'data_set_name': '可以使用:nws5_peratio', 'description': '不可使用,仅供参考:Reported price-to-earnings ratio for the calendar day of the session'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple14d_ew_sent_mean_range', 'description': '不可使用,仅供参考:14-day Simple average of Range of Sentiment Average'} |
||||
{'data_set_name': '可以使用:pv87_prv2_expavg60_topic_nip_all', 'description': '不可使用,仅供参考:60-day Exponential average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for topic All'} |
||||
{'data_set_name': '可以使用:anl10_salpast_det_estvalue_1124', 'description': '不可使用,仅供参考:Estimate value for sales'} |
||||
{'data_set_name': '可以使用:pv87_wasteandhazardousmaterialsmanagement_pulse_mean', 'description': '不可使用,仅供参考:Short-term score of Waste And Hazardous Materials Management topic'} |
||||
{'data_set_name': '可以使用:current_price_to_intrinsic_value_ratio', 'description': '不可使用,仅供参考:Ratio of the current share price to the calculated intrinsic value.'} |
||||
{'data_set_name': '可以使用:oth432_rasv2splitprofitabilityebitd_q_profitability11', 'description': '不可使用,仅供参考:11th profitability field of Earnings before Interest, Tax, and Depreciation'} |
||||
{'data_set_name': '可以使用:rsk62_industry_1_100_val36', 'description': '不可使用,仅供参考:Industry return'} |
||||
{'data_set_name': '可以使用:parkinson_volatility_30', 'description': "不可使用,仅供参考:Parkinson model's historical volatility over 30 days"} |
||||
{'data_set_name': '可以使用:pv87_2_roa_qf_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Return On Assets *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:fnd65_allcap_sedol_pctabv260low', 'description': "不可使用,仅供参考:It is defined as a stock's current closing price divided by its lowest daily low price in last 260 trading days."} |
||||
{'data_set_name': '可以使用:pv87_2_csh_qf_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Common Shares *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple7d_sent_trend2', 'description': '不可使用,仅供参考:trend2 of Sentiment'} |
||||
{'data_set_name': '可以使用:fnd72_q2_trail_12m_foreign_exch', 'description': '不可使用,仅供参考:Calculated by adding 4 quarters, 2 semi-annuals, or annual of Foreign Exchange Gain or Loss'} |
||||
{'data_set_name': '可以使用:min_investing_cashflow_guidance', 'description': '不可使用,仅供参考:Cash Flow From Investing - Minimum guidance value'} |
||||
{'data_set_name': '可以使用:anl69_eps_gaap_4wk_chg_best_fperiod_override', 'description': '不可使用,仅供参考:Fiscal Period Override'} |
||||
{'data_set_name': '可以使用:principal_component3_grouping5_top3000', 'description': '不可使用,仅供参考:Third principal component grouping for top 3000 securities with 5 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_2_bps_af_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Book Value Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg20_group_event_sentiment_score_legal', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Legal'} |
||||
{'data_set_name': '可以使用:pv87_webv2_expavg20_group_event_sentiment_score_price_targets', 'description': '不可使用,仅供参考:20-day Exponential average of Event Sentiment Score for group Price Targets'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_matrix_vol_vol_std_trend2', 'description': '不可使用,仅供参考:Trend of Volume Standard deviation'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_sent_trend2', 'description': '不可使用,仅供参考:7-day Volume weighted average of Trend of Sentiment'} |
||||
{'data_set_name': '可以使用:est_q_grm_lowered_1wk', 'description': '不可使用,仅供参考:Count of unique IDs of industry participants. Industry stands for an aggregate view of all equity clearance activity for the date, symbol, and transaction type in question.'} |
||||
{'data_set_name': '可以使用:cash_and_marketable_investments', 'description': '不可使用,仅供参考:Cash and marketable investment securities held at period end.'} |
||||
{'data_set_name': '可以使用:fn_avg_diluted_sharesout_adj_q', 'description': '不可使用,仅供参考:The sum of dilutive potential common shares or units used in the calculation of the diluted per-share or per-unit computation.'} |
||||
{'data_set_name': '可以使用:top3000_pca_component4', 'description': '不可使用,仅供参考:Fourth principal component value for top 3000 securities.'} |
||||
{'data_set_name': '可以使用:anl69_eps_hi_best_fperiod_override', 'description': '不可使用,仅供参考:Fiscal Period Override'} |
||||
{'data_set_name': '可以使用:fnd72_s_pit_or_is_q_is_earn_bef_xo_items_per_sh', 'description': '不可使用,仅供参考:Diluted EPS'} |
||||
{'data_set_name': '可以使用:mdl262_rtlr_q_profitability_profitability6', 'description': '不可使用,仅供参考:6th profitability field of Total Revenue'} |
||||
{'data_set_name': '可以使用:fnd72_q2_trail_12m_other_non_oper_loss', 'description': '不可使用,仅供参考:Calculated by adding 4 quarters, 2 semi-annuals, or annual of Net Other Non-Operating Gain or Loss'} |
||||
{'data_set_name': '可以使用:mdl177_2_pricemomemtummodel_visiratio', 'description': "不可使用,仅供参考:The Visibility Ratio : It equals to a stock's most recent daily trading volume divided by the average daily trading volume in previous 50 trading days."} |
||||
{'data_set_name': '可以使用:nws12_mainz_short_interest', 'description': '不可使用,仅供参考:Total number of shares sold short divided by total number of shares outstanding'} |
||||
{'data_set_name': '可以使用:est_q_roa_low', 'description': '不可使用,仅供参考:Lowest analyst estimate of return on assets in percent regarding the next quarter'} |
||||
{'data_set_name': '可以使用:mdl262_rasv2splitprofitabilityebt_ttm_profitability12', 'description': '不可使用,仅供参考:12th profitability field of Earnings before tax, trailing 12 months'} |
||||
{'data_set_name': '可以使用:earnings_expectation_module_score', 'description': '不可使用,仅供参考:Earnings Expectations'} |
||||
{'data_set_name': '可以使用:communications_top3000_grouping_20_clusters', 'description': '不可使用,仅供参考:Grouping of top 3000 communications stocks using 20 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_event_sentiment_score_earnings', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Earnings'} |
||||
{'data_set_name': '可以使用:fn_excess_tax_benefit_from_share_based_comp_fin_activities_q', 'description': "不可使用,仅供参考:Amount of cash inflow from realized tax benefit related to deductible compensation cost reported on the entity's tax return for equity instruments in excess of the compensation cost for those instruments recognized for financial reporting purposes."} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volivcallmputs5', 'description': '不可使用,仅供参考:implied volatility volume of in call minus put options with the same strike prices, which are in the money'} |
||||
{'data_set_name': '可以使用:anl4_totgw_high', 'description': '不可使用,仅供参考:Total Goodwill - The highest estimation'} |
||||
{'data_set_name': '可以使用:est_cashflow_invst', 'description': '不可使用,仅供参考:Cash Flow From Investing - mean of estimations'} |
||||
{'data_set_name': '可以使用:consumer_electronics_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the consumer electronics sector factor.'} |
||||
{'data_set_name': '可以使用:mdl77_liquidityriskfactor_nlassets', 'description': '不可使用,仅供参考:Natural Logarithm of Total Assets: It is defined as the natural logarithm of the most recent quarterly reported total assets.'} |
||||
{'data_set_name': '可以使用:fin_nonreit_industry_grouping_method4_2', 'description': '不可使用,仅供参考:Industry grouping for financial sector excluding REITs using method 4 with 2 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_ew_sent_z_daydiff', 'description': '不可使用,仅供参考:7-day Volume weighted average of Daily difference of Sentiment'} |
||||
{'data_set_name': '可以使用:mdl219_3_qva_yoychgshares', 'description': '不可使用,仅供参考:Year-over-year change in shares outstanding for the third module.'} |
||||
{'data_set_name': '可以使用:oth699_prevnumofshares_18', 'description': '不可使用,仅供参考:the number of shares the user had prior to the transaction'} |
||||
{'data_set_name': '可以使用:latest_annual_period_end_update_cash_flow_per_share_second', 'description': '不可使用,仅供参考:Date or timestamp when the annual period end for cash flow per share was last updated in the second version module.'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_r6_net_debt_consensus_mean_numupunfiltered', 'description': '不可使用,仅供参考:Number of up revisions of Net Debt Consensus Mean'} |
||||
{'data_set_name': '可以使用:mdl77_devnorthamericashortsentimentfactor_days_to_cover', 'description': '不可使用,仅供参考:Days to Cover'} |
||||
{'data_set_name': '可以使用:pv87_dps_consensus_low_scale', 'description': '不可使用,仅供参考:Scale of DPS Consensus Low'} |
||||
{'data_set_name': '可以使用:anl11_cit2reg_industryrnk', 'description': '不可使用,仅供参考:Industry Rank on CIT2 1 being the highest rank'} |
||||
{'data_set_name': '可以使用:anl44_2_netprofit_prevalue', 'description': '不可使用,仅供参考:netprofit prevalue'} |
||||
{'data_set_name': '可以使用:pv87_revenue_estimate_1_yr_annual_growth_scale', 'description': '不可使用,仅供参考:Scale of Revenue Estimate - 1 Yr Annual Growth %'} |
||||
{'data_set_name': '可以使用:pv87_prv2_simpleavg60_group_event_sentiment_score_all', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for group All'} |
||||
{'data_set_name': '可以使用:mdl262_ninc_q_profitability_profitability2', 'description': '不可使用,仅供参考:2nd profitability field of Income Incl Extra Before Distributions'} |
||||
{'data_set_name': '可以使用:anl49_annualfiscalearningspershareindicator', 'description': '不可使用,仅供参考:Annual fiscal earnings per share indicator'} |
||||
{'data_set_name': '可以使用:anl10_netrevise_value_fq1_2514', 'description': '不可使用,仅供参考:Delta consensus for net income Q1 (difference between old and current updated value)'} |
||||
{'data_set_name': '可以使用:temporary_investments_balance_fast_d1', 'description': '不可使用,仅供参考:Value of investments expected to be liquidated within a year.'} |
||||
{'data_set_name': '可以使用:est_q_tbv_lowerednum_1mth', 'description': '不可使用,仅供参考:Count of unique IDs of industry participants. Industry stands for an aggregate view of all equity clearance activity for the date, symbol, and transaction type in question.'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_nip_marketing', 'description': '不可使用,仅供参考:20-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Marketing'} |
||||
{'data_set_name': '可以使用:mdl219_1_curratio', 'description': '不可使用,仅供参考:Current ratio calculated as current assets divided by current liabilities.'} |
||||
{'data_set_name': '可以使用:mdl177_2_growthanalystmodel_qga_epstrend', 'description': '不可使用,仅供参考:EPS Trend'} |
||||
{'data_set_name': '可以使用:rsk62_industry_5_100_val42', 'description': '不可使用,仅供参考:Industry return'} |
||||
{'data_set_name': '可以使用:mdl77_liquidityriskfactor_idb', 'description': '不可使用,仅供参考:Basic Defensive Interval: It measures how many days that a company can cover its daily operating expenses (cost of goods sold and SG&A) by only using its cash and receivables on its balance sheet.'} |
||||
{'data_set_name': '可以使用:pv87_2_roe_af_matrix_all_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Return On Equity'} |
||||
{'data_set_name': '可以使用:high', 'description': '不可使用,仅供参考:Daily high price'} |
||||
{'data_set_name': '可以使用:mdl77_deepvaluefactor_ebitdaev', 'description': '不可使用,仅供参考:TTM EBITDA-to-Enterprise Value: It is defined as the trailing 12-month earnings before interest, taxes, depreciation, and amortization for a stock deflated by its enterprise value (EV). EV = Equity Market Value + Long-term Debt + Short-term Debt + Preferred Stock + Minority Interest - Cash.'} |
||||
{'data_set_name': '可以使用:pv87_marketimpactscore_mean', 'description': '不可使用,仅供参考:Mean of Market impact score - The estimated risk-adjusted 1 minute forward return for a given article as measured by stock return minus the stock beta multiplied market return, -5 being most negative impact and +5 most positive'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_ebit_estimate_low', 'description': '不可使用,仅供参考:Low of EBIT Estimate'} |
||||
{'data_set_name': '可以使用:suspect_data_indicator_quarter3_earnings', 'description': '不可使用,仅供参考:Flag indicating potentially unreliable data for third fiscal quarter earnings.'} |
||||
{'data_set_name': '可以使用:snt21_7pos_conf_low', 'description': '不可使用,仅供参考:Lower confidence bound for positive sentiment scores.'} |
||||
{'data_set_name': '可以使用:offer_premium_one_week_prior', 'description': "不可使用,仅供参考:Premium of offer price to target's closing stock price one week before announcement."} |
||||
{'data_set_name': '可以使用:pv87_matrix_nonperiodic_consensus_recommendation_numdownunfiltered', 'description': '不可使用,仅供参考:Number of down revisions (unfiltered) of Consensus Recommendation'} |
||||
{'data_set_name': '可以使用:fn_accum_oth_income_loss_net_of_tax_a', 'description': '不可使用,仅供参考:Accumulated change in equity from transactions and other events and circumstances from non-owner sources, net of tax effect, at period end. Excludes Net Income (Loss), and accumulated changes in equity from transactions resulting from investments by owners and distributions to owners. Includes foreign currency translation items, certain pension adjustments, unrealized gains and losses on certain investments in debt and equity securities, other than temporary impairment (OTTI) losses related to factors other than credit losses on available-for-sale and held-to-maturity debt securities that an entity does not intend to sell and it is not more likely than not that the entity will be required to sell before recovery of the amortized cost basis, as well as changes in the fair value of derivatives related to the effective portion of a designated cash flow hedge.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volvegacallmput6', 'description': '不可使用,仅供参考:Weighted average Vega for far out-of-the-money call and put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_webv2_simpleavg1_topic_event_sentiment_score_business', 'description': '不可使用,仅供参考:1-day Simple average of Event Sentiment Score for topic Business'} |
||||
{'data_set_name': '可以使用:fnd3_qacctadjequitybeforenci_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance AdjustmentStockholders Equity Before Non-Controlling Interest'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg60_group_css_dividends', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Dividends'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volivcall4', 'description': '不可使用,仅供参考:Weighted average Implied volatility for near-the-money call options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:shrt10_900_standalone_bear2x', 'description': '不可使用,仅供参考:Specifies whether a fund is inversely leveraged 2x'} |
||||
{'data_set_name': '可以使用:anl82_ebtq_profitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on value of Q EBITDA'} |
||||
{'data_set_name': '可以使用:pv87_2_roe_af_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Return On Equity *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:fn_comprehensive_income_net_of_tax_q', 'description': '不可使用,仅供参考:Amount after tax of increase (decrease) in equity from transactions and other events and circumstances from net income and other comprehensive income, attributable to parent entity. Excludes changes in equity resulting from investments by owners and distributions to owners.'} |
||||
{'data_set_name': '可以使用:std_adj_recent_earnings_surprise', 'description': '不可使用,仅供参考:Most Recent Quarterly Earnings Surprise'} |
||||
{'data_set_name': '可以使用:workplace_diversity_labor_rights_score', 'description': '不可使用,仅供参考:Score measuring workplace diversity, labor relations, and employee rights.'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_css_earnings', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Earnings'} |
||||
{'data_set_name': '可以使用:snt21_2neut_conf_low_156', 'description': '不可使用,仅供参考:Lower confidence bound for neutral sentiment scores.'} |
||||
{'data_set_name': '可以使用:fnd7_ointfund_qcbuse', 'description': '不可使用,仅供参考:Quarterly Fundamental Item: Equity in Net Loss (Earnings) (Statement of Cash Flows)'} |
||||
{'data_set_name': '可以使用:pv87_2_netdebt_af_matrix_p1_b_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Net Asset Value (NAV)'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volthetacall5', 'description': '不可使用,仅供参考:theta volume of in call options'} |
||||
{'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_slope4qsales3y', 'description': '不可使用,仅供参考:Slope of 3-yr TTM Sales Trend Line'} |
||||
{'data_set_name': '可以使用:pv87_v2_expavg60_topic_css_all', 'description': '不可使用,仅供参考:60-day Exponential average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for topic All'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg60_group_css_marketing', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Marketing'} |
||||
{'data_set_name': '可以使用:mdl177_2_pricemomentumfactor_pctabv260low', 'description': '不可使用,仅供参考:Price Above Last 260-day Lowest Trading Price'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_ew_sent_mean_trend2', 'description': '不可使用,仅供参考:7-day Volume weighted average of Trend of Sentiment Average'} |
||||
{'data_set_name': '可以使用:pv87_matrix_nonperiodic_eps_lt_growth_consensus_mean_numdownunfiltered', 'description': '不可使用,仅供参考:Number of down revisions (unfiltered) of EPS LT Growth Consensus Mean (%)'} |
||||
{'data_set_name': '可以使用:gas_utilities_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the gas utilities sector factor.'} |
||||
{'data_set_name': '可以使用:pv87_free_cash_flow_of_estimates_scale', 'description': '不可使用,仅供参考:Scale of Free Cash Flow - # of Estimates'} |
||||
{'data_set_name': '可以使用:pv98_usa_pricesnap_13_low_13', 'description': '不可使用,仅供参考:Low price at 13:00'} |
||||
{'data_set_name': '可以使用:sta2_top3000_fact4_c2', 'description': '不可使用,仅供参考:statistical industry classification'} |
||||
{'data_set_name': '可以使用:pv87_2_netdebt_af_matrix_p1_b_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Net Asset Value (NAV)'} |
||||
{'data_set_name': '可以使用:pv87_2_dps_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Dividends Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:other_participant_sentence_count_qa', 'description': '不可使用,仅供参考:Total number of sentences spoken by other participants in the Q&A section.'} |
||||
{'data_set_name': '可以使用:fnd31_qsg5additionalfactor3_backfilled_ps_wt', 'description': '不可使用,仅供参考:Time Weighted Sales Yield. It is defined as the time-weighted sales per share for FY1 and FY2 divided by its price.'} |
||||
{'data_set_name': '可以使用:pca_factor_5_top1000', 'description': '不可使用,仅供参考:Sixth principal component value for top 1000 securities.'} |
||||
{'data_set_name': '可以使用:fnd31_qsg5additionalfactor3_backfilled_tw_ebitdaev', 'description': '不可使用,仅供参考:Time-Weighted EBITDA/EV. It is defined as the time-weighted EBITDA/Enterprise Value for FY1 and FY2.'} |
||||
{'data_set_name': '可以使用:mdl77_2gdna_cashsev', 'description': '不可使用,仅供参考:Cash to Enterprise Value: It is defined as the total cash & equivalents divided by the sum of the market value of common equity and book value of long-term debt.'} |
||||
{'data_set_name': '可以使用:sector_grouping_level20_consumer_staples', 'description': '不可使用,仅供参考:Industry grouping at level 20 for consumer non-cyclical sector.'} |
||||
{'data_set_name': '可以使用:fnd3_Aacctadj_opeexpenseexitems', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Operating Expense Extraordinary Items'} |
||||
{'data_set_name': '可以使用:snt21_neut_conf_low', 'description': '不可使用,仅供参考:Lower confidence bound for neutral sentiment scores.'} |
||||
{'data_set_name': '可以使用:rsk62_industry_1_100_val73', 'description': '不可使用,仅供参考:Industry return'} |
||||
{'data_set_name': '可以使用:fnd1_stdevtimebrd', 'description': '不可使用,仅供参考:The standard deviation of the population of Time on Board values for the Executive Directors'} |
||||
{'data_set_name': '可以使用:fnd89_csjones_industry_major_13', 'description': '不可使用,仅供参考:Cross Sectional Ratio of Cash-related field (income statement), scaled by Average Total Asset across Industry'} |
||||
{'data_set_name': '可以使用:oth432_cashflows_rtlr_predict', 'description': '不可使用,仅供参考:Predict value of Total Revenue'} |
||||
{'data_set_name': '可以使用:pv20_net_indicator_2_feature6', 'description': '不可使用,仅供参考:[Features heuristically extracted from ibes modules of Pre-tax Profit] [Fiscal Year 2] [Non-trivial feature]'} |
||||
{'data_set_name': '可以使用:oth460_put_call_erlanger_ratio_class', 'description': "不可使用,仅供参考:Predicted trend of 'Premium Ratio' (1: fall, 2: neutral, 3: move-up)"} |
||||
{'data_set_name': '可以使用:cons_cyclical_method3_group10_score', 'description': '不可使用,仅供参考:Score from the third method for consumer cyclical sector, grouped into 10 clusters.'} |
||||
{'data_set_name': '可以使用:mdl177_2_managementqualityfactor_noato', 'description': '不可使用,仅供参考:Net Operating Asset Turnover : It is defined as trailing-12-month sales divided by the last 4-quarters average net operating assets, which equals short-term debt + long-term debt + preferred equity + common equity - cash'} |
||||
{'data_set_name': '可以使用:fnd72_pit_or_is_a_is_tot_cash_com_dvd', 'description': '不可使用,仅供参考:Dividends paid to common shareholders from the profits of the company'} |
||||
{'data_set_name': '可以使用:pv87_2_eps_qf_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Earnings Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:rsk62_industry_1_100_val52', 'description': '不可使用,仅供参考:Industry return'} |
||||
{'data_set_name': '可以使用:pv87_2_capex_qf_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Capital Expenditure *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:mdl177_earningmomentumfactor_perg', 'description': '不可使用,仅供参考:Risk-adjusted PEG Ratio'} |
||||
{'data_set_name': '可以使用:fnd72_s_pit_or_bs_q_2_bs_allow_doubtful_acc_rec', 'description': '不可使用,仅供参考:A contra asset account that is subtracted from trade and notes receivables on the balance sheet'} |
||||
{'data_set_name': '可以使用:quarterly_long_term_tax_liability', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Deferred Tax Liabilities, noncurrent'} |
||||
{'data_set_name': '可以使用:mdl177_2_5yearrelativevaluefactor_rel5ycoreepsp', 'description': '不可使用,仅供参考:5-yr Relative TTM Core Earnings-to-Price'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volvegacall0', 'description': '不可使用,仅供参考:vega volume of all call options'} |
||||
{'data_set_name': '可以使用:top200_method3_group50_score', 'description': '不可使用,仅供参考:Score from the third method for top 200 securities, grouped into 50 clusters.'} |
||||
{'data_set_name': '可以使用:mdl262_rasv2splitprofitabilityebt_q_profitability9', 'description': '不可使用,仅供参考:9th profitability field of Earnings before tax'} |
||||
{'data_set_name': '可以使用:nws29_full_topic1', 'description': '不可使用,仅供参考:The news topic code. A news item can have several topics.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_sent_std_daydiff', 'description': '不可使用,仅供参考:14-day Volume weighted average of Daily difference of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:exclusion_factor_score_previous_year', 'description': '不可使用,仅供参考:Percentile score for exclusion factors from the previous year.'} |
||||
{'data_set_name': '可以使用:star_sr_profitability', 'description': '不可使用,仅供参考:Financial health score: profitability'} |
||||
{'data_set_name': '可以使用:mdl77_liquidityriskfactor_cashratio', 'description': '不可使用,仅供参考:Cash & Equivalents-to-Current Liabilities: It is defined as the most recently reported quarterly cash & equivalents divided by current liabilities.'} |
||||
{'data_set_name': '可以使用:anl14_high_eps_fp2', 'description': '不可使用,仅供参考:The highest estimation of Earnings Per Share - upcoming 2 quarters'} |
||||
{'data_set_name': '可以使用:fnd65_us5000_cusip_impduration', 'description': "不可使用,仅供参考:It is an equity risk measure based on Macaulay's traditional measure of bond duration. It combines book value, expected growth, expected profitability, and current stock trading price."} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_pctchgeps', 'description': "不可使用,仅供参考:The percent change in a stock's most recent trailing 12-month earnings per share before extra items as compared to itself 4 quarters ago."} |
||||
{'data_set_name': '可以使用:fn_prepaid_expense_a', 'description': '不可使用,仅供参考:Carrying amount for an unclassified balance sheet date of expenditures made in advance of when the economic benefit of the cost will be realized, and which will be expensed in future periods with the passage of time or when a triggering event occurs. For a classified balance sheet, represents the noncurrent portion of prepaid expenses (the current portion has a separate concept).'} |
||||
{'data_set_name': '可以使用:fnd72_a1_net_non_oper_loss_yr_growth', 'description': '不可使用,仅供参考:Percentage change in net non-operating loss from last year to the current year'} |
||||
{'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on delta of Q net income'} |
||||
{'data_set_name': '可以使用:pv87_webv2_expavg60_topic_event_sentiment_score_business', 'description': '不可使用,仅供参考:60-day Exponential average of Event Sentiment Score for topic Business'} |
||||
{'data_set_name': '可以使用:pv87_scores_certaintypartnormscr_median', 'description': '不可使用,仅供参考:Median of Certainity partial score'} |
||||
{'data_set_name': '可以使用:robust_factor_1_top2000', 'description': '不可使用,仅供参考:Second robust factor for top 2000 securities.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_matrix_vol_vol_std_daydiff', 'description': '不可使用,仅供参考:Daily difference of Volume Standard deviation'} |
||||
{'data_set_name': '可以使用:rsk62_factor_5_100_val84', 'description': '不可使用,仅供参考:Factor return'} |
||||
{'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:fnd3_qacctadjequitybeforenci', 'description': '不可使用,仅供参考:Quarterly Accountance AdjustmentStockholders Equity Before Non-Controlling Interest'} |
||||
{'data_set_name': '可以使用:mdl230_allcap_sedol_rationalalpha', 'description': '不可使用,仅供参考:It evaluates stocks based on their historical 12-month market (S&P 500) adjusted excess return (the Y intercept from an OLS regression equation) using a proprietary rational decay function.'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oivegacallmput9', 'description': '不可使用,仅供参考:vega of deep in call minus put options'} |
||||
{'data_set_name': '可以使用:fnd2_dbplanartonplas', 'description': '不可使用,仅供参考:Defined Benefit Plan, Benefits Paid, Plan Assets'} |
||||
{'data_set_name': '可以使用:pv87_weightedavg60_group_v2_0_1_ess_revenues', 'description': '不可使用,仅供参考:60-day Weighted average of ESS - Event Sentiment Score for group Revenues'} |
||||
{'data_set_name': '可以使用:anl49_earningspredictabilityindex', 'description': '不可使用,仅供参考:A measure of the reliability of an earnings forecast. Predictability is based upon the stability of year-toyear comparisons, with recent years being weighted more heavily than earlier ones. The most reliable forecasts tend to be those with the highest rating (100); the least reliable, the lowest (5). The earnings stability is derived from the standard deviation percentage changes in quarterly earnings over an eight-year period. Special adjustments are made for comparisons around zero and from plus to minus.'} |
||||
========================= 数据字段结束 ======================================= |
||||
|
||||
以上数据字段和操作符, 按照Description说明组合, 但是每一个 alpha 组合的使用的数据字段和操作符不要过于集中, 在符合语法的情况下, 多尝试不同的组合 |
||||
|
||||
你再检查一下, 如果你使用了 |
||||
Operator abs does not support event inputs |
||||
Operator ts_mean does not support event inputs |
||||
Operator ts_scale does not support event inputs |
||||
Operator add does not support event inputs |
||||
Operator sign does not support event inputs |
||||
Operator greater does not support event inputs |
||||
Operator ts_av_diff does not support event inputs |
||||
Operator ts_quantile does not support event inputs |
||||
Operator ts_arg_min does not support event inputs |
||||
Operator divide does not support event inputs |
||||
Operator ts_corr does not support event inputs |
||||
Operator ts_decay_linear does not support event inputs |
||||
Operator ts_sum does not support event inputs |
||||
Operator ts_delay does not support event inputs |
||||
Operator ts_arg_max does not support event inputs |
||||
Operator ts_std_dev does not support event inputs |
||||
Operator ts_regression does not support event inputs |
||||
Operator ts_backfill does not support event inputs |
||||
Operator signed_power does not support event inputs |
||||
Operator ts_product does not support event inputs |
||||
Operator ts_zscore does not support event inputs |
||||
Operator group_rank does not support event inputs |
||||
Operator subtract does not support event inputs |
||||
Operator ts_delta does not support event inputs |
||||
Operator ts_rank does not support event inputs |
||||
Operator ts_count_nans does not support event inputs |
||||
Operator ts_covariance does not support event inputs |
||||
Operator multiply does not support event inputs |
||||
Operator if_else does not support event inputs |
||||
Operator group_neutralize does not support event inputs |
||||
Operator group_zscore does not support event inputs |
||||
Operator winsorize does not support event inputs |
||||
注意, 以上操作符不能使用事件类型的数据集, 以上操作符禁止使用事件类型的数据集!! |
||||
@ -0,0 +1,617 @@ |
||||
跨境技术溢出效应 |
||||
假设 |
||||
在全球化产业链中，若一家公司的海外主要客户或供应商拥有强大的技术创新能力（如高研发投入、高专利质量），则该公司可能通过业务关联，获得隐性的知识外溢与技术扩散益处。这种“技术溢出”能提升该公司的运营效率、产品竞争力或降低其研发风险，从而可能在未来转化为超预期的盈利增长与估值提升。市场对这类隐含的、非线性的增长期权可能存在定价不足。 |
||||
实施方案 |
||||
构建“技术关联强度”因子。识别公司年报或供应链数据中披露的前五大海外客户/供应商，并获取这些关联实体的公开技术创新指标（如人均专利引用量、研发费用增速）。使用加权平均算子，依据交易金额占比为权重，计算公司所关联的海外实体的整体技术强度。使用时序滞后算子，将技术强度数据滞后6-12个月以匹配技术吸收与转化周期，再通过横截面排名评估公司在全市场中的相对技术关联优势。 |
||||
阿尔法因子优化建议 |
||||
技术溢出的效果受公司自身“吸收能力”调节。建议引入公司自身的研发团队质量（如技术人员占比）、内部研发投入强度作为调节变量，通过交互项算子或条件分层处理（例如，仅在自身研发投入超过行业平均的公司样本中，技术关联强度因子才被启用），以更精准地捕捉那些既拥有外部技术源头、又有能力内部化的优质标的。 |
||||
Cross-Border Technology Spillover Effect |
||||
Hypothesis |
||||
In the global industrial chain, if a company's key overseas customers or suppliers possess strong technological innovation capabilities (e.g., high R&D investment, high patent quality), the company may benefit from implicit knowledge spillover and technology diffusion through these business linkages. This "technology spillover" can enhance the company's operational efficiency, product competitiveness, or reduce its R&D risks, potentially translating into unexpected profit growth and valuation appreciation in the future. The market may underprice this implicit, non-linear growth option. |
||||
Implementation Plan |
||||
Construct a "Technology Linkage Intensity" factor. Identify the top five overseas customers/suppliers disclosed in the company's annual reports or supply chain data, and obtain public technological innovation metrics for these linked entities (e.g., patent citations per capita, R&D expense growth rate). Use a weighted average operator, with transaction amount proportion as weights, to calculate the aggregated technological strength of the overseas entities linked to the company. Apply a time-series lag operator to lag the technology strength data by 6-12 months to account for technology absorption and conversion cycles, then assess the company's relative technological linkage advantage across the market via cross-sectional ranking. |
||||
Alpha Factor Optimization Suggestion |
||||
The effect of technology spillover is moderated by the company's own "absorptive capacity." It is suggested to introduce the quality of the company's own R&D team (e.g., proportion of technical staff) and internal R&D intensity as moderating variables. Through interaction term operators or conditional stratification (e.g., enabling the Technology Linkage Intensity factor only within the subsample of companies whose own R&D investment exceeds the industry average), the factor can more precisely identify high-quality targets that possess both external technology sources and the internal capability to assimilate them. |
||||
*=========================================================================================* |
||||
输出格式： |
||||
输出必须是且仅是纯文本。 |
||||
每一行是一个完整、独立、语法正确的WebSim表达式。 |
||||
严禁任何形式的解释、编号、标点包裹（如引号）、Markdown格式或额外文本。 |
||||
===================== !!! 重点(输出方式) !!! ===================== |
||||
现在，请严格遵守以上所有规则，开始生成可立即在WebSim中运行的复合因子表达式。 |
||||
不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 |
||||
**输出格式**(一行一个表达式, 每个表达式中间需要添加一个空行, 只要表达式本身, 不需要赋值, 不要解释, 不需要序号, 也不要输出多余的东西)： |
||||
表达式 |
||||
表达式 |
||||
表达式 |
||||
... |
||||
表达式 |
||||
================================================================= |
||||
重申：请确保所有表达式都使用WorldQuant WebSim平台函数，不要使用pandas、numpy或其他Python库函数。输出必须是一行有效的WQ表达式。 |
||||
以下是我的账号有权限使用的操作符, 请严格按照操作符, 以及我提供的数据集, 进行生成,组合 100 个 alpha： |
||||
不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 |
||||
================================================================= |
||||
ts_product ts_zscore ts_mean ts_scale add sign subtract ts_delta ts_rank greater ts_av_diff ts_quantile ts_count_nans ts_covariance |
||||
ts_arg_min divide ts_corr multiply if_else ts_sum ts_delay group_zscore ts_arg_max ts_std_de ts_backfill |
||||
以上这些操作符不能传入事件类型的数据集, 只能传入时间序列数据集, 不能传入事件数据,不能传入事件数据,不能传入事件数据 |
||||
|
||||
以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子 |
||||
|
||||
========================= 操作符开始 ======================================= |
||||
注意: Operator: 后面的是操作符(是可以使用的), |
||||
Description: 此字段后面的是操作符对应的描述或使用说明(禁止使用, 仅供参考), Description字段后面的内容是使用说明, 不是操作符 |
||||
特别注意!!!! 必须按照操作符字段Operator的使用说明生成 alphaOperator: abs(x) |
||||
Description: Absolute value of x |
||||
Operator: add(x, y, filter = false) |
||||
Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding |
||||
Operator: densify(x) |
||||
Description: Converts a grouping field of many buckets into lesser number of only available buckets so as to make working with grouping fields computationally efficient |
||||
Operator: divide(x, y) |
||||
Description: x / y |
||||
Operator: inverse(x) |
||||
Description: 1 / x |
||||
Operator: log(x) |
||||
Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights. |
||||
Operator: max(x, y, ..) |
||||
Description: Maximum value of all inputs. At least 2 inputs are required |
||||
Operator: min(x, y ..) |
||||
Description: Minimum value of all inputs. At least 2 inputs are required |
||||
Operator: multiply(x ,y, ... , filter=false) |
||||
Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1 |
||||
Operator: power(x, y) |
||||
Description: x ^ y |
||||
Operator: reverse(x) |
||||
Description: - x |
||||
Operator: sign(x) |
||||
Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN; |
||||
Operator: signed_power(x, y) |
||||
Description: x raised to the power of y such that final result preserves sign of x |
||||
Operator: sqrt(x) |
||||
Description: Square root of x |
||||
Operator: subtract(x, y, filter=false) |
||||
Description: x-y. If filter = true, filter all input NaN to 0 before subtracting |
||||
Operator: and(input1, input2) |
||||
Description: Logical AND operator, returns true if both operands are true and returns false otherwise |
||||
Operator: if_else(input1, input2, input 3) |
||||
Description: If input1 is true then return input2 else return input3. |
||||
Operator: input1 < input2 |
||||
Description: If input1 < input2 return true, else return false |
||||
Operator: input1 <= input2 |
||||
Description: Returns true if input1 <= input2, return false otherwise |
||||
Operator: input1 == input2 |
||||
Description: Returns true if both inputs are same and returns false otherwise |
||||
Operator: input1 > input2 |
||||
Description: Logic comparison operators to compares two inputs |
||||
Operator: input1 >= input2 |
||||
Description: Returns true if input1 >= input2, return false otherwise |
||||
Operator: input1!= input2 |
||||
Description: Returns true if both inputs are NOT the same and returns false otherwise |
||||
Operator: is_nan(input) |
||||
Description: If (input == NaN) return 1 else return 0 |
||||
Operator: not(x) |
||||
Description: Returns the logical negation of x. If x is true (1), it returns false (0), and if input is false (0), it returns true (1). |
||||
Operator: or(input1, input2) |
||||
Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise |
||||
Operator: days_from_last_change(x) |
||||
Description: Amount of days since last change of x |
||||
Operator: hump(x, hump = 0.01) |
||||
Description: Limits amount and magnitude of changes in input (thus reducing turnover) |
||||
Operator: kth_element(x, d, k) |
||||
Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1 |
||||
Operator: last_diff_value(x, d) |
||||
Description: Returns last x value not equal to current x value from last d days |
||||
Operator: ts_arg_max(x, d) |
||||
Description: Returns the relative index of the max value in the time series for the past d days. If the current day has the max value for the past d days, it returns 0. If previous day has the max value for the past d days, it returns 1 |
||||
Operator: ts_arg_min(x, d) |
||||
Description: Returns the relative index of the min value in the time series for the past d days; If the current day has the min value for the past d days, it returns 0; If previous day has the min value for the past d days, it returns 1. |
||||
Operator: ts_av_diff(x, d) |
||||
Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation |
||||
Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN") |
||||
Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value) |
||||
Operator: ts_corr(x, y, d) |
||||
Description: Returns correlation of x and y for the past d days |
||||
Operator: ts_count_nans(x ,d) |
||||
Description: Returns the number of NaN values in x for the past d days |
||||
Operator: ts_covariance(y, x, d) |
||||
Description: Returns covariance of y and x for the past d days |
||||
Operator: ts_decay_linear(x, d, dense = false) |
||||
Description: Returns the linear decay on x for the past d days. Dense parameter=false means operator works in sparse mode and we treat NaN as 0. In dense mode we do not. |
||||
Operator: ts_delay(x, d) |
||||
Description: Returns x value d days ago |
||||
Operator: ts_delta(x, d) |
||||
Description: Returns x - ts_delay(x, d) |
||||
Operator: ts_mean(x, d) |
||||
Description: Returns average value of x for the past d days. |
||||
Operator: ts_product(x, d) |
||||
Description: Returns product of x for the past d days |
||||
Operator: ts_quantile(x,d, driver="gaussian" ) |
||||
Description: It calculates ts_rank and apply to its value an inverse cumulative density function from driver distribution. Possible values of driver (optional ) are "gaussian", "uniform", "cauchy" distribution where "gaussian" is the default. |
||||
Operator: ts_rank(x, d, constant = 0) |
||||
Description: Rank the values of x for each instrument over the past d days, then return the rank of the current value + constant. If not specified, by default, constant = 0. |
||||
Operator: ts_regression(y, x, d, lag = 0, rettype = 0) |
||||
Description: Returns various parameters related to regression function |
||||
Operator: ts_scale(x, d, constant = 0) |
||||
Description: Returns (x - ts_min(x, d)) / (ts_max(x, d) - ts_min(x, d)) + constant. This operator is similar to scale down operator but acts in time series space |
||||
Operator: ts_std_dev(x, d) |
||||
Description: Returns standard deviation of x for the past d days |
||||
Operator: ts_step(1) |
||||
Description: Returns days' counter |
||||
Operator: ts_sum(x, d) |
||||
Description: Sum values of x for the past d days. |
||||
Operator: ts_zscore(x, d) |
||||
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean: (x - tsmean(x,d)) / tsstddev(x,d). This operator may help reduce outliers and drawdown. |
||||
Operator: normalize(x, useStd = false, limit = 0.0) |
||||
Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element |
||||
Operator: quantile(x, driver = gaussian, sigma = 1.0) |
||||
Description: Rank the raw vector, shift the ranked Alpha vector, apply distribution (gaussian, cauchy, uniform). If driver is uniform, it simply subtract each Alpha value with the mean of all Alpha values in the Alpha vector |
||||
Operator: rank(x, rate=2) |
||||
Description: Ranks the input among all the instruments and returns an equally distributed number between 0.0 and 1.0. For precise sort, use the rate as 0 |
||||
Operator: scale(x, scale=1, longscale=1, shortscale=1) |
||||
Description: Scales input to booksize. We can also scale the long positions and short positions to separate scales by mentioning additional parameters to the operator |
||||
Operator: winsorize(x, std=4) |
||||
Description: Winsorizes x to make sure that all values in x are between the lower and upper limits, which are specified as multiple of std. |
||||
Operator: zscore(x) |
||||
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean |
||||
Operator: vec_avg(x) |
||||
Description: Taking mean of the vector field x |
||||
Operator: vec_sum(x) |
||||
Description: Sum of vector field x |
||||
Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10") |
||||
Description: Convert float values into indexes for user-specified buckets. Bucket is useful for creating group values, which can be passed to GROUP as input |
||||
Operator: trade_when(x, y, z) |
||||
Description: Used in order to change Alpha values only under a specified condition and to hold Alpha values in other cases. It also allows to close Alpha positions (assign NaN values) under a specified condition |
||||
Operator: group_backfill(x, group, d, std = 4.0) |
||||
Description: If a certain value for a certain date and instrument is NaN, from the set of same group instruments, calculate winsorized mean of all non-NaN values over last d days |
||||
Operator: group_mean(x, weight, group) |
||||
Description: All elements in group equals to the mean |
||||
Operator: group_neutralize(x, group) |
||||
Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant |
||||
Operator: group_rank(x, group) |
||||
Description: Each elements in a group is assigned the corresponding rank in this group |
||||
Operator: group_scale(x, group) |
||||
Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin) |
||||
Operator: group_zscore(x, group) |
||||
Description: Calculates group Z-score - numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. zscore = (data - mean) / stddev of x for each instrument within its group. |
||||
========================= 操作符结束 ======================================= |
||||
|
||||
========================= 数据字段开始 ======================================= |
||||
注意: data_set_name: 后面的是数据字段(可以使用), description: 此字段后面的是数据字段对应的描述或使用说明(不能使用) |
||||
|
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w3_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 5 groups.'} |
||||
{'data_set_name': '可以使用:top300_factor3_group10_score', 'description': '不可使用,仅供参考:Third factor score for top 300 securities, grouped into 10 clusters.'} |
||||
{'data_set_name': '可以使用:pv52_yse_shares_60_299_sec', 'description': '不可使用,仅供参考:Shares from 60 to 299 Seconds'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_css_investor_relations', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Investor Relations'} |
||||
{'data_set_name': '可以使用:health_services_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the health services industry factor.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_z_trend2', 'description': '不可使用,仅供参考:14-day Volume weighted average of Trend of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_2_roe_af_matrix_p1_b_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Return On Equity *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:fnd65_allcap_sedol_curratio', 'description': '不可使用,仅供参考:It is defined as the reported current assets from the most recent quarter divided by the current liabilities from the most recent quarter.'} |
||||
{'data_set_name': '可以使用:short_term_price_momentum_score_3', 'description': '不可使用,仅供参考:Score for price momentum over a short-term period, such as 3 months or 1 week (alternate module).'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w5_pca_fact3_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 20 groups.'} |
||||
{'data_set_name': '可以使用:pv87_webweightedavg20_group_ess_all', 'description': '不可使用,仅供参考:20-day Weighted average of ESS - Event Sentiment Score for group All'} |
||||
{'data_set_name': '可以使用:mdl77_2pricemomemtummodel_rationalalpha', 'description': '不可使用,仅供参考:Rational Decay Alpha: It evaluates stocks based on their historical 12-month market (S&P 500) adjusted excess return (the Y-intercept from an OLS regression equation) using a proprietary rational decay function.'} |
||||
{'data_set_name': '可以使用:anl49_backfill_salesorrevenues', 'description': '不可使用,仅供参考:Total sales revenue less returns, allowances; and sales discounts; also known as net sales.'} |
||||
{'data_set_name': '可以使用:anl44_eps_ratio_best_cur_fiscal_qtr_period', 'description': '不可使用,仅供参考:eps ratio best cur fiscal qtr period'} |
||||
{'data_set_name': '可以使用:max_reported_eps_guidance_2', 'description': '不可使用,仅供参考:Reported Earnings Per Share - Maximum guidance value for the annual period'} |
||||
{'data_set_name': '可以使用:other_executive_singular_plural_pronoun_ratio_presentation', 'description': '不可使用,仅供参考:Ratio of singular to plural pronouns used by other executives in the presentation section.'} |
||||
{'data_set_name': '可以使用:oth460_technical_dma_high_class', 'description': '不可使用,仅供参考:Predicted trend of 6-Day Moving Average of the stock\'s daily high value" (1: fall, 2: neutral, 3: move-up)"'} |
||||
{'data_set_name': '可以使用:pv87_book_value_share_actual', 'description': '不可使用,仅供参考:Book Value / Share Actual'} |
||||
{'data_set_name': '可以使用:sector_value_momentum_rank_float', 'description': '不可使用,仅供参考:Precise sector-relative value-momentum ranking as a floating-point value.'} |
||||
{'data_set_name': '可以使用:pv87_2_roa_af_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Return On Assets *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:other_participant_fkgl_score_qa', 'description': '不可使用,仅供参考:Flesch-Kincaid Grade Level (FKGL) for other participants in Q&A section.'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_pctchgfcf', 'description': "不可使用,仅供参考:1-yr Growth in TTM Free Cash Flow : It is defined as the percent change in a stock's most recent trailing 12-month free cash flow per share (FCF) as compared to the FCF 4 quarters ago."} |
||||
{'data_set_name': '可以使用:anl44_sales_best_cur_fiscal_qtr_period', 'description': '不可使用,仅供参考:sales best cur fiscal qtr period'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg60_group_event_sentiment_score_labor_issues', 'description': '不可使用,仅供参考:60-day Weighted average of Event Sentiment Score for group Labor Issues'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_z_range', 'description': '不可使用,仅供参考:14-day Volume weighted average of Range of Sentiment'} |
||||
{'data_set_name': '可以使用:aerospace_defense_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the aerospace and defense sector factor.'} |
||||
{'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_quick_ratio', 'description': "不可使用,仅供参考:Ratio to indicate the company's ability to pay back its short-term liabilities with its liquid assets"} |
||||
{'data_set_name': '可以使用:mdl230_totalcap_cusip_cashsale', 'description': '不可使用,仅供参考:It is defined as the average cash & equivalents in the trailing 12-month divided by the trailing 12-month sales.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volivcall1', 'description': '不可使用,仅供参考:Weighted average Implied volatility for near in-the-money and out-of-the-money call options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w2_kmeans_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 20 groups.'} |
||||
{'data_set_name': '可以使用:fnd72_q2_repay_ratio', 'description': '不可使用,仅供参考:Measures the percentage of excess cash flow to reimbursement of long-term debts'} |
||||
{'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_chgepsp', 'description': '不可使用,仅供参考:The difference between the most recently reported trailing 12-month earnings per share and that of 4 quarters ago for a stock deflated by its month-end trading price.'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oiivcallmputs7', 'description': '不可使用,仅供参考:implied volatility of near out call minus put options with the same strike prices, which are in the money'} |
||||
{'data_set_name': '可以使用:oth455_partner_roam_w1_pca_fact3_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using the 3rd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:mdl77_2gdna_totalsaleg', 'description': "不可使用,仅供参考:Yearly TTM Total Sales Growth Rate: It is defined as the percent change in a company's trailing 12-month total sales (TOTSALE) as compared to the TOTSALE one year ago."} |
||||
{'data_set_name': '可以使用:avg_recommend_to_peer_score', 'description': '不可使用,仅供参考:Average score indicating if reviewers would recommend the company to a friend.'} |
||||
{'data_set_name': '可以使用:pv87_customerwelfareindustrypercentile_momentum_mean', 'description': '不可使用,仅供参考:Trailing 12m score of Customer Welfare topic'} |
||||
{'data_set_name': '可以使用:pv87_productqualityandsafety_insight_mean', 'description': '不可使用,仅供参考:Long-term score of Product Quality And Safety topic'} |
||||
{'data_set_name': '可以使用:oth455_customer_roam_w2_pca_fact2_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using the 2nd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:info10_tone_score', 'description': '不可使用,仅供参考:Overall sentiment score for the event transcript or story in the info10 module.'} |
||||
{'data_set_name': '可以使用:share_redemption_premium', 'description': '不可使用,仅供参考:Share redemption premium reported for the annual period.'} |
||||
{'data_set_name': '可以使用:fnd3_aacctadj_comstk_divpershare', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Common Stock Dividends Per Share'} |
||||
{'data_set_name': '可以使用:fnd72_a1_net_non_oper_loss_yr_growth', 'description': '不可使用,仅供参考:Percentage change in net non-operating loss from last year to the current year'} |
||||
{'data_set_name': '可以使用:anl44_best_pe_ratio', 'description': '不可使用,仅供参考:best pe ratio'} |
||||
{'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_fcfghc', 'description': '不可使用,仅供参考:1-yr Chg in Assets-adj TTM Free Cash Flow: It is defined as the trailing 12-month free cash flow minus 4 quarters ago trailing 12-month free cash flow divided by the average total assets.'} |
||||
{'data_set_name': '可以使用:oth455_customer_roam_w2_pca_fact1_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using the 1st eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:mdl262_sales_ev', 'description': '不可使用,仅供参考:Sales to Enterprise value ratio of Predictive models'} |
||||
{'data_set_name': '可以使用:mdl26_actual_last_y_revenue', 'description': '不可使用,仅供参考:actual last YEAR revenue'} |
||||
{'data_set_name': '可以使用:pv87_revenue_standard_deviation_scale', 'description': '不可使用,仅供参考:Scale of Revenue - Standard Deviation'} |
||||
{'data_set_name': '可以使用:fnd28_growthratesa_value_08646a', 'description': '不可使用,仅供参考:value of annual field: Operating Income Growth'} |
||||
{'data_set_name': '可以使用:pv87_eps_lt_growth_consensus_low', 'description': '不可使用,仅供参考:EPS LT Growth Consensus Low (%)'} |
||||
{'data_set_name': '可以使用:pv87_indrank_item_5030_364', 'description': '不可使用,仅供参考:Industry ranked item score for item 364 in topic Management Of The Legal Regulatory Environment'} |
||||
{'data_set_name': '可以使用:sales_surprise_score', 'description': '不可使用,仅供参考:Sales Surprise'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p50_q200_w4_pca_fact1_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 1st eigenvalue of PCA into 20 groups.'} |
||||
{'data_set_name': '可以使用:pv87_2_capex_qf_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Capital Expenditure *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:mdl262_saleq_profitability_profitability1', 'description': '不可使用,仅供参考:1st profitability field of Sales/Turnover (Net)'} |
||||
{'data_set_name': '可以使用:fnd72_q1_depr_exp_yr_growth', 'description': '不可使用,仅供参考:Percentage increase or decrease of depreciation expenses by comparing current period with same period prior year'} |
||||
{'data_set_name': '可以使用:pv87_2_netdebt_qf_matrix_p1_b_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg60_group_nip_revenues', 'description': '不可使用,仅供参考:60-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Revenues'} |
||||
{'data_set_name': '可以使用:energy_sector_factor4_group2_score', 'description': '不可使用,仅供参考:Fourth factor score for energy sector, grouped into 2 clusters.'} |
||||
{'data_set_name': '可以使用:star_si_cap_rank', 'description': '不可使用,仅供参考:the market cap group 1~100 percentile rank of the stock versus all other US trading stocks'} |
||||
{'data_set_name': '可以使用:mdl77_historicalgrowthfactor_pfcghc', 'description': '不可使用,仅供参考:The difference between the trailing 12-month cash flow per share and that of 12 quarters ago for a stock divided by its trading price.'} |
||||
{'data_set_name': '可以使用:comm_sector_factor2_group5_score', 'description': '不可使用,仅供参考:Second factor score for communications sector, grouped into 5 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetacall8', 'description': '不可使用,仅供参考:theta of near in call options'} |
||||
{'data_set_name': '可以使用:mdl109_es_sale_ntm_r3m', 'description': '不可使用,仅供参考:NTM revenue revision, 3M'} |
||||
{'data_set_name': '可以使用:pv87_prv2_expavg20_group_event_sentiment_score_labor_issues', 'description': '不可使用,仅供参考:20-day Exponential average of Event Sentiment Score for group Labor Issues'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_ew_sent_mean_std', 'description': '不可使用,仅供参考:14-day Volume weighted average of Standard deviation of Sentiment Average'} |
||||
{'data_set_name': '可以使用:pv87_v2_simpleavg20_group_event_sentiment_score_equity_actions', 'description': '不可使用,仅供参考:20-day Simple average of Event Sentiment Score for group Equity Actions'} |
||||
{'data_set_name': '可以使用:anl49_backfill_cashflowpershareindicator', 'description': '不可使用,仅供参考:Cash flow per share indicator'} |
||||
{'data_set_name': '可以使用:pv87_web_weightedavg20_group_css_earnings', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Earnings'} |
||||
{'data_set_name': '可以使用:mdl77_historicalgrowthfactor_salesaccel4q', 'description': '不可使用,仅供参考:4-Quarter Sales Acceleration: It is defined as the slope of the regression line between year-over-year sales growth and time.'} |
||||
{'data_set_name': '可以使用:anl14_numofests_revenue_fy3', 'description': '不可使用,仅供参考:Num of Estimations of Revenue - upcoming 3 years'} |
||||
{'data_set_name': '可以使用:anl10_fcfpast_det_excflag_1633', 'description': '不可使用,仅供参考:Exclusion flag for free cash flow estimates'} |
||||
{'data_set_name': '可以使用:mws50_country_code', 'description': "不可使用,仅供参考:The two character ISO-3166 country code associated with an entity. Companies and organizations are associated with the country of incorporation, currencies are associated with the country where the central bank resides, and commodities are global and not associated with specific countries, so their COUNTRY_CODE label is 'XX'"} |
||||
{'data_set_name': '可以使用:pv87_buy_sharesdivhold_sum', 'description': '不可使用,仅供参考:Sum of Buying Shares / Holdings'} |
||||
{'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:mdl354_group_pt1sale_ev', 'description': '不可使用,仅供参考:Revenue/TEV'} |
||||
{'data_set_name': '可以使用:anl69_eqy_dvd_ex_flag', 'description': '不可使用,仅供参考:Ex-Dividend Flag'} |
||||
{'data_set_name': '可以使用:mdl77_historicalgrowthfactor_y3fcq4rqsr', 'description': '不可使用,仅供参考:R-Sqr of 3-yr TTM Cash Flow Trend Line: It is defined as the conditional square of the correlation between monthly dates and the corresponding trailing 12-month cash flow per share in the prior 12 quarters.'} |
||||
{'data_set_name': '可以使用:pv87_2_epsr_af_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Earnings Per Share - As Reported *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:fnd65_totalcap_cusip_curratio', 'description': '不可使用,仅供参考:It is defined as the reported current assets from most recent quarter divided by the current liabilities from most recent quarter.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volivcallmput9', 'description': '不可使用,仅供参考:Weighted average Implied volatility for deep in-the-money call and put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:oth460_share_chg_l2', 'description': '不可使用,仅供参考:The probability that the future trend of YoY change in share count" will be neutral"'} |
||||
{'data_set_name': '可以使用:mdl15_mixed_score', 'description': '不可使用,仅供参考:Probability of outperformance in the next 6 months is measured by this score.'} |
||||
{'data_set_name': '可以使用:oth432_saleq_profitability_profitability4', 'description': '不可使用,仅供参考:4th profitability field of Sales/Turnover (Net)'} |
||||
{'data_set_name': '可以使用:mdl37_bk_global_rank', 'description': "不可使用,仅供参考:The global 1-100 percentile rank of a company's 1-year default probability"} |
||||
{'data_set_name': '可以使用:anl69_cest_sales', 'description': '不可使用,仅供参考:Sales'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_chgocfp', 'description': '不可使用,仅供参考:The difference between the most recently reported trailing 12-month operating cash flow per share and that of 4 quarters ago for a stock divided by its trading price.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_mean_tsrank', 'description': '不可使用,仅供参考:14-day Volume weighted average of End-of-day time series rank of Sentiment Average'} |
||||
{'data_set_name': '可以使用:sales_revenue_total_2', 'description': '不可使用,仅供参考:Total sales or revenue generated during the period.'} |
||||
{'data_set_name': '可以使用:anl44_second_en_sales_value', 'description': '不可使用,仅供参考:sales value'} |
||||
{'data_set_name': '可以使用:management_ethics_industry_rank', 'description': '不可使用,仅供参考:Company’s rank within its industry peer group for management standards and ethics.'} |
||||
{'data_set_name': '可以使用:pv87_2_ebitda_qf_matrix_p1_b_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of EBITDA *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:credit_risk_country_percentile_score_float_3', 'description': '不可使用,仅供参考:Country-level percentile rank of credit risk as a floating point value (third source).'} |
||||
{'data_set_name': '可以使用:pv87_revenue_surprise', 'description': '不可使用,仅供参考:Revenue Surprise %'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted28d_ew_sent_z_tsrank', 'description': '不可使用,仅供参考:28-day Volume weighted average of End-of-day time series rank of Sentiment'} |
||||
{'data_set_name': '可以使用:mdl177_fa_aspanratio', 'description': '不可使用,仅供参考:Attention Span Ratio'} |
||||
{'data_set_name': '可以使用:mid_term_price_momentum_score_2', 'description': '不可使用,仅供参考:Score for price momentum over a medium-term period, such as 6 months.'} |
||||
{'data_set_name': '可以使用:fnd2_itxreclnondeductibleexp', 'description': '不可使用,仅供参考:Amount of the difference between reported income tax expense (benefit) and expected income tax expense (benefit) computed by applying the domestic federal statutory income tax rates to pretax income (loss) from continuing operations attributable to nondeductible expenses.'} |
||||
{'data_set_name': '可以使用:mdl177_2_globaldevnorthamerica_v502_totalsaleg', 'description': "不可使用,仅供参考:Yearly TTM Total Sales Growth Rate : It is defined as the percent change in a company's trailing 12-month total sales (TOTSALE) as compared to the TOTSALE one year ago."} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_r6_cash_flow_share_consensus_mean_numanalystsunfiltered', 'description': '不可使用,仅供参考:Number of analysts (unfiltered) of Cash Flow / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:mdl230_allcap_sedol_cg3ysales', 'description': '不可使用,仅供参考:It is defined as the geometric growth rate of the trailing 12-month sales per share in the last 12 quarters.'} |
||||
{'data_set_name': '可以使用:pv87_indrank_item_1030_350', 'description': '不可使用,仅供参考:Industry ranked item score for item 350 in topic Energy Management'} |
||||
{'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_b_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p10_q50_w3_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 5 groups.'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p50_q200_w3_kmeans_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 20 groups.'} |
||||
{'data_set_name': '可以使用:fnd72_a1_liab_growth', 'description': '不可使用,仅供参考:Percentage change in total liabilities from last year to the current year'} |
||||
{'data_set_name': '可以使用:pv87_webv2_expavg20_group_event_sentiment_score_stock_prices', 'description': '不可使用,仅供参考:20-day Exponential average of Event Sentiment Score for group Stock Prices'} |
||||
{'data_set_name': '可以使用:pv87_v2_expavg20_group_css_partnerships', 'description': '不可使用,仅供参考:20-day Exponential average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Partnerships'} |
||||
{'data_set_name': '可以使用:mdl77_garpanalystmodel_qgp_growthval', 'description': '不可使用,仅供参考:Growth Valuation : Growth Valuation'} |
||||
{'data_set_name': '可以使用:electrical_equipment_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the electrical equipment sector factor.'} |
||||
{'data_set_name': '可以使用:pv87_v2_simpleavg60_group_event_sentiment_score_price_targets', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for group Price Targets'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_sent_std_tsrank', 'description': '不可使用,仅供参考:28-day Volume weighted average of End-of-day time series rank of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:oth432_saleq_profitability_profitability8', 'description': '不可使用,仅供参考:8th profitability field of Sales/Turnover (Net)'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p50_q50_w4_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:buyside_cli_score_qa', 'description': '不可使用,仅供参考:Coleman–Liau Index (CLI) for buy-side investors in Q&A section.'} |
||||
{'data_set_name': '可以使用:pv87_interval_slippageinterval_volume_rankcorrel', 'description': '不可使用,仅供参考:Rank correlation between interval slippage and volume'} |
||||
{'data_set_name': '可以使用:pv87_2_eps_qf_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Earnings Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volthetacallmput9', 'description': '不可使用,仅供参考:Weighted average Theta for deep in-the-money call and put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:current_price_to_intrinsic_value_ratio', 'description': '不可使用,仅供参考:Ratio of the current share price to the calculated intrinsic value.'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_book_value_share_consensus_mean_numup', 'description': '不可使用,仅供参考:Number of up revisions of Book Value / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p50_q50_w3_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:mdl177_2_managementqualityfactor_sga', 'description': '不可使用,仅供参考:SG&A Expenses-to-Sales : It is defined as the trailing 12-month selling, general management, and administration expenses divided by the trailing 12-month sales.'} |
||||
{'data_set_name': '可以使用:pv87_weightedavg1_group_ess_revenues', 'description': '不可使用,仅供参考:1-day Weighted average of ESS - Event Sentiment Score for group Revenues'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_event_sentiment_score_assets', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Assets'} |
||||
{'data_set_name': '可以使用:pv87_prv2_simpleavg1_group_event_sentiment_score_acquisitions_mergers', 'description': '不可使用,仅供参考:1-day Simple average of Event Sentiment Score for group Acquisitions Mergers'} |
||||
{'data_set_name': '可以使用:pv87_prv2_expavg60_group_css_partnerships', 'description': '不可使用,仅供参考:60-day Exponential average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Partnerships'} |
||||
{'data_set_name': '可以使用:assetutilization_neutral_score', 'description': '不可使用,仅供参考:Neutral sentiment score for asset utilization in a transcript chunk.'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg60_group_css_credit_ratings', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Credit Ratings'} |
||||
{'data_set_name': '可以使用:pv87_2_bps_qf_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Book Value Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:news_pct_10min', 'description': '不可使用,仅供参考:The percent change in price in the first 10 minutes following the news release'} |
||||
{'data_set_name': '可以使用:pv87_2_dps_af_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Dividends Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:mdl230_us5000_cusip_flowratio', 'description': '不可使用,仅供参考:It is defined as the difference between current assets and cash & equivalents divided by the difference between current liabilities and short-term debt. All items are from the most recent quarter.'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p10_q50_w4_kmeans_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 20 groups.'} |
||||
{'data_set_name': '可以使用:pv52_yse_chicago_shares_60_299_sec', 'description': '不可使用,仅供参考:Shares from 60 to 299 Seconds'} |
||||
{'data_set_name': '可以使用:mdl262_trkdpitpredictiverndexpense_mad_act', 'description': '不可使用,仅供参考:Mean Absolute Deviation of scaled actual value of Research&Development Expense'} |
||||
{'data_set_name': '可以使用:social_pillar_composite_score', 'description': '不可使用,仅供参考:Aggregated score representing company’s overall social performance.'} |
||||
{'data_set_name': '可以使用:pv87_hitscore_wordcount_mean', 'description': '不可使用,仅供参考:Mean of Total number of words in the Post'} |
||||
{'data_set_name': '可以使用:snt26_topranking_10', 'description': '不可使用,仅供参考:The top ranking'} |
||||
{'data_set_name': '可以使用:anl49_vector_3rdfiscalquartersalesorrevenues', 'description': '不可使用,仅供参考:Third fiscal quarter sales or revenues as reported.'} |
||||
{'data_set_name': '可以使用:pv87_v2_simpleavg60_group_event_sentiment_score_legal', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for group Legal'} |
||||
{'data_set_name': '可以使用:pv87_2_capex_qf_matrix_p1_b_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Capital Expenditure *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_scores_uncertaintypartnormscr_std', 'description': '不可使用,仅供参考:Standard deviation of Uncertainity partial score'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg20_group_event_sentiment_score_assets', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Assets'} |
||||
{'data_set_name': '可以使用:buyback_yield_relative_component_rank', 'description': '不可使用,仅供参考:Global rank for the share buyback yield component in the valuation model.'} |
||||
{'data_set_name': '可以使用:tech_sector_factor4_group20_score', 'description': '不可使用,仅供参考:Fourth factor score for technology sector, grouped into 20 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg60_group_nip_acquisitions_mergers', 'description': '不可使用,仅供参考:60-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Acquisitions Mergers'} |
||||
{'data_set_name': '可以使用:pv87_webweightedavg60_group_ess_dividends', 'description': '不可使用,仅供参考:60-day Weighted average of ESS - Event Sentiment Score for group Dividends'} |
||||
{'data_set_name': '可以使用:operating_expense', 'description': '不可使用,仅供参考:Operating Expense - Total'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_z_median', 'description': '不可使用,仅供参考:14-day Volume weighted average of Median of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple14d_ew_sent_mean_tsrank', 'description': '不可使用,仅供参考:14-day Simple average of End-of-day time series rank of Sentiment Average'} |
||||
{'data_set_name': '可以使用:oth335_combined_all_region_mind', 'description': '不可使用,仅供参考:Final composite MIND score'} |
||||
{'data_set_name': '可以使用:pv87_v2item_indrank_item_6030_221', 'description': '不可使用,仅供参考:Industry ranked item score for item 221 in topic Board Structure'} |
||||
{'data_set_name': '可以使用:fnd72_pit_or_cr_q_ev_to_t12m_sales', 'description': '不可使用,仅供参考:Periodic enterprise value as a multiple of sales'} |
||||
{'data_set_name': '可以使用:fnd72_a2_sales_to_tot_asset', 'description': '不可使用,仅供参考:Assets turnover ratio represents the amount of sales or revenues generated per dollar of assets'} |
||||
{'data_set_name': '可以使用:pv87_2_ebitda_qf_matrix_p1_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of EBITDA *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_revenue_estimate_2_yr_annual_growth_scale', 'description': '不可使用,仅供参考:Scale of Revenue Estimate - 2 Yr Annual Growth %'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q50_w2_pca_fact2_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:utilities_method2_group20_score', 'description': '不可使用,仅供参考:Score from the second method for utilities sector, grouped into 20 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_css_labor_issues', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Labor Issues'} |
||||
{'data_set_name': '可以使用:oth432_saleq_profitability_profitability5', 'description': '不可使用,仅供参考:5th profitability field of Sales/Turnover (Net)'} |
||||
{'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volvegaput5', 'description': '不可使用,仅供参考:Weighted average Vega for in-the-money put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:governance_corr_weighted_sector_percentile', 'description': '不可使用,仅供参考:Company’s percentile within its sector based on governance score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:top200_method3_group20_score', 'description': '不可使用,仅供参考:Score from the third method for top 200 securities, grouped into 20 clusters.'} |
||||
{'data_set_name': '可以使用:common_shares_outstanding_quarter_2', 'description': '不可使用,仅供参考:Number of common shares outstanding at quarter end.'} |
||||
{'data_set_name': '可以使用:headline_negative_sentiment_score', 'description': '不可使用,仅供参考:Negative sentiment score derived from the news headline.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oigammaput5', 'description': '不可使用,仅供参考:Weighted average Gamma for in-the-money put options with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:anl49_vector_dividendsdeclaredpershare', 'description': "不可使用,仅供参考:The common dividends divided by the weighted average number of shares that were declared during the company's fiscal year (but not necessarily paid during the same year)."} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w4_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:mdl177_earningsqualityfactor_uinv_alt', 'description': '不可使用,仅供参考:The difference of inventory between present and expected levels.'} |
||||
{'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_b_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:sentiment2_raw_score', 'description': '不可使用,仅供参考:Raw value of the second sentiment metric for the entity.'} |
||||
{'data_set_name': '可以使用:mdl354_sector_pt1country', 'description': '不可使用,仅供参考:2-digit ISO Country Code'} |
||||
{'data_set_name': '可以使用:pv48_r3000_shares_cur_growth', 'description': '不可使用,仅供参考:Current growth shares for the US 3000 index.'} |
||||
{'data_set_name': '可以使用:insd3_10q_freq_flag', 'description': '不可使用,仅供参考:10-Q Frequency Flag'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volivcallmput1', 'description': '不可使用,仅供参考:Weighted average Implied volatility for near in-the-money and out-of-the-money call and put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p50_q200_w1_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 5 groups.'} |
||||
{'data_set_name': '可以使用:mdl230_totalcap_cusip_impduration', 'description': "不可使用,仅供参考:It is an equity risk measure based on Macaulay's traditional measure of bond duration. It combines book value, expected growth, expected profitability, and current stock trading price."} |
||||
{'data_set_name': '可以使用:coverage_sources_cash_flow_per_share', 'description': '不可使用,仅供参考:List or indicator of which data sources have covered the cash flow per share forecast.'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg60_topic_nip_business', 'description': '不可使用,仅供参考:60-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for topic Business'} |
||||
{'data_set_name': '可以使用:airlines_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the airlines industry factor.'} |
||||
{'data_set_name': '可以使用:mdl264_call_put_erlanger_ratio_l1', 'description': "不可使用,仅供参考:The probability that the future trend of 'Premium Ratio' will fall"} |
||||
{'data_set_name': '可以使用:mdl354_sector_pt2sale_sur', 'description': '不可使用,仅供参考:Revenue surprise (vs consensus)'} |
||||
{'data_set_name': '可以使用:pv87_2_dps_qf_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Dividends Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_2_fcfps_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Financing Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:fn_comp_options_exercisable_weighted_avg_q', 'description': '不可使用,仅供参考:The weighted-average price as of the balance sheet date at which grantees can acquire the shares reserved for issuance on vested portions of options outstanding and currently exercisable under the stock option plan.'} |
||||
{'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:composite_factor_score_derivative', 'description': '不可使用,仅供参考:Change in overall composite factor score from the prior period.'} |
||||
{'data_set_name': '可以使用:anl10_epsinnovation_score_fq1', 'description': '不可使用,仅供参考:Innovation score for earnings per share Q1 (innovate_increase - innovate_decrease)'} |
||||
{'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_b_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oivegacallmput5', 'description': '不可使用,仅供参考:Weighted average Vega for in-the-money call and put options with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:principal_component_score_9_top3000', 'description': '不可使用,仅供参考:Value of the ninth principal component for the top 3000 securities.'} |
||||
{'data_set_name': '可以使用:oth567score_culture_341', 'description': '不可使用,仅供参考:Culture score'} |
||||
{'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_b_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oigammacallmputs6', 'description': '不可使用,仅供参考:Weighted average Gamma for far out-of-the-money call options and put options with the same strike prices with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_2_ebit_af_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of EBIT *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_ew_sent_z_deviation', 'description': '不可使用,仅供参考:28-day Volume weighted average of Deviation of Sentiment'} |
||||
{'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_fcghc', 'description': '不可使用,仅供参考:1-yr Change in Assets-adj TTM Cash Flow: It is defined as the trailing 12-month cash flow minus comparable trailing 12-month cash flow from 4 quarters ago scaled by the average total assets.'} |
||||
{'data_set_name': '可以使用:pv173_zscoresatlas_unit_name', 'description': '不可使用,仅供参考:Atlas unit name'} |
||||
{'data_set_name': '可以使用:mdl77_oearningsqualityfactor_indrelrecd_', 'description': "不可使用,仅供参考:Industry-Adjusted Doubtful Account Receivables: It is defined as a stock's asset-adjusted annual doubtful receivables minus the average of the receivables of all stocks in the same industry deflated by the standard deviation of these receivables."} |
||||
{'data_set_name': '可以使用:pv87_2_bps_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Book Value Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:resource_efficiency_subsector_rank', 'description': '不可使用,仅供参考:Company’s rank within its subsector peer group for resource efficiency.'} |
||||
{'data_set_name': '可以使用:anl14_low_revenue_fp1', 'description': '不可使用,仅供参考:The lowest estimation of revenue - upcoming quarter'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple7d_ew_sent_z_tsrank', 'description': '不可使用,仅供参考:tsrank of Sentiment'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p50_q50_w1_pca_fact2_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 2nd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:share_premium', 'description': '不可使用,仅供参考:Total value of share premium or additional paid-in capital.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volgammaput7', 'description': '不可使用,仅供参考:Weighted average Gamma for near out-of-the-money put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_sent_z_range', 'description': '不可使用,仅供参考:14-day Volume weighted average of Range of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_nip_marketing', 'description': '不可使用,仅供参考:20-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Marketing'} |
||||
{'data_set_name': '可以使用:pv87_webv2_simpleavg20_group_css_partnerships', 'description': '不可使用,仅供参考:20-day Simple average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Partnerships'} |
||||
{'data_set_name': '可以使用:anl10_prrrevise_ratio_to_consensus_fy2_2571', 'description': '不可使用,仅供参考:Consensus estimate value for price return ratio FY2'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volthetaput4', 'description': '不可使用,仅供参考:Weighted average Theta for near-the-money put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_interval_asksizeinterval_bidsize_rankcorrel', 'description': '不可使用,仅供参考:Rank correlation between interval ask size and bid size'} |
||||
{'data_set_name': '可以使用:credit_risk_news_component_score_float_2', 'description': '不可使用,仅供参考:Credit risk score from news articles, as a floating point value (alternate source).'} |
||||
{'data_set_name': '可以使用:mdl264_prior_short_rank_class', 'description': '不可使用,仅供参考:Predicted trend of "Previous reporting periods value" (1: fall, 2: neutral, 3: move-up)'} |
||||
{'data_set_name': '可以使用:pv87_grossdiv3ygrowthrate', 'description': '不可使用,仅供参考:Last of dividend growth rate in 3 years, where rate = 100 * ((annual dividend per share/annual DPS 3 years ago)^(1/3)-1)'} |
||||
{'data_set_name': '可以使用:social_corr_weighted_score', 'description': '不可使用,仅供参考:Social score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:info10_positive_sentiment_score_simple_fast_d1', 'description': '不可使用,仅供参考:Score representing the degree of positive sentiment in the event transcript or story (simple version).'} |
||||
{'data_set_name': '可以使用:mdl26_v14_prsprise_pct_fy1_revenue', 'description': '不可使用,仅供参考:predicted surprise (actual value - predicted value) percentage FYEAR1 revenue'} |
||||
{'data_set_name': '可以使用:anl69_best_sales_median', 'description': '不可使用,仅供参考:Sales Median'} |
||||
{'data_set_name': '可以使用:anl11_regionsectcount', 'description': '不可使用,仅供参考:Region Sector Count'} |
||||
{'data_set_name': '可以使用:mdl230_allcap_sedol_rationalalpha', 'description': '不可使用,仅供参考:It evaluates stocks based on their historical 12-month market (S&P 500) adjusted excess return (the Y intercept from an OLS regression equation) using a proprietary rational decay function.'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volthetaput6', 'description': '不可使用,仅供参考:theta volume of far out put options'} |
||||
{'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_b_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Sales'} |
||||
{'data_set_name': '可以使用:credit_risk_region_percentile_score_float', 'description': '不可使用,仅供参考:Region-level percentile rank of credit risk as a floating point value.'} |
||||
{'data_set_name': '可以使用:analyst_gfi_score_presentation', 'description': '不可使用,仅供参考:Gunning Fog Index (GFI) for analysts in presentation section.'} |
||||
{'data_set_name': '可以使用:pv87_book_value_share_difference', 'description': '不可使用,仅供参考:Book Value / Share Difference'} |
||||
{'data_set_name': '可以使用:pv87_2_cfps_qf_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv52_yse_chicago_tot_cov_shares', 'description': '不可使用,仅供参考:Total Covered Shares'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_sent_mean_median', 'description': '不可使用,仅供参考:7-day Volume weighted average of Median of Sentiment Average'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_cash_flow_share_consensus_mean_numup', 'description': '不可使用,仅供参考:Number of up revisions of Cash Flow / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:mdl177_2_earningsqualityfactor_saleeps', 'description': '不可使用,仅供参考:Change in TTM Sales vsEPS : It is defined as the absolute value of the difference between the yearly percent change in trailing 12-month sales per share and the yearly percent change in trailing 12-month diluted earnings per share before extraordinary items.'} |
||||
{'data_set_name': '可以使用:pv87_revenue_difference_scale', 'description': '不可使用,仅供参考:Scale of Revenue Difference'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg60_group_event_sentiment_score_equity_actions', 'description': '不可使用,仅供参考:60-day Weighted average of Event Sentiment Score for group Equity Actions'} |
||||
{'data_set_name': '可以使用:fnd28_growthratesa_value_08615a', 'description': '不可使用,仅供参考:value of annual field: Dividends Per Share - 5 Yr Annual Growth'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_std_tsrank', 'description': '不可使用,仅供参考:14-day Volume weighted average of End-of-day time series rank of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:rsk62_beta_factor_1_100_growth', 'description': '不可使用,仅供参考:eps growth'} |
||||
{'data_set_name': '可以使用:capex_to_depreciation_linkage', 'description': '不可使用,仅供参考:Capital Expenditures to Depreciation Linkage'} |
||||
{'data_set_name': '可以使用:mdl26_arm_score_change_3', 'description': '不可使用,仅供参考:score change for days: 3'} |
||||
{'data_set_name': '可以使用:pv87_2_fcfps_qf_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Financing Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_2_dps_qf_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Dividends Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:min_adjusted_funds_from_operations_guidance_2', 'description': '不可使用,仅供参考:Adjusted funds from operation - minimum guidance for the annual period'} |
||||
{'data_set_name': '可以使用:anl10_dpspast_det_estflag_1230', 'description': '不可使用,仅供参考:Estimate flag for dividends per share'} |
||||
{'data_set_name': '可以使用:oth455_partner_roam_w1_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:energy_sector_factor4_group5_score', 'description': '不可使用,仅供参考:Fourth factor score for energy sector, grouped into 5 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_sent_z_range', 'description': '不可使用,仅供参考:7-day Volume weighted average of Range of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_marketimpactscore_sum', 'description': '不可使用,仅供参考:Sum of Market impact score - The estimated risk-adjusted 1 minute forward return for a given article as measured by stock return minus the stock beta multiplied market return, -5 being most negative impact and +5 most positive'} |
||||
{'data_set_name': '可以使用:anl14_mean_revenue_fp2', 'description': '不可使用,仅供参考:Mean of Estimations of Revenue - upcoming 2 quarters'} |
||||
{'data_set_name': '可以使用:mdl31_bv_share_last_qtr', 'description': '不可使用,仅供参考:The ratio of the Book Value to the total shares outstanding.'} |
||||
{'data_set_name': '可以使用:mdl77_historicalgrowthfactor_fcfghc', 'description': '不可使用,仅供参考:1-yr Chg in Assets-adj TTM Free Cash Flow: It is defined as the trailing 12-month free cash flow minus 4 quarters ago trailing 12-month free cash flow divided by the average total assets.'} |
||||
{'data_set_name': '可以使用:pv87_webv2_simpleavg60_group_css_partnerships', 'description': '不可使用,仅供参考:60-day Simple average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Partnerships'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_sent_mean_tsrank', 'description': '不可使用,仅供参考:28-day Volume weighted average of End-of-day time series rank of Sentiment Average'} |
||||
{'data_set_name': '可以使用:credit_risk_industry_percentile_score_float_2', 'description': '不可使用,仅供参考:Industry-level percentile rank of credit risk as a floating point value (alternate source).'} |
||||
{'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:tech_sector_factor1_group2_score', 'description': '不可使用,仅供参考:First factor score for technology sector, grouped into 2 clusters.'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p50_q50_w3_pca_fact1_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 1st eigenvalue of PCA into 20 groups.'} |
||||
{'data_set_name': '可以使用:oth176_lmt_open_eq_score', 'description': '不可使用,仅供参考:Model Composite Score'} |
||||
{'data_set_name': '可以使用:mdl177_2_managementqualityfactor_opmb', 'description': '不可使用,仅供参考:Operating Profit Margin : It is defined as the most recently reported quarterly operating income divided by the corresponding quarterly sales.'} |
||||
{'data_set_name': '可以使用:oth455_partner_roam_w3_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using K-means into 10 groups.'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_r6_cash_flow_share_consensus_mean_numnochange', 'description': '不可使用,仅供参考:Number of no change revisions of Cash Flow / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:pv87_daily_ann_matrix_r1_net_asset_value_share_consensus_mean_numdownunfiltered', 'description': '不可使用,仅供参考:Number of down revisions (unfiltered) of Net Asset Value / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:se_pos_score', 'description': '不可使用,仅供参考:number of positive words/number of all words.'} |
||||
{'data_set_name': '可以使用:top300_factor3_group2_score', 'description': '不可使用,仅供参考:Third factor score for top 300 securities, grouped into 2 clusters.'} |
||||
{'data_set_name': '可以使用:mdl354_group_pt1gr_fy2_sale', 'description': '不可使用,仅供参考:FY2 Revenue growth'} |
||||
{'data_set_name': '可以使用:mdl354_group_pt1es_sale_fy1_r1m', 'description': '不可使用,仅供参考:FY1 revenue revision, 1M'} |
||||
{'data_set_name': '可以使用:pv87_book_value_share_consensus_low_scale', 'description': '不可使用,仅供参考:Scale of Book Value / Share Consensus Low'} |
||||
{'data_set_name': '可以使用:fnd6_newqeventv110_mibtq', 'description': '不可使用,仅供参考:Noncontrolling Interests - Total - Balance Sheet - Quarterly'} |
||||
{'data_set_name': '可以使用:previous_forecast_value_cash_flow_per_share', 'description': '不可使用,仅供参考:Previous forecasted value for cash flow per share before the current estimate.'} |
||||
{'data_set_name': '可以使用:service_contract_revenue', 'description': '不可使用,仅供参考:[Quarterly] Service Cost - Domestic'} |
||||
{'data_set_name': '可以使用:pv52_yse_arca_atquote_shares', 'description': '不可使用,仅供参考:At-the Quote Shares'} |
||||
{'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_pretax_inc_to_net_sales', 'description': '不可使用,仅供参考:Pre-tax income as a percentage of net sales'} |
||||
{'data_set_name': '可以使用:pv20_country_code', 'description': '不可使用,仅供参考:ISO country code for the data.'} |
||||
{'data_set_name': '可以使用:pv87_weightedavg60_group_ess_all', 'description': '不可使用,仅供参考:60-day Weighted average of ESS - Event Sentiment Score for group All'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg60_group_nip_marketing', 'description': '不可使用,仅供参考:60-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Marketing'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_chg3ycfast_alt', 'description': '不可使用,仅供参考:3-yr Change in Assets-adj TTM Cash Flow : It is defined as the most recently reported trailing 12-month operating cash flow minus 12-quarter ago comparable trailing 12-month cash flow scaled by the average total assets in the same period.'} |
||||
{'data_set_name': '可以使用:sustainability_corr_weighted_subsector_position', 'description': '不可使用,仅供参考:Company’s position within its subsector based on sustainability score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:oth455_partner_roam_w2_pca_fact2_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using the 2nd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:anl69_id_bb_prim_security_flag', 'description': '不可使用,仅供参考:Equity Primary Security Flag'} |
||||
{'data_set_name': '可以使用:anl49_backfill_4thfiscalquartersalesorrevenues', 'description': '不可使用,仅供参考:Fiscal quarter sales or revenues as reported.'} |
||||
{'data_set_name': '可以使用:info10_expiration_date', 'description': '不可使用,仅供参考:The date when the info10 data record is set to expire or become inactive.'} |
||||
{'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:common_shares_outstanding', 'description': '不可使用,仅供参考:Number of common shares currently issued and outstanding.'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_r6_capital_expenditure_consensus_mean_numupunfiltered', 'description': '不可使用,仅供参考:Number of up revisions of Capital Expenditure Consensus Mean'} |
||||
{'data_set_name': '可以使用:mdl39_1_val_mo_sector_rank', 'description': '不可使用,仅供参考:Sector-relative 1-100 ranking of the Val-Mo model'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volvegaput9', 'description': '不可使用,仅供参考:Weighted average Vega for deep in-the-money put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:fnd72_a1_cfo_to_sales', 'description': '不可使用,仅供参考:Measures the percentage of Cash from Operations to Sales'} |
||||
{'data_set_name': '可以使用:latest_annual_period_end_update_dividend_per_share', 'description': '不可使用,仅供参考:Date or timestamp when the annual period end for dividend per share was last updated.'} |
||||
{'data_set_name': '可以使用:pv87_2_ebitda_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of EBITDA *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:top200_method3_group10_score', 'description': '不可使用,仅供参考:Score from the third method for top 200 securities, grouped into 10 clusters.'} |
||||
{'data_set_name': '可以使用:fnd28_annualforeign_value_08711a', 'description': '不可使用,仅供参考:value of annual field: Foreign Return on Assets'} |
||||
{'data_set_name': '可以使用:mdl77_historicalgrowthfactor_y3speq4vc', 'description': "不可使用,仅供参考:Stability of 3-yr TTM Earnings per Share: It is defined as the standard deviation of the last 12 quarters' trailing 12-month earnings per share (EPS) divided by the mean of these EPS's."} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oithetacallmput8', 'description': '不可使用,仅供参考:Weighted average Theta for near in-the-money call and put options with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:inst4_tran_shares', 'description': '不可使用,仅供参考:The as-reported number of shares acquired or disposed'} |
||||
{'data_set_name': '可以使用:mdl177_2_growthanalystmodel_qga_composite', 'description': '不可使用,仅供参考:Growth Analyst Composite'} |
||||
{'data_set_name': '可以使用:se_neg_score', 'description': '不可使用,仅供参考:number of negative words/number of all words.'} |
||||
{'data_set_name': '可以使用:fnd28_annualforeign_value_08745a', 'description': '不可使用,仅供参考:value of annual field: Foreign Income % Total Income Other Fields'} |
||||
{'data_set_name': '可以使用:relative_valuation_regional_position_v3', 'description': '不可使用,仅供参考:Regional rank of a stock based on its relative valuation score (variant 3).'} |
||||
{'data_set_name': '可以使用:quarterly_common_dividend_per_share', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Common Stock Dividends Per Share'} |
||||
{'data_set_name': '可以使用:mws87_oper_sent_score_pres', 'description': '不可使用,仅供参考:The Sentiment Score of Operator in Presentation'} |
||||
{'data_set_name': '可以使用:revenue_revision_score_float', 'description': '不可使用,仅供参考:Score component based on analyst revenue revisions, as a float value.'} |
||||
{'data_set_name': '可以使用:pv87_2_bps_qf_matrix_p1_b_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Book Value Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted28d_sent_z_trend2', 'description': '不可使用,仅供参考:28-day Volume weighted average of Trend of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_revenue_consensus_median', 'description': '不可使用,仅供参考:Revenue Consensus Median'} |
||||
{'data_set_name': '可以使用:fnd90_qes_gamef_score', 'description': '不可使用,仅供参考:Score'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg60_group_css_assets', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Assets'} |
||||
{'data_set_name': '可以使用:oth455_partner_roam_w4_pca_fact1_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using the 1st eigenvalue of PCA into 20 groups.'} |
||||
{'data_set_name': '可以使用:headline_positive_sentiment_score_story', 'description': '不可使用,仅供参考:Positive sentiment score derived from the headline in the story analysis.'} |
||||
{'data_set_name': '可以使用:oth567score_company_size', 'description': '不可使用,仅供参考:Company size score'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_rsqr4qfcf3y_alt', 'description': '不可使用,仅供参考:R-Sqr of 3-yr TTM FCF Trend Line'} |
||||
{'data_set_name': '可以使用:pv87_scores_finhypepartnormscr_mean', 'description': '不可使用,仅供参考:Mean of Financial hype partial score'} |
||||
{'data_set_name': '可以使用:mdl230_us5000_cusip_irttmsalesev', 'description': "不可使用,仅供参考:It is defined as a stock's trailing 12 month sales-to-enterprise (SEV) value less the average of the SEVs of all stocks in the same industry deflated by the standard deviation of the SEVs of all stocks in the same relative universe."} |
||||
{'data_set_name': '可以使用:pv87_2_bps_af_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Book Value Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:ceo_lix_score_qa', 'description': '不可使用,仅供参考:LIX readability score for CEO in Q&A section.'} |
||||
{'data_set_name': '可以使用:pv87_cash_from_operations_consensus_high_scale', 'description': '不可使用,仅供参考:Scale of Cash From Operations Consensus High'} |
||||
{'data_set_name': '可以使用:oth179_sector_d1_ranking', 'description': '不可使用,仅供参考:Ranking given to the sectors as per the return'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p50_q200_w5_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:oth401_qes_gamef_score', 'description': '不可使用,仅供参考:Score'} |
||||
{'data_set_name': '可以使用:fnd14_hiwater_total_shares_outstanding', 'description': '不可使用,仅供参考:Highest number of total shares outstanding'} |
||||
{'data_set_name': '可以使用:time_weighted_cash_flow_to_price', 'description': '不可使用,仅供参考:Time-weighted average of cash flows per share estimates for the next two years divided by price.'} |
||||
{'data_set_name': '可以使用:anl69_sales_latest_ann_dt_qtrly', 'description': '不可使用,仅供参考:Latest Announcement Date Quarterly'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w4_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_b_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_webv2_expavg60_topic_event_sentiment_score_business', 'description': '不可使用,仅供参考:60-day Exponential average of Event Sentiment Score for topic Business'} |
||||
{'data_set_name': '可以使用:anl49_backfill_performancerank', 'description': "不可使用,仅供参考:A measure of a company's relative price performance over the next 12 months. It is a purely quantitative measure that is based on past earnings and price performance data. Companies are ranked relative to one another using a scale from 1 (Highest) to 5 (Lowest)."} |
||||
{'data_set_name': '可以使用:banking_sector_exposure_score_2', 'description': '不可使用,仅供参考:Exposure or sensitivity to the banking sector factor.'} |
||||
{'data_set_name': '可以使用:mdl354_group_pt1es_sale_fy1_r3m', 'description': '不可使用,仅供参考:FY1 revenue revision, 3M'} |
||||
{'data_set_name': '可以使用:pv87_2_netdebt_qf_matrix_p1_b_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p50_q50_w5_pca_fact3_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 20 groups.'} |
||||
{'data_set_name': '可以使用:fn_oth_comp_grants_weighted_avg_grant_date_fair_value_a', 'description': '不可使用,仅供参考:Annual Share-Based Compensation Equity Instruments Other Than Options Nonvested Weighted Average Grant Date Fair Value'} |
||||
{'data_set_name': '可以使用:oth460_share_chg_l1', 'description': '不可使用,仅供参考:The probability that the future trend of YoY change in share count" will fall"'} |
||||
{'data_set_name': '可以使用:pv87_2_ebitda_qf_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of EBITDA *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oiivcallmputs9', 'description': '不可使用,仅供参考:Weighted average Implied volatility for deep in-the-money call options and put options with the same strike prices with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_ew_sent_std_daydiff', 'description': '不可使用,仅供参考:14-day Volume weighted average of Daily difference of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:ltip_to_total_remuneration_ratio_2', 'description': '不可使用,仅供参考:Ratio of long-term incentive plan value to total remuneration for the period (alternate).'} |
||||
{'data_set_name': '可以使用:pv87_daily_matrix_nonperiodic_eps_lt_growth_consensus_mean_numup', 'description': '不可使用,仅供参考:Number of up revisions of EPS LT Growth Consensus Mean (%)'} |
||||
{'data_set_name': '可以使用:fnd65_allcap_sedol_fcfsale', 'description': '不可使用,仅供参考:It is defined as the trailing 12-month free cash flow divided by the trailing 12-month sales.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_sent_mean_trend2', 'description': '不可使用,仅供参考:7-day Volume weighted average of Trend of Sentiment Average'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_sent_trend', 'description': '不可使用,仅供参考:14-day Volume weighted average of Trend of Sentiment'} |
||||
{'data_set_name': '可以使用:mws87_actinvoratiocfopres', 'description': '不可使用,仅供参考:Number of words of CFO/number of words of executives in presentation'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg60_group_event_sentiment_score_products_services', 'description': '不可使用,仅供参考:60-day Weighted average of Event Sentiment Score for group Products Services'} |
||||
{'data_set_name': '可以使用:oth553_rec_answer_ratio', 'description': '不可使用,仅供参考:Ratio of answers in earnings call transcripts related to recommendations.'} |
||||
{'data_set_name': '可以使用:pv87_2_grossmargin_af_matrix_p1_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Gross Margin *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_net_asset_value_share_consensus_mean_numupunfiltered', 'description': '不可使用,仅供参考:Number of up revisions of Net Asset Value / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:min_basic_shares_guidance', 'description': '不可使用,仅供参考:Shares Basic - Minimum guidance value'} |
||||
{'data_set_name': '可以使用:fnd65_totalcap_cusip_saleicap', 'description': '不可使用,仅供参考:It is defined as the trailing 12-month total revenues divided by the average of the invested capital in the same period.'} |
||||
{'data_set_name': '可以使用:anl4_fcfps_flag', 'description': '不可使用,仅供参考:Free cash flow per share - forecast type (revision/new/...)'} |
||||
{'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Sales'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_mean_trend2', 'description': '不可使用,仅供参考:14-day Volume weighted average of Trend of Sentiment Average'} |
||||
{'data_set_name': '可以使用:anti_pollution_policy_industry_rank', 'description': '不可使用,仅供参考:Company’s rank within its industry peer group for anti-pollution policies.'} |
||||
{'data_set_name': '可以使用:fnd28_growthratesa_value_08635a', 'description': '不可使用,仅供参考:value of annual field: Net Sales / Revenues - 5 Yr Annual Growth'} |
||||
{'data_set_name': '可以使用:oth455_customer_roam_w4_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using K-means into 10 groups.'} |
||||
{'data_set_name': '可以使用:mdl77_historicalgrowthfactor_mpoghc', 'description': '不可使用,仅供参考:1-Year Change in Operating Profit Margin: It is defined as the most recent quarterly operating profit margin minus that of 4 quarters ago. Operating profit margin is income from operations divided by total sales.'} |
||||
{'data_set_name': '可以使用:mdl177_2_growthanalystmodel_qga_fcfroe', 'description': '不可使用,仅供参考:Free Cash Flow ROE'} |
||||
{'data_set_name': '可以使用:shareholders_net_total_dividends', 'description': '不可使用,仅供参考:Total net dividends to shareholders for the interim period.'} |
||||
{'data_set_name': '可以使用:mdl177_growthanalystmodel_qga_epstrend_alt', 'description': '不可使用,仅供参考:EPS Trend'} |
||||
{'data_set_name': '可以使用:oth460_tech_rank_class', 'description': '不可使用,仅供参考:Predicted trend of Relative Strength Ranking Value" (1: fall, 2: neutral, 3: move-up)"'} |
||||
{'data_set_name': '可以使用:exclusion_factor_score_change_1fy', 'description': '不可使用,仅供参考:Change in exclusion factor percentile score over one fiscal year.'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w2_pca_fact1_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 1st eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:oth432_saleq_profitability_profitability12', 'description': '不可使用,仅供参考:12th profitability field of Sales/Turnover (Net)'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p50_q50_w4_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 10 groups.'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p50_q200_w2_pca_fact3_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 3rd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:anl10_cpsinnovation_score_fy2', 'description': '不可使用,仅供参考:Innovation score for cash per share FY2 (innovate_increase - innovate_decrease)'} |
||||
{'data_set_name': '可以使用:sustainability_corr_weighted_sector_position', 'description': '不可使用,仅供参考:Company’s position within its sector based on sustainability score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:anl44_sales_best_cur_fiscal_year_period', 'description': '不可使用,仅供参考:sales best cur fiscal year period'} |
||||
{'data_set_name': '可以使用:rp_css_technical', 'description': '不可使用,仅供参考:Composite sentiment score based on technical analysis'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_sent_mean_tsrank', 'description': '不可使用,仅供参考:14-day Volume weighted average of End-of-day time series rank of Sentiment Average'} |
||||
{'data_set_name': '可以使用:momentum_score_long_term_float', 'description': '不可使用,仅供参考:Numeric value for the long-term momentum component based on extended return periods.'} |
||||
{'data_set_name': '可以使用:mdl230_totalcap_cusip_saleicap', 'description': '不可使用,仅供参考:It is defined as the trailing 12-month total revenues divided by the average of the invested capital in the same period.'} |
||||
{'data_set_name': '可以使用:pv87_scores_negnormscr_std', 'description': '不可使用,仅供参考:Standard deviation of negative score'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w3_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:mdl26_smartestimate_fq2_revenue', 'description': '不可使用,仅供参考:Estimate FQTR2 revenue'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oiivcallmputs7', 'description': '不可使用,仅供参考:Weighted average Implied volatility for near out-of-the-money call options and put options with the same strike prices with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:mdl354_group_pt1gr_intr_sale', 'description': '不可使用,仅供参考:Historical YoY interim revenue growth'} |
||||
{'data_set_name': '可以使用:trend_estimation_confidence_score', 'description': '不可使用,仅供参考:Confidence level for the accuracy of the estimated trend value.'} |
||||
{'data_set_name': '可以使用:retail_sentiment_score_qa', 'description': '不可使用,仅供参考:Overall sentiment score for retail investors in the Q&A section.'} |
||||
{'data_set_name': '可以使用:oth546_nlpbusnet_strength', 'description': '不可使用,仅供参考:Measures the strength of connections or relationships in the NLPBusNet module'} |
||||
{'data_set_name': '可以使用:fnd14_mail_state_country', 'description': '不可使用,仅供参考:Mail state country of registrant'} |
||||
{'data_set_name': '可以使用:pv87_psale_fy1_mean', 'description': '不可使用,仅供参考:Price-to-sales, FY1'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volthetaput7', 'description': '不可使用,仅供参考:theta volume of near out put options'} |
||||
{'data_set_name': '可以使用:mdl177_2_globaldevnorthamerica_v502_fcfsale', 'description': '不可使用,仅供参考:TTM Free Cash Flow-to-TTM Sales : It is defined as the trailing 12-month free cash flow divided by the trailing 12-month sales.'} |
||||
{'data_set_name': '可以使用:mdl77_historicalgrowthfactor_chg3yepsp', 'description': '不可使用,仅供参考:The difference between the trailing 12-month earnings per share and that of 12-quarters ago for a stock divided by its month-end trading price.'} |
||||
{'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_cvopinc', 'description': '不可使用,仅供参考:CV of Oper Income per Share in Last 12 QTRs: It is defined as the standard deviation of the trailing 12-month operating income per share (OPINC) in the prior 12 quarters divided by the mean of the OPINCs in the same period.'} |
||||
{'data_set_name': '可以使用:mdl177_2_managementqualityfactor_cfita', 'description': '不可使用,仅供参考:TTM Cash Flow from Investment to Total Assets : It is defined as the trailing 12-month cash flow from the investing portion of the cash flow statement divided by the last 4 quarters average total assets'} |
||||
{'data_set_name': '可以使用:pv87_2_fcfps_af_matrix_p1_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Financing Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:mdl354_group_pt1gr_fy1_sale', 'description': '不可使用,仅供参考:FY1 Revenue growth'} |
||||
{'data_set_name': '可以使用:fnd65_totalcap_cusip_salesaccel4q', 'description': '不可使用,仅供参考:It is defined as the slope of the regression line between year over year sales growth and time.'} |
||||
{'data_set_name': '可以使用:fnd2_a_ltrmdmrepoplinythree', 'description': '不可使用,仅供参考:Amount of long-term debt payable, sinking fund requirements, and other securities issued that are redeemable by holder at fixed or determinable prices and dates maturing in the 3rd fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple7d_ew_sent_tsrank', 'description': '不可使用,仅供参考:tsrank of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_ew_sent_mean', 'description': '不可使用,仅供参考:14-day Volume weighted average of Average of Sentiment'} |
||||
{'data_set_name': '可以使用:mdl262_saleq_profitability_profitability11', 'description': '不可使用,仅供参考:11th profitability field of Sales/Turnover (Net)'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_event_sentiment_score_acquisitions_mergers', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Acquisitions Mergers'} |
||||
{'data_set_name': '可以使用:anl10_roepast_det_estflag', 'description': '不可使用,仅供参考:Estimate flag for return on equity'} |
||||
{'data_set_name': '可以使用:mdl109_es_sale_fy1_r1m', 'description': '不可使用,仅供参考:FY1 (Future Year) Revenue Revision'} |
||||
{'data_set_name': '可以使用:social_corr_weighted_sector_percentile', 'description': '不可使用,仅供参考:Company’s percentile within its sector based on social score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:mdl31_pricesales_current', 'description': '不可使用,仅供参考:Current price to sales ratio'} |
||||
{'data_set_name': '可以使用:mdl230_us5000_cusip_apsales', 'description': '不可使用,仅供参考:It is defined as the annual aggregate sales for Asia-Pacific as reported by the company divided by total annual sales.'} |
||||
========================= 数据字段结束 ======================================= |
||||
|
||||
以上数据字段和操作符, 按照Description说明组合, 但是每一个 alpha 组合的使用的数据字段和操作符不要过于集中, 在符合语法的情况下, 多尝试不同的组合 |
||||
|
||||
你再检查一下, 如果你使用了 |
||||
Operator abs does not support event inputs |
||||
Operator ts_mean does not support event inputs |
||||
Operator ts_scale does not support event inputs |
||||
Operator add does not support event inputs |
||||
Operator sign does not support event inputs |
||||
Operator greater does not support event inputs |
||||
Operator ts_av_diff does not support event inputs |
||||
Operator ts_quantile does not support event inputs |
||||
Operator ts_arg_min does not support event inputs |
||||
Operator divide does not support event inputs |
||||
Operator ts_corr does not support event inputs |
||||
Operator ts_decay_linear does not support event inputs |
||||
Operator ts_sum does not support event inputs |
||||
Operator ts_delay does not support event inputs |
||||
Operator ts_arg_max does not support event inputs |
||||
Operator ts_std_dev does not support event inputs |
||||
Operator ts_regression does not support event inputs |
||||
Operator ts_backfill does not support event inputs |
||||
Operator signed_power does not support event inputs |
||||
Operator ts_product does not support event inputs |
||||
Operator ts_zscore does not support event inputs |
||||
Operator group_rank does not support event inputs |
||||
Operator subtract does not support event inputs |
||||
Operator ts_delta does not support event inputs |
||||
Operator ts_rank does not support event inputs |
||||
Operator ts_count_nans does not support event inputs |
||||
Operator ts_covariance does not support event inputs |
||||
Operator multiply does not support event inputs |
||||
Operator if_else does not support event inputs |
||||
Operator group_neutralize does not support event inputs |
||||
Operator group_zscore does not support event inputs |
||||
Operator winsorize does not support event inputs |
||||
注意, 以上操作符不能使用事件类型的数据集, 以上操作符禁止使用事件类型的数据集!! |
||||
@ -0,0 +1,617 @@ |
||||
跨境技术溢出效应 |
||||
假设 |
||||
在全球化产业链中，若一家公司的海外主要客户或供应商拥有强大的技术创新能力（如高研发投入、高专利质量），则该公司可能通过业务关联，获得隐性的知识外溢与技术扩散益处。这种“技术溢出”能提升该公司的运营效率、产品竞争力或降低其研发风险，从而可能在未来转化为超预期的盈利增长与估值提升。市场对这类隐含的、非线性的增长期权可能存在定价不足。 |
||||
实施方案 |
||||
构建“技术关联强度”因子。识别公司年报或供应链数据中披露的前五大海外客户/供应商，并获取这些关联实体的公开技术创新指标（如人均专利引用量、研发费用增速）。使用加权平均算子，依据交易金额占比为权重，计算公司所关联的海外实体的整体技术强度。使用时序滞后算子，将技术强度数据滞后6-12个月以匹配技术吸收与转化周期，再通过横截面排名评估公司在全市场中的相对技术关联优势。 |
||||
阿尔法因子优化建议 |
||||
技术溢出的效果受公司自身“吸收能力”调节。建议引入公司自身的研发团队质量（如技术人员占比）、内部研发投入强度作为调节变量，通过交互项算子或条件分层处理（例如，仅在自身研发投入超过行业平均的公司样本中，技术关联强度因子才被启用），以更精准地捕捉那些既拥有外部技术源头、又有能力内部化的优质标的。 |
||||
Cross-Border Technology Spillover Effect |
||||
Hypothesis |
||||
In the global industrial chain, if a company's key overseas customers or suppliers possess strong technological innovation capabilities (e.g., high R&D investment, high patent quality), the company may benefit from implicit knowledge spillover and technology diffusion through these business linkages. This "technology spillover" can enhance the company's operational efficiency, product competitiveness, or reduce its R&D risks, potentially translating into unexpected profit growth and valuation appreciation in the future. The market may underprice this implicit, non-linear growth option. |
||||
Implementation Plan |
||||
Construct a "Technology Linkage Intensity" factor. Identify the top five overseas customers/suppliers disclosed in the company's annual reports or supply chain data, and obtain public technological innovation metrics for these linked entities (e.g., patent citations per capita, R&D expense growth rate). Use a weighted average operator, with transaction amount proportion as weights, to calculate the aggregated technological strength of the overseas entities linked to the company. Apply a time-series lag operator to lag the technology strength data by 6-12 months to account for technology absorption and conversion cycles, then assess the company's relative technological linkage advantage across the market via cross-sectional ranking. |
||||
Alpha Factor Optimization Suggestion |
||||
The effect of technology spillover is moderated by the company's own "absorptive capacity." It is suggested to introduce the quality of the company's own R&D team (e.g., proportion of technical staff) and internal R&D intensity as moderating variables. Through interaction term operators or conditional stratification (e.g., enabling the Technology Linkage Intensity factor only within the subsample of companies whose own R&D investment exceeds the industry average), the factor can more precisely identify high-quality targets that possess both external technology sources and the internal capability to assimilate them. |
||||
*=========================================================================================* |
||||
输出格式： |
||||
输出必须是且仅是纯文本。 |
||||
每一行是一个完整、独立、语法正确的WebSim表达式。 |
||||
严禁任何形式的解释、编号、标点包裹（如引号）、Markdown格式或额外文本。 |
||||
===================== !!! 重点(输出方式) !!! ===================== |
||||
现在，请严格遵守以上所有规则，开始生成可立即在WebSim中运行的复合因子表达式。 |
||||
不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 |
||||
**输出格式**(一行一个表达式, 每个表达式中间需要添加一个空行, 只要表达式本身, 不需要赋值, 不要解释, 不需要序号, 也不要输出多余的东西)： |
||||
表达式 |
||||
表达式 |
||||
表达式 |
||||
... |
||||
表达式 |
||||
================================================================= |
||||
重申：请确保所有表达式都使用WorldQuant WebSim平台函数，不要使用pandas、numpy或其他Python库函数。输出必须是一行有效的WQ表达式。 |
||||
以下是我的账号有权限使用的操作符, 请严格按照操作符, 以及我提供的数据集, 进行生成,组合 100 个 alpha： |
||||
不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 |
||||
================================================================= |
||||
ts_product ts_zscore ts_mean ts_scale add sign subtract ts_delta ts_rank greater ts_av_diff ts_quantile ts_count_nans ts_covariance |
||||
ts_arg_min divide ts_corr multiply if_else ts_sum ts_delay group_zscore ts_arg_max ts_std_de ts_backfill |
||||
以上这些操作符不能传入事件类型的数据集, 只能传入时间序列数据集, 不能传入事件数据,不能传入事件数据,不能传入事件数据 |
||||
|
||||
以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子 |
||||
|
||||
========================= 操作符开始 ======================================= |
||||
注意: Operator: 后面的是操作符(是可以使用的), |
||||
Description: 此字段后面的是操作符对应的描述或使用说明(禁止使用, 仅供参考), Description字段后面的内容是使用说明, 不是操作符 |
||||
特别注意!!!! 必须按照操作符字段Operator的使用说明生成 alphaOperator: abs(x) |
||||
Description: Absolute value of x |
||||
Operator: add(x, y, filter = false) |
||||
Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding |
||||
Operator: densify(x) |
||||
Description: Converts a grouping field of many buckets into lesser number of only available buckets so as to make working with grouping fields computationally efficient |
||||
Operator: divide(x, y) |
||||
Description: x / y |
||||
Operator: inverse(x) |
||||
Description: 1 / x |
||||
Operator: log(x) |
||||
Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights. |
||||
Operator: max(x, y, ..) |
||||
Description: Maximum value of all inputs. At least 2 inputs are required |
||||
Operator: min(x, y ..) |
||||
Description: Minimum value of all inputs. At least 2 inputs are required |
||||
Operator: multiply(x ,y, ... , filter=false) |
||||
Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1 |
||||
Operator: power(x, y) |
||||
Description: x ^ y |
||||
Operator: reverse(x) |
||||
Description: - x |
||||
Operator: sign(x) |
||||
Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN; |
||||
Operator: signed_power(x, y) |
||||
Description: x raised to the power of y such that final result preserves sign of x |
||||
Operator: sqrt(x) |
||||
Description: Square root of x |
||||
Operator: subtract(x, y, filter=false) |
||||
Description: x-y. If filter = true, filter all input NaN to 0 before subtracting |
||||
Operator: and(input1, input2) |
||||
Description: Logical AND operator, returns true if both operands are true and returns false otherwise |
||||
Operator: if_else(input1, input2, input 3) |
||||
Description: If input1 is true then return input2 else return input3. |
||||
Operator: input1 < input2 |
||||
Description: If input1 < input2 return true, else return false |
||||
Operator: input1 <= input2 |
||||
Description: Returns true if input1 <= input2, return false otherwise |
||||
Operator: input1 == input2 |
||||
Description: Returns true if both inputs are same and returns false otherwise |
||||
Operator: input1 > input2 |
||||
Description: Logic comparison operators to compares two inputs |
||||
Operator: input1 >= input2 |
||||
Description: Returns true if input1 >= input2, return false otherwise |
||||
Operator: input1!= input2 |
||||
Description: Returns true if both inputs are NOT the same and returns false otherwise |
||||
Operator: is_nan(input) |
||||
Description: If (input == NaN) return 1 else return 0 |
||||
Operator: not(x) |
||||
Description: Returns the logical negation of x. If x is true (1), it returns false (0), and if input is false (0), it returns true (1). |
||||
Operator: or(input1, input2) |
||||
Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise |
||||
Operator: days_from_last_change(x) |
||||
Description: Amount of days since last change of x |
||||
Operator: hump(x, hump = 0.01) |
||||
Description: Limits amount and magnitude of changes in input (thus reducing turnover) |
||||
Operator: kth_element(x, d, k) |
||||
Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1 |
||||
Operator: last_diff_value(x, d) |
||||
Description: Returns last x value not equal to current x value from last d days |
||||
Operator: ts_arg_max(x, d) |
||||
Description: Returns the relative index of the max value in the time series for the past d days. If the current day has the max value for the past d days, it returns 0. If previous day has the max value for the past d days, it returns 1 |
||||
Operator: ts_arg_min(x, d) |
||||
Description: Returns the relative index of the min value in the time series for the past d days; If the current day has the min value for the past d days, it returns 0; If previous day has the min value for the past d days, it returns 1. |
||||
Operator: ts_av_diff(x, d) |
||||
Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation |
||||
Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN") |
||||
Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value) |
||||
Operator: ts_corr(x, y, d) |
||||
Description: Returns correlation of x and y for the past d days |
||||
Operator: ts_count_nans(x ,d) |
||||
Description: Returns the number of NaN values in x for the past d days |
||||
Operator: ts_covariance(y, x, d) |
||||
Description: Returns covariance of y and x for the past d days |
||||
Operator: ts_decay_linear(x, d, dense = false) |
||||
Description: Returns the linear decay on x for the past d days. Dense parameter=false means operator works in sparse mode and we treat NaN as 0. In dense mode we do not. |
||||
Operator: ts_delay(x, d) |
||||
Description: Returns x value d days ago |
||||
Operator: ts_delta(x, d) |
||||
Description: Returns x - ts_delay(x, d) |
||||
Operator: ts_mean(x, d) |
||||
Description: Returns average value of x for the past d days. |
||||
Operator: ts_product(x, d) |
||||
Description: Returns product of x for the past d days |
||||
Operator: ts_quantile(x,d, driver="gaussian" ) |
||||
Description: It calculates ts_rank and apply to its value an inverse cumulative density function from driver distribution. Possible values of driver (optional ) are "gaussian", "uniform", "cauchy" distribution where "gaussian" is the default. |
||||
Operator: ts_rank(x, d, constant = 0) |
||||
Description: Rank the values of x for each instrument over the past d days, then return the rank of the current value + constant. If not specified, by default, constant = 0. |
||||
Operator: ts_regression(y, x, d, lag = 0, rettype = 0) |
||||
Description: Returns various parameters related to regression function |
||||
Operator: ts_scale(x, d, constant = 0) |
||||
Description: Returns (x - ts_min(x, d)) / (ts_max(x, d) - ts_min(x, d)) + constant. This operator is similar to scale down operator but acts in time series space |
||||
Operator: ts_std_dev(x, d) |
||||
Description: Returns standard deviation of x for the past d days |
||||
Operator: ts_step(1) |
||||
Description: Returns days' counter |
||||
Operator: ts_sum(x, d) |
||||
Description: Sum values of x for the past d days. |
||||
Operator: ts_zscore(x, d) |
||||
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean: (x - tsmean(x,d)) / tsstddev(x,d). This operator may help reduce outliers and drawdown. |
||||
Operator: normalize(x, useStd = false, limit = 0.0) |
||||
Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element |
||||
Operator: quantile(x, driver = gaussian, sigma = 1.0) |
||||
Description: Rank the raw vector, shift the ranked Alpha vector, apply distribution (gaussian, cauchy, uniform). If driver is uniform, it simply subtract each Alpha value with the mean of all Alpha values in the Alpha vector |
||||
Operator: rank(x, rate=2) |
||||
Description: Ranks the input among all the instruments and returns an equally distributed number between 0.0 and 1.0. For precise sort, use the rate as 0 |
||||
Operator: scale(x, scale=1, longscale=1, shortscale=1) |
||||
Description: Scales input to booksize. We can also scale the long positions and short positions to separate scales by mentioning additional parameters to the operator |
||||
Operator: winsorize(x, std=4) |
||||
Description: Winsorizes x to make sure that all values in x are between the lower and upper limits, which are specified as multiple of std. |
||||
Operator: zscore(x) |
||||
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean |
||||
Operator: vec_avg(x) |
||||
Description: Taking mean of the vector field x |
||||
Operator: vec_sum(x) |
||||
Description: Sum of vector field x |
||||
Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10") |
||||
Description: Convert float values into indexes for user-specified buckets. Bucket is useful for creating group values, which can be passed to GROUP as input |
||||
Operator: trade_when(x, y, z) |
||||
Description: Used in order to change Alpha values only under a specified condition and to hold Alpha values in other cases. It also allows to close Alpha positions (assign NaN values) under a specified condition |
||||
Operator: group_backfill(x, group, d, std = 4.0) |
||||
Description: If a certain value for a certain date and instrument is NaN, from the set of same group instruments, calculate winsorized mean of all non-NaN values over last d days |
||||
Operator: group_mean(x, weight, group) |
||||
Description: All elements in group equals to the mean |
||||
Operator: group_neutralize(x, group) |
||||
Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant |
||||
Operator: group_rank(x, group) |
||||
Description: Each elements in a group is assigned the corresponding rank in this group |
||||
Operator: group_scale(x, group) |
||||
Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin) |
||||
Operator: group_zscore(x, group) |
||||
Description: Calculates group Z-score - numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. zscore = (data - mean) / stddev of x for each instrument within its group. |
||||
========================= 操作符结束 ======================================= |
||||
|
||||
========================= 数据字段开始 ======================================= |
||||
注意: data_set_name: 后面的是数据字段(可以使用), description: 此字段后面的是数据字段对应的描述或使用说明(不能使用) |
||||
|
||||
{'data_set_name': '可以使用:info1d0_negative_sentiment_score', 'description': '不可使用,仅供参考:Score representing the degree of negative sentiment in the event transcript or story (info_1_D0 module).'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q50_w1_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:fnd3_aacctadj_capitalassetsales_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Proceeds from Sale of Productive Assets'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volvegacall1', 'description': '不可使用,仅供参考:Weighted average Vega for near in-the-money and out-of-the-money call options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:oth460_call_put_ratio_10_day_l1', 'description': '不可使用,仅供参考:The probability that the future trend of 10-Day Median of Call Volume to Put Volume" will be fall"'} |
||||
{'data_set_name': '可以使用:environmental_corr_weighted_score', 'description': '不可使用,仅供参考:Environmental score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:workforce_corr_weighted_industry_position', 'description': '不可使用,仅供参考:Company’s position within its industry based on employee-related score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:pv87_prv2_expavg20_group_event_sentiment_score_labor_issues', 'description': '不可使用,仅供参考:20-day Exponential average of Event Sentiment Score for group Labor Issues'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oithetacallmputs6', 'description': '不可使用,仅供参考:Weighted average Theta for far out-of-the-money call options and put options with the same strike prices with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_matrix_sent_ew_sent_tsrank', 'description': '不可使用,仅供参考:tsrank of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted28d_ew_sent_z_trend2', 'description': '不可使用,仅供参考:28-day Volume weighted average of Trend of Sentiment'} |
||||
{'data_set_name': '可以使用:mdl77_400_visiratio', 'description': "不可使用,仅供参考:The Visibility Ratio: It equals a stock's most recent daily trading volume divided by the average daily trading volume in the previous 50 trading days."} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_r6_revenue_consensus_mean_numnochangeunfiltered', 'description': '不可使用,仅供参考:Number of no change revisions (unfiltered) of Revenue Consensus Mean'} |
||||
{'data_set_name': '可以使用:anl10_cpspast_det_excflag_2191', 'description': '不可使用,仅供参考:Exclusion flag for cash per share estimates'} |
||||
{'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_fcfequity', 'description': '不可使用,仅供参考:TTM Free Cash Flow to Equity: It is defined as the trailing 12-month free cash flow divided by the average book equity value in the same period.'} |
||||
{'data_set_name': '可以使用:fnd65_us5000_cusip_saleeps', 'description': '不可使用,仅供参考:It is defined as the absolute value of the difference between the yearly percent change in trailing 12-month sales per share and the yearly percent change in trailing 12-month diluted earnings per share before extraordinary items.'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg20_group_event_sentiment_score_stock_prices', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Stock Prices'} |
||||
{'data_set_name': '可以使用:pv87_v2_simpleavg20_group_event_sentiment_score_assets', 'description': '不可使用,仅供参考:20-day Simple average of Event Sentiment Score for group Assets'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p50_q200_w2_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 10 groups.'} |
||||
{'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_ew_sent_z_tsrank', 'description': '不可使用,仅供参考:14-day Volume weighted average of End-of-day time series rank of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_book_value_share_consensus_mean_numanalystsunfiltered', 'description': '不可使用,仅供参考:Number of analysts (unfiltered) of Book Value / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_css_analyst_ratings', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Analyst Ratings'} |
||||
{'data_set_name': '可以使用:mdl264_group_rank_l2', 'description': '不可使用,仅供参考:The probability that the future trend of "Industry Ranking" will be neutral'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w5_pca_fact3_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_matrix_vol_vol_mean_tsrank', 'description': '不可使用,仅供参考:End-of-day time series rank of Volume Average'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg60_group_css_labor_issues', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Labor Issues'} |
||||
{'data_set_name': '可以使用:pv48_constituent_v1_2_0_valueshares', 'description': '不可使用,仅供参考:No field description'} |
||||
{'data_set_name': '可以使用:technology_pca_factor1_grouping5', 'description': '不可使用,仅供参考:First principal component grouping for technology sector with 5 clusters.'} |
||||
{'data_set_name': '可以使用:anl10_cpsinnovation_score_fq1', 'description': '不可使用,仅供参考:Innovation score for cash per share Q1 (innovate_increase - innovate_decrease)'} |
||||
{'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_chg3yepsast', 'description': '不可使用,仅供参考:3-yr Change in Assets-adj TTM EPS: It is defined as the trailing 12-month earnings per share before extra items (EPS) minus the EPS 12-quarters ago, deflated by the average total assets per share.'} |
||||
{'data_set_name': '可以使用:fnd3_q_capitalassetsales', 'description': '不可使用,仅供参考:Quarterly Proceeds from Sale of Productive Assets'} |
||||
{'data_set_name': '可以使用:board_independence_sector_rank', 'description': '不可使用,仅供参考:Company’s rank within its sector peer group for board independence and diversity.'} |
||||
{'data_set_name': '可以使用:insd3_10q_info_positive_score', 'description': '不可使用,仅供参考:10-Q Info Positive Score'} |
||||
{'data_set_name': '可以使用:software_services_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the software and services sector factor.'} |
||||
{'data_set_name': '可以使用:mdl77_omomemtumanalystmodel_qma_eplinkage', 'description': '不可使用,仅供参考:The equal-weighted average of the Change in Free Cash Flow Rank, the Industry Relative 3-Month Return Rank, the Market Earnings Response Rank, and the Change in Net Working Capital Rank.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_sent_trend', 'description': '不可使用,仅供参考:14-day Volume weighted average of Trend of Sentiment'} |
||||
{'data_set_name': '可以使用:fnd3_qacctadj_sharesauthorized', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Shares Authorized'} |
||||
{'data_set_name': '可以使用:oth455_customer_roam_w1_pca_fact3_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using the 3rd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:fnd6_eventv110_pncidq', 'description': '不可使用,仅供参考:Core Pension Interest Adjustment Diluted EPS Effect'} |
||||
{'data_set_name': '可以使用:pv20_score', 'description': '不可使用,仅供参考:Score for the dataset'} |
||||
{'data_set_name': '可以使用:precious_metals_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the precious metals industry factor.'} |
||||
{'data_set_name': '可以使用:other_participant_fkgl_score_qa', 'description': '不可使用,仅供参考:Flesch-Kincaid Grade Level (FKGL) for other participants in Q&A section.'} |
||||
{'data_set_name': '可以使用:fnd31_devnorthamericaadditionalfactor4_fqsurstd60dlag', 'description': '不可使用,仅供参考:60-Day Lagged Quarterly Earnings Surprise. It is defined as the most recent actual fiscal quarter EPS less the consensus earnings estimate 60 days ago, adjusted by the standard deviation of analyst forecasts 60 days ago.'} |
||||
{'data_set_name': '可以使用:pv87_v2item_indrank_item_6080_271', 'description': '不可使用,仅供参考:Industry ranked item score for item 271 in topic Transparency'} |
||||
{'data_set_name': '可以使用:anl44_eps_ratio_best_cur_fiscal_semi_year_period', 'description': '不可使用,仅供参考:eps ratio best cur fiscal semi year period'} |
||||
{'data_set_name': '可以使用:mdl39_1_val_mo_sector_rank', 'description': '不可使用,仅供参考:Sector-relative 1-100 ranking of the Val-Mo model'} |
||||
{'data_set_name': '可以使用:pv87_2_tbvps_af_matrix_p1_b_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Tangible Book Value Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:insd3_edgar_insider_shares', 'description': '不可使用,仅供参考:Insider Shares'} |
||||
{'data_set_name': '可以使用:technology_pca_factor3_grouping5', 'description': '不可使用,仅供参考:Third principal component grouping for technology sector with 5 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_2_roa_af_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Return On Assets *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg20_group_event_sentiment_score_products_services', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Products Services'} |
||||
{'data_set_name': '可以使用:pv87_2_nav_af_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p50_q50_w4_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 5 groups.'} |
||||
{'data_set_name': '可以使用:chunk_relevance_z1_flag_fast_d1', 'description': "不可使用,仅供参考:Indicator if the chunk's relevance z-score exceeds 1."} |
||||
{'data_set_name': '可以使用:capital_expenditure_amount', 'description': '不可使用,仅供参考:Capital Expenditures - Total value'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetaput9', 'description': '不可使用,仅供参考:theta of deep in put options'} |
||||
{'data_set_name': '可以使用:employee_training_sector_rank', 'description': '不可使用,仅供参考:Company’s rank within its sector peer group for employee training, safety, and well-being.'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_reinrate', 'description': '不可使用,仅供参考:Reinvestment Rate : It is defined as the trailing 12-month earnings per share before extra items less the trailing 12-month dividends per share by ex-date divided by the average book equity per share in the same period.'} |
||||
{'data_set_name': '可以使用:nws73_globalsent_certaintyscore', 'description': '不可使用,仅供参考:Global Certainty'} |
||||
{'data_set_name': '可以使用:pv87_2_ebitda_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of EBITDA *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volgammacall5', 'description': '不可使用,仅供参考:Weighted average Gamma for in-the-money call options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_prv2_simpleavg1_group_event_sentiment_score_marketing', 'description': '不可使用,仅供参考:1-day Simple average of Event Sentiment Score for group Marketing'} |
||||
{'data_set_name': '可以使用:mdl233_companies_d1_ranking', 'description': '不可使用,仅供参考:Ranking given to the companies as per the return'} |
||||
{'data_set_name': '可以使用:workforce_positive_corr_score', 'description': '不可使用,仅供参考:Employee-related score weighted by KPIs most positively correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:pv87_daily_ann_matrix_r1_net_asset_value_share_consensus_mean_numup', 'description': '不可使用,仅供参考:Number of up revisions of Net Asset Value / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:fnd3_qacctadj_sharesissued', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Number of Shares Issued'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg20_topic_css_business', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for topic Business'} |
||||
{'data_set_name': '可以使用:insd3_10q_positive_score', 'description': '不可使用,仅供参考:10-Q Positive Score'} |
||||
{'data_set_name': '可以使用:mdl264_group_rank_class', 'description': "不可使用,仅供参考:Predicted trend of 'Industry ranking' (1: fall, 2: neutral, 3: move up)"} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg60_group_css_partnerships', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Partnerships'} |
||||
{'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_susgrowth', 'description': '不可使用,仅供参考:The maximum growth rate a firm can sustain without having to increase financial leverage.'} |
||||
{'data_set_name': '可以使用:pv20_q_1_ard_treasury_shares_num', 'description': '不可使用,仅供参考:ARD Treasury Shares (Number)'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple14d_sent_z_tsrank', 'description': '不可使用,仅供参考:14-day Simple average of End-of-day time series rank of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_2_netdebt_qf_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w2_pca_fact2_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 2nd eigenvalue of PCA into 20 groups.'} |
||||
{'data_set_name': '可以使用:mdl77_oearningsqualityfactor_rau', 'description': "不可使用,仅供参考:Unexpected Change in Accounts Receivable: It is defined as the difference between current accounts receivable and the expected level of accounts receivable (multiplying the prior year's closing account balance by the growth in sales in the trailing 12 months) scaled by the total assets."} |
||||
{'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_pfcfghc', 'description': '不可使用,仅供参考:The difference between the trailing 12-month free cash flow per share and that of 4 quarters ago for a stock divided by its trading price.'} |
||||
{'data_set_name': '可以使用:credit_risk_growth_score', 'description': '不可使用,仅供参考:Percentile score reflecting growth and stability factors in credit risk.'} |
||||
{'data_set_name': '可以使用:fnd65_us5000_cusip_slope4qsales3y', 'description': '不可使用,仅供参考:It is defined as the slope coefficient between monthly dates and the corresponding trailing 12-month sales per share in the prior 12 quarters.'} |
||||
{'data_set_name': '可以使用:cons_cyclical_method1_group10_score', 'description': '不可使用,仅供参考:Score from the first method for consumer cyclical sector, grouped into 10 clusters.'} |
||||
{'data_set_name': '可以使用:social_corr_weighted_subsector_percentile', 'description': '不可使用,仅供参考:Company’s percentile within its subsector based on social score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_cv4qcf3y_alt', 'description': '不可使用,仅供参考:Stability of 3-yr TTM Cash Flow'} |
||||
{'data_set_name': '可以使用:mdl177_liquidityriskfactor_cashratio_alt', 'description': '不可使用,仅供参考:Cash & Equivalents-to-Current Liabilities : It is defined as the most recently reported quarterly cash & equivalents divided by current liabilities.'} |
||||
{'data_set_name': '可以使用:mdl138_qpdi5_sale_empl', 'description': '不可使用,仅供参考:QPDI-5 Factor based on Revenue per Employee'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_cash_flow_share_consensus_mean_numanalysts', 'description': '不可使用,仅供参考:Number of analysts of Cash Flow / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:workplace_diversity_labor_rights_score', 'description': '不可使用,仅供参考:Score measuring workplace diversity, labor relations, and employee rights.'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_css_price_targets', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Price Targets'} |
||||
{'data_set_name': '可以使用:top200_method1_group10_score', 'description': '不可使用,仅供参考:Score from the first method for top 200 securities, grouped into 10 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_v2_expavg60_topic_event_sentiment_score_all', 'description': '不可使用,仅供参考:60-day Exponential average of Event Sentiment Score for topic All'} |
||||
{'data_set_name': '可以使用:fnd72_a1_geo_grow_cur_ratio', 'description': '不可使用,仅供参考:Compound 5-year growth rate in current ratio'} |
||||
{'data_set_name': '可以使用:pv87_2_eps_af_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Earnings Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:mdl77_pricemomemtummodel_rationalalpha', 'description': '不可使用,仅供参考:Rational Decay Alpha: It evaluates stocks based on their historical 12-month market (S&P 500) adjusted excess return (the Y intercept from an OLS regression equation) using a proprietary rational decay function'} |
||||
{'data_set_name': '可以使用:mdl26_v14_actual_last_y_revenue', 'description': '不可使用,仅供参考:actual last YEAR revenue'} |
||||
{'data_set_name': '可以使用:fn_repurchased_shares_value_a', 'description': '不可使用,仅供参考:Shares repurchased and either retired or put into treasury stock, likely as part of a share buyback plan.'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_css_marketing', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Marketing'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg20_topic_event_sentiment_score_business', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for topic Business'} |
||||
{'data_set_name': '可以使用:mdl264_group_rank_l3', 'description': '不可使用,仅供参考:The probability that the future trend of "Industry Ranking" will be move-up'} |
||||
{'data_set_name': '可以使用:pv87_2_epsr_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Earnings Per Share - As Reported *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_sent_mean_tsrank', 'description': '不可使用,仅供参考:14-day Volume weighted average of End-of-day time series rank of Sentiment Average'} |
||||
{'data_set_name': '可以使用:fnd65_us5000_cusip_cashsale', 'description': '不可使用,仅供参考:It is defined as the average cash and equivalents in the trailing 12 months divided by the trailing 12-month sales.'} |
||||
{'data_set_name': '可以使用:pv87_2_nav_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:oth460_sector_rank_l1', 'description': "不可使用,仅供参考:The probability that the future trend of 'Sector Ranking' will fall"} |
||||
{'data_set_name': '可以使用:pv87_2_sales_af_matrix_all_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:mdl230_us5000_cusip_ocfratio', 'description': "不可使用,仅供参考:It is defined as a stock's most recently reported quarterly cash flow from operations divided by its current liabilities."} |
||||
{'data_set_name': '可以使用:mdl77_ohistoricalgrowthfactor_pfcoy3ghc', 'description': '不可使用,仅供参考:The difference between the trailing 12-month operating cash flow per share and that of 12 quarters ago for a stock divided by its trading price.'} |
||||
{'data_set_name': '可以使用:sales_estimate_minimum', 'description': '不可使用,仅供参考:Sales - The lowest estimation'} |
||||
{'data_set_name': '可以使用:earnings_per_share_guidance_value', 'description': '不可使用,仅供参考:Earnings Per Share - guidance value for annual frequency'} |
||||
{'data_set_name': '可以使用:credit_risk_leverage_score', 'description': '不可使用,仅供参考:Percentile score reflecting leverage factors in credit risk assessment.'} |
||||
{'data_set_name': '可以使用:nws73_globalsent_fearscore', 'description': '不可使用,仅供参考:Global Fear'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volgammacallmputs2', 'description': '不可使用,仅供参考:Weighted average Gamma for near out-of-the-money and in-the-money call options and put options with the same strike prices with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:mdl307_sales_pct_unclassified', 'description': '不可使用,仅供参考:Fraction of Sale Unclassified'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volthetacallmput9', 'description': '不可使用,仅供参考:theta volume of deep in call minus put options'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg20_group_nip_technical_analysis', 'description': '不可使用,仅供参考:20-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Technical Analysis'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_revenue_consensus_mean_numupunfiltered', 'description': '不可使用,仅供参考:Number of up revisions of Revenue Consensus Mean'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_pctchgastto', 'description': '不可使用,仅供参考:1-yr Change in Asset Turnover Ratio : It is defined as the percent change in the most recent asset turnover ratio as compared to that of 4 quarters agoAsset turnover ratio is the trailing 12-month sales divided by the average total assets in the same period.'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p50_q50_w3_kmeans_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 20 groups.'} |
||||
{'data_set_name': '可以使用:pv87_eps_lt_growth_consensus_low', 'description': '不可使用,仅供参考:EPS LT Growth Consensus Low (%)'} |
||||
{'data_set_name': '可以使用:oth432_saleq_profitability_profitability12', 'description': '不可使用,仅供参考:12th profitability field of Sales/Turnover (Net)'} |
||||
{'data_set_name': '可以使用:pv87_prv2_simpleavg1_group_event_sentiment_score_acquisitions_mergers', 'description': '不可使用,仅供参考:1-day Simple average of Event Sentiment Score for group Acquisitions Mergers'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volthetacall8', 'description': '不可使用,仅供参考:theta volume of near in call options'} |
||||
{'data_set_name': '可以使用:oth455_partner_roam_w5_pca_fact3_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using the 3rd eigenvalue of PCA into 20 groups.'} |
||||
{'data_set_name': '可以使用:pv87_2_netdebt_af_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv48_dynamic_shares_cur', 'description': '不可使用,仅供参考:Current shares for dynamic index.'} |
||||
{'data_set_name': '可以使用:mdl77_oearningsqualityfactor_ccacw', 'description': '不可使用,仅供参考:Working Capital Accruals: It equals to: Increase in Accounts Receivables + Increase in Inventory + Decrease in Accounts Payable and Accrued Liabilities + Decrease in Accrued Income Taxes + Increase (Decrease) in Assets (Liabilities).'} |
||||
{'data_set_name': '可以使用:mdl77_historicalgrowthfactor_pctchg3ycf', 'description': "不可使用,仅供参考:The percent change in a stock's most recent trailing 12-month cash flow per share as compared to itself 12 quarters ago."} |
||||
{'data_set_name': '可以使用:mdl177_2_globaldevnorthamerica_v502_nlsales', 'description': "不可使用,仅供参考:Natural Logarithm of TTM Sales : It is defined as the natural logarithm of the cubic of a company's trailing 12-month sales."} |
||||
{'data_set_name': '可以使用:anl44_best_sales_median', 'description': '不可使用,仅供参考:best sales median'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volvegacall6', 'description': '不可使用,仅供参考:vega volume of far out call options'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oivegaput0', 'description': '不可使用,仅供参考:vega of all put options'} |
||||
{'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_b_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:fnd65_allcap_sedol_ttmsaleev', 'description': '不可使用,仅供参考:It is defined as the trailing 12-month sales for a stock divided by the most recent enterprise value (EV). EV = Equity Market Value + Long-term Debt + Short-term Debt + Preferred Stock + Minority Interest - Cash & Cash Equivalents.'} |
||||
{'data_set_name': '可以使用:pv87_2_ebitdaps_qf_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of EBITDA per share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:oth455_customer_roam_w4_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using K-means into 10 groups.'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_cash_flow_share_consensus_mean_numnochange', 'description': '不可使用,仅供参考:Number of no change revisions of Cash Flow / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:fnd28_growthratesa_value_08601a', 'description': '不可使用,仅供参考:value of annual field: Earnings per Share Growth'} |
||||
{'data_set_name': '可以使用:pv87_webv2_simpleavg20_topic_event_sentiment_score_all', 'description': '不可使用,仅供参考:20-day Simple average of Event Sentiment Score for topic All'} |
||||
{'data_set_name': '可以使用:mdl264_put_call_erlanger_ratio_l2', 'description': '不可使用,仅供参考:The probability that the future trend of "Premium Ratio" will be neutral'} |
||||
{'data_set_name': '可以使用:mdl77_400_rdsale', 'description': '不可使用,仅供参考:R&D Intensity: It is defined as the average of the research & development expenses in the trailing 12-months deflated by the sum of total sales in the same period.'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetacall4', 'description': '不可使用,仅供参考:theta of near call options'} |
||||
{'data_set_name': '可以使用:top300_factor4_group20_score', 'description': '不可使用,仅供参考:Fourth factor score for top 300 securities, grouped into 20 clusters.'} |
||||
{'data_set_name': '可以使用:star_v14_val_industry_rank', 'description': '不可使用,仅供参考:Industry-relative (1-100) Relative Valuation Rank'} |
||||
{'data_set_name': '可以使用:coverage_sources_sales_orig', 'description': '不可使用,仅供参考:List or indicator of which data sources have covered the sales forecast in the original version module.'} |
||||
{'data_set_name': '可以使用:mdl177_pricemomentumfactor_rationalalpha_alt', 'description': '不可使用,仅供参考:Rational Decay Alpha : It evaluates stocks based on their historical 12-month market (S&P 500) adjusted excess return (the Y intercept from an OLS regression equation) using a proprietary rational decay function'} |
||||
{'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:anl49_backfill_dividendsdeclaredpershareindicator', 'description': '不可使用,仅供参考:Dividends declared per share indicator'} |
||||
{'data_set_name': '可以使用:info1d0_tone_score', 'description': '不可使用,仅供参考:Overall sentiment score for the event transcript or story in the info_1_D0 module.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_ew_sent_std', 'description': '不可使用,仅供参考:28-day Volume weighted average of Standard deviation of Sentiment'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p50_q50_w1_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:mdl230_us5000_cusip_mad3yttmsale', 'description': '不可使用,仅供参考:It is defined as the mean absolute deviation of 12-quarter trailing 12-month sales deflated by the average of total assests.'} |
||||
{'data_set_name': '可以使用:parkinson_volatility_10', 'description': "不可使用,仅供参考:Parkinson model's historical volatility over 2 weeks"} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_ew_sent_mean_mean', 'description': '不可使用,仅供参考:28-day Volume weighted average of Average of Sentiment Average'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_ew_sent_z_std', 'description': '不可使用,仅供参考:7-day Volume weighted average of Standard deviation of Sentiment'} |
||||
{'data_set_name': '可以使用:pv173_ranksbondreturn20deqwt_220', 'description': '不可使用,仅供参考:It is defined as the equally weighted single bond return over last 20 days with the filter of the bonds that mature between 3 years and 7 years.'} |
||||
{'data_set_name': '可以使用:pv87_2_cfps_qf_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_webv2_simpleavg60_topic_event_sentiment_score_business', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for topic Business'} |
||||
{'data_set_name': '可以使用:anl10_salinnovation_score_fy1_1696', 'description': '不可使用,仅供参考:Innovation score for sales FY1 (innovate_increase - innovate_decrease)'} |
||||
{'data_set_name': '可以使用:mdl177_valuemomemtummodel_earningsqualitymodule', 'description': '不可使用,仅供参考:Earnings Quality Module'} |
||||
{'data_set_name': '可以使用:asset_growth_rate', 'description': '不可使用,仅供参考:Aggregate Gamma'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_cash_flow_share_consensus_mean_numnochange', 'description': '不可使用,仅供参考:Number of no change revisions of Cash Flow / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:board_independence_subsector_rank', 'description': '不可使用,仅供参考:Company’s rank within its subsector peer group for board independence and diversity.'} |
||||
{'data_set_name': '可以使用:pv87_scores_fin_upmdown_partnormscr_std', 'description': '不可使用,仅供参考:Standard deviation of Financial up minus down partial score'} |
||||
{'data_set_name': '可以使用:mdl177_2_pricemomentumfactor_pc_ratio', 'description': '不可使用,仅供参考:Put/Call Ratio'} |
||||
{'data_set_name': '可以使用:oth432_trkdpitpredictiverndexpense_mae', 'description': '不可使用,仅供参考:Mean Average Error of the model of Research & Development Expense'} |
||||
{'data_set_name': '可以使用:mws87_sent_score_all', 'description': '不可使用,仅供参考:The sentiment score of all.'} |
||||
{'data_set_name': '可以使用:currency_gain_percentage', 'description': '不可使用,仅供参考:The percentage return generated from currency movements.'} |
||||
{'data_set_name': '可以使用:social_score_total_correlation', 'description': '不可使用,仅供参考:Social score weighted by metrics most strongly correlated (positive and negative) to financial returns.'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_book_value_share_consensus_mean_numanalystsunfiltered', 'description': '不可使用,仅供参考:Number of analysts (unfiltered) of Book Value / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_r6_book_value_share_consensus_mean_numupunfiltered', 'description': '不可使用,仅供参考:Number of up revisions of Book Value / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:pcf_ratio_relative_component_rank_v2', 'description': '不可使用,仅供参考:Global rank for the price-to-cash-flow ratio component in the valuation model (variant 2).'} |
||||
{'data_set_name': '可以使用:pv87_2_bps_af_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Book Value Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_hitscore_wordcount_sum', 'description': '不可使用,仅供参考:Sum of Total number of words in the Post'} |
||||
{'data_set_name': '可以使用:pv87_v2item_indrank_item_6050_258', 'description': '不可使用,仅供参考:Industry ranked item score for item 258 in topic Executive Compensation Schemes'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthmodel_div5yg', 'description': '不可使用,仅供参考:5-Year Dividend Growth Rate : It is defined as the 5-year growth in dividends'} |
||||
{'data_set_name': '可以使用:fn_treasury_stock_shares_a', 'description': '不可使用,仅供参考:Number of common and preferred shares that were previously issued and that were repurchased by the issuing entity and held in treasury on the financial statement date. This stock has no voting rights and receives no dividends.'} |
||||
{'data_set_name': '可以使用:oth567_deltascore_management_393', 'description': '不可使用,仅供参考:Management score'} |
||||
{'data_set_name': '可以使用:fscore_bfl_profitability', 'description': '不可使用,仅供参考:The purpose of this metric is to rank stock based on their ability to generate cash flows.'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_chgocfp_alt', 'description': '不可使用,仅供参考:The difference between the most recently reported trailing 12-month operating cash flow per share and that of 4 quarters ago for a stock divided by its trading price.'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volthetaput6', 'description': '不可使用,仅供参考:theta volume of far out put options'} |
||||
{'data_set_name': '可以使用:mdl264_sector_rank_l3', 'description': "不可使用,仅供参考:The probability that the future trend of 'Sector ranking' will move up"} |
||||
{'data_set_name': '可以使用:pv87_v2_expavg60_group_nip_partnerships', 'description': '不可使用,仅供参考:60-day Exponential average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Partnerships'} |
||||
{'data_set_name': '可以使用:pv87_2_eps_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Earnings Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:anl69_sales_market_status', 'description': '不可使用,仅供参考:Market Status'} |
||||
{'data_set_name': '可以使用:growth_potential_rank_derivative', 'description': '不可使用,仅供参考:Change in ranking for medium-term growth potential compared to previous period.'} |
||||
{'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_cv4qsales3y', 'description': '不可使用,仅供参考:Stability of 3-yr TTM Sales'} |
||||
{'data_set_name': '可以使用:pv87_webweightedavg60_group_ess_dividends', 'description': '不可使用,仅供参考:60-day Weighted average of ESS - Event Sentiment Score for group Dividends'} |
||||
{'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_chg3yepsp', 'description': '不可使用,仅供参考:The difference between the trailing 12-month earnings per share and that of 12-quarters ago for a stock divided by its month-end trading price.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_simple14d_ew_sent_z_tsrank', 'description': '不可使用,仅供参考:14-day Simple average of End-of-day time series rank of Sentiment'} |
||||
{'data_set_name': '可以使用:mdl109_gr_intr_sale', 'description': '不可使用,仅供参考:Historical YoY interim revenue growth'} |
||||
{'data_set_name': '可以使用:pv87_scores_fearnormscr_mean', 'description': '不可使用,仅供参考:Mean of fear score'} |
||||
{'data_set_name': '可以使用:mdl177_2_globaldevnorthamerica_v502_aspanratio', 'description': "不可使用,仅供参考:Stock's quarterly operating assets minus its operating liabilities deflated by the lagged total assets"} |
||||
{'data_set_name': '可以使用:oth455_partner_roam_w4_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using K-means into 10 groups.'} |
||||
{'data_set_name': '可以使用:mdl138_pdi5_sale', 'description': '不可使用,仅供参考:PDI-5 Factor based on Sales/Turnover'} |
||||
{'data_set_name': '可以使用:pv87_daily_qtr_matrix_cash_flow_share_consensus_mean_numupunfiltered', 'description': '不可使用,仅供参考:Number of up revisions of Cash Flow / Share Consensus Mean'} |
||||
{'data_set_name': '可以使用:mdl77_valueanalystmodel_qva_yoychgshares', 'description': "不可使用,仅供参考:Change in Shares Outstanding Rank: It is defined as a company's change in common shares outstanding over the last 12 months."} |
||||
{'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_speghc', 'description': '不可使用,仅供参考:1-yr Change in Assets-adj TTM EPS: It is defined as the trailing 12-month earnings per share before extra items (EPS) minus 4 quarters ago EPS deflated by the average total assets per share.'} |
||||
{'data_set_name': '可以使用:snt26_top75pctrankingavg', 'description': '不可使用,仅供参考:The average ranking of the top 75% percentile'} |
||||
{'data_set_name': '可以使用:fnd72_a2_sales_to_invent', 'description': '不可使用,仅供参考:Sales to inventory ratio provides critical clues about whether the firm is keeping storage costs under control and achieving the target revenues'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_sent_mean_mean', 'description': '不可使用,仅供参考:7-day Volume weighted average of Average of Sentiment Average'} |
||||
{'data_set_name': '可以使用:environmental_corr_weighted_sector_position', 'description': '不可使用,仅供参考:Company’s position within its sector based on environmental score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:nws12_mainz_close_vol', 'description': '不可使用,仅供参考:Main close volume'} |
||||
{'data_set_name': '可以使用:fnd72_a2_sales_to_other_asset', 'description': "不可使用,仅供参考:Other assets turnover ratio measures the efficiency of a company's use of its other assets in generating revenue or income to the company, in actual"} |
||||
{'data_set_name': '可以使用:oth455_partner_roam_w3_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using K-means into 5 groups.'} |
||||
{'data_set_name': '可以使用:management_ethics_subsector_rank', 'description': '不可使用,仅供参考:Company’s rank within its subsector peer group for management standards and ethics.'} |
||||
{'data_set_name': '可以使用:fnd65_totalcap_cusip_saleicap', 'description': '不可使用,仅供参考:It is defined as the trailing 12-month total revenues divided by the average of the invested capital in the same period.'} |
||||
{'data_set_name': '可以使用:fnd90_game_optimism_sale', 'description': '不可使用,仅供参考:Analyst Optimism Sales'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_sent_median', 'description': '不可使用,仅供参考:7-day Volume weighted average of Median of Sentiment'} |
||||
{'data_set_name': '可以使用:mdl230_allcap_sedol_rdsale', 'description': '不可使用,仅供参考:It is defined as the average of the research & development expenses in the trailing 12-months deflated by the sum of total sales in the same period.'} |
||||
{'data_set_name': '可以使用:other_participant_fre_score_presentation', 'description': '不可使用,仅供参考:Flesch Reading Ease (FRE) for other participants in presentation section.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_ew_sent_std_trend', 'description': '不可使用,仅供参考:28-day Volume weighted average of Trend of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:principal_component_score_14_top3000', 'description': '不可使用,仅供参考:Value of the fourteenth principal component for the top 3000 securities.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volvegacallmput1', 'description': '不可使用,仅供参考:Weighted average Vega for near in-the-money and out-of-the-money call and put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:oth460_technical_dma_high_l2', 'description': "不可使用,仅供参考:The probability that the future trend of '6 Day Moving Average of the stock's daily high value' will be neutral"} |
||||
{'data_set_name': '可以使用:mdl77_ohistoricalgrowthfactor_susgrowth', 'description': '不可使用,仅供参考:The maximum growth rate a firm can sustain without having to increase financial leverage.'} |
||||
{'data_set_name': '可以使用:mdl31_v14_ab1_bv_share_last_qtr', 'description': '不可使用,仅供参考:Last quarter book value per share'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oivegacallmput8', 'description': '不可使用,仅供参考:vega of near in call minus put options'} |
||||
{'data_set_name': '可以使用:anl10_prerevise_ratio_to_consensus_fy2_1392', 'description': '不可使用,仅供参考:Consensus estimate value for pre-tax or preliminary FY2'} |
||||
{'data_set_name': '可以使用:pv87_net_asset_value_share_consensus_median', 'description': '不可使用,仅供参考:Net Asset Value / Share Consensus Median'} |
||||
{'data_set_name': '可以使用:energy_sector_factor1_group20_score', 'description': '不可使用,仅供参考:First factor score for energy sector, grouped into 20 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oivegacall7', 'description': '不可使用,仅供参考:vega of near out call options'} |
||||
{'data_set_name': '可以使用:retail_dcs_score_presentation', 'description': '不可使用,仅供参考:Dale–Chall Score (DCS) for retail investors in presentation section.'} |
||||
{'data_set_name': '可以使用:anl49_4thfiscalquartersalesorrevenues', 'description': '不可使用,仅供参考:Fiscal quarter sales or revenues as reported.'} |
||||
{'data_set_name': '可以使用:pv87_v2_expavg20_group_event_sentiment_score_earnings', 'description': '不可使用,仅供参考:20-day Exponential average of Event Sentiment Score for group Earnings'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg60_group_event_sentiment_score_dividends', 'description': '不可使用,仅供参考:60-day Weighted average of Event Sentiment Score for group Dividends'} |
||||
{'data_set_name': '可以使用:mdl177_earningsqualityfactor_chgsgasale', 'description': '不可使用,仅供参考:Change in QTR SG&A Expenses vsSales : It is defined as the difference between the yearly change in quarterly Selling, General and Administrative expenses and yearly change in quarterly sales.'} |
||||
{'data_set_name': '可以使用:snt26_top10pctrankingavg_14', 'description': '不可使用,仅供参考:The average ranking of the top 10% percentile'} |
||||
{'data_set_name': '可以使用:fnd65_allcap_sedol_pctchgqtrsales', 'description': '不可使用,仅供参考:It is defined as the growth in the most recently reported quarterly sales per share as compared to 4 quarters ago.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple28d_ew_sent_mean_tsrank', 'description': '不可使用,仅供参考:28-day Simple average of End-of-day time series rank of Sentiment Average'} |
||||
{'data_set_name': '可以使用:anl4_cfi_flag', 'description': '不可使用,仅供参考:Cash Flow From Investing - forecast type (revision/new/...)'} |
||||
{'data_set_name': '可以使用:pv87_weightedavg20_topic_ess_all', 'description': '不可使用,仅供参考:20-day Weighted average of ESS - Event Sentiment Score for topic All'} |
||||
{'data_set_name': '可以使用:pv87_scores_negpartnormscr_median', 'description': '不可使用,仅供参考:Median of Negativity partial score'} |
||||
{'data_set_name': '可以使用:anl10_ebtrevise_ratio_to_close_fq1_1031', 'description': '不可使用,仅供参考:Ratio of delta consensus to adjusted close for earnings before tax Q1'} |
||||
{'data_set_name': '可以使用:nws94_web_v2_comp_flag_intraday', 'description': '不可使用,仅供参考:Flag to show if the news item arrived overnight (0) or intraday (1)'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volivcall4', 'description': '不可使用,仅供参考:Weighted average Implied volatility for near-the-money call options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:star_v14_val_piv_region_rank', 'description': '不可使用,仅供参考:Region-relative (1-100) rank of Price / Intrinsic Value'} |
||||
{'data_set_name': '可以使用:pv87_ac_5y_sale_mean', 'description': '不可使用,仅供参考:Historical 5Y revenue growth acceleration'} |
||||
{'data_set_name': '可以使用:mdl77_ovalueanalystmodel_qva_yoychgshares', 'description': "不可使用,仅供参考:Change in Shares Outstanding Rank: It is defined as a company's change in common shares outstanding over the last 12 months."} |
||||
{'data_set_name': '可以使用:mdl37_bk_broker_research', 'description': "不可使用,仅供参考:The global 1-100 rank of a company's credit riskiness based on textual data in broker research documents"} |
||||
{'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_slope4qcf3y', 'description': '不可使用,仅供参考:Slope of 3-yr TTM Cash Flow Trend Line'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetaput7', 'description': '不可使用,仅供参考:theta of near out put options'} |
||||
{'data_set_name': '可以使用:rp_nip_technical', 'description': '不可使用,仅供参考:News impact projection based on technical analysis'} |
||||
{'data_set_name': '可以使用:snt26_top50pctranking_2', 'description': '不可使用,仅供参考:The top 50% percentile ranking'} |
||||
{'data_set_name': '可以使用:pv87_2_ffops_qf_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Funds from Operations per Share (FFOPS) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volivput1', 'description': '不可使用,仅供参考:implied volatility volume of near in and out put options'} |
||||
{'data_set_name': '可以使用:rsk62_beta_factor_1_100_growth', 'description': '不可使用,仅供参考:eps growth'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg20_group_css_credit_ratings', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Credit Ratings'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volgammacall8', 'description': '不可使用,仅供参考:Weighted average Gamma for near in-the-money call options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:employee_compensation_subsector_rank', 'description': '不可使用,仅供参考:Company’s rank within its subsector peer group for employee compensation and satisfaction.'} |
||||
{'data_set_name': '可以使用:oth250_rank', 'description': '不可使用,仅供参考:Daily rank of product at time of collection out of 100'} |
||||
{'data_set_name': '可以使用:pv87_2_tbvps_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Tangible Book Value Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:anl49_vector_35estd35yrgrowthratedividendspershare', 'description': '不可使用,仅供参考:The annual compounded growth rate using the average of the three latest base years to the projected 3-5-year Dividends Declared per Share.'} |
||||
{'data_set_name': '可以使用:comm_sector_factor4_group2_score', 'description': '不可使用,仅供参考:Fourth factor score for communications sector, grouped into 2 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_ew_sent_std_range', 'description': '不可使用,仅供参考:14-day Volume weighted average of Range of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:broad_market_factor_score', 'description': '不可使用,仅供参考:Exposure to the broad market factor, representing overall market movements.'} |
||||
{'data_set_name': '可以使用:pv87_v2_simpleavg60_group_event_sentiment_score_acquisitions_mergers', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for group Acquisitions Mergers'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted28d_ew_sent_trend2', 'description': '不可使用,仅供参考:28-day Volume weighted average of Trend of Sentiment'} |
||||
{'data_set_name': '可以使用:cons_cyclical_method2_group20_score', 'description': '不可使用,仅供参考:Score from the second method for consumer cyclical sector, grouped into 20 clusters.'} |
||||
{'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_chg3yocfp', 'description': '不可使用,仅供参考:The difference between the the trailing 12-month operating cash flow per share and that of 12-quarters ago for a stock divided by its trading price.'} |
||||
{'data_set_name': '可以使用:mdl177_earningsqualityfactor_chgshare', 'description': "不可使用,仅供参考:Percent Change in Shares Outstanding : It is defined as the percent change in a company's current number of outstanding shares as compared to the number of shares outstanding one year ago."} |
||||
{'data_set_name': '可以使用:retail_sentiment_score_presentation', 'description': '不可使用,仅供参考:Overall sentiment score for retail investors in the presentation section.'} |
||||
{'data_set_name': '可以使用:pv87_prv2_simpleavg60_group_event_sentiment_score_partnerships', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for group Partnerships'} |
||||
{'data_set_name': '可以使用:pv87_websimpleavg20_group_ess_revenues', 'description': '不可使用,仅供参考:20-day Simple average of ESS - Event Sentiment Score for group Revenues'} |
||||
{'data_set_name': '可以使用:pv87_capital_expenditure_consensus_mean', 'description': '不可使用,仅供参考:Capital Expenditure Consensus Mean'} |
||||
{'data_set_name': '可以使用:top200_method3_group20_score', 'description': '不可使用,仅供参考:Score from the third method for top 200 securities, grouped into 20 clusters.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volvegaput6', 'description': '不可使用,仅供参考:Weighted average Vega for far out-of-the-money put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetacall5', 'description': '不可使用,仅供参考:theta of in call options'} |
||||
{'data_set_name': '可以使用:pv20_ard_shares_authorized', 'description': '不可使用,仅供参考:ARD Shares Authorized'} |
||||
{'data_set_name': '可以使用:pv87_sale_ev_mean', 'description': '不可使用,仅供参考:Revenue/TEV'} |
||||
{'data_set_name': '可以使用:fnd14_loc_state_country', 'description': '不可使用,仅供参考:Registrant location country/region'} |
||||
{'data_set_name': '可以使用:fnd65_totalcap_cusip_rationalalpha', 'description': '不可使用,仅供参考:It evaluates stocks based on their historical 12-month market (S&P 500) adjusted excess return (the Y intercept from an OLS regression equation) using a proprietary rational decay function.'} |
||||
{'data_set_name': '可以使用:tech_sector_factor3_group2_score', 'description': '不可使用,仅供参考:Third factor score for technology sector, grouped into 2 clusters.'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p50_q200_w1_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 10 groups.'} |
||||
{'data_set_name': '可以使用:mdl177_historicalgrowthfactor_chgocf', 'description': '不可使用,仅供参考:1-yr Chg in Assets-adj TTM Oper Cash Flow : It is defined as the most recently reported trailing 12-month operating cash flow minus 4 quarter ago trailing 12-month operating cash flow divided by the average total assets.'} |
||||
{'data_set_name': '可以使用:pv87_2_capex_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Capital Expenditure *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:company_name_match_score', 'description': '不可使用,仅供参考:Numeric score indicating similarity between extracted and actual company name.'} |
||||
{'data_set_name': '可以使用:anl10_ndtpast_det_excflag_1682', 'description': '不可使用,仅供参考:Exclusion flag for date estimates'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg60_group_css_analyst_ratings', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Analyst Ratings'} |
||||
{'data_set_name': '可以使用:oth567_deltaprimary_country_367', 'description': '不可使用,仅供参考:Country'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_css_labor_issues', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Labor Issues'} |
||||
{'data_set_name': '可以使用:oth567score_diversity_and_inclusion', 'description': '不可使用,仅供参考:Score for diversity and inclusion'} |
||||
{'data_set_name': '可以使用:pv52_asdaq_shares_0_9_sec', 'description': '不可使用,仅供参考:Shares from 0 to 9 Seconds'} |
||||
{'data_set_name': '可以使用:pv87_web_expavg60_group_css_revenues', 'description': '不可使用,仅供参考:60-day Exponential average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Revenues'} |
||||
{'data_set_name': '可以使用:fnd72_pit_or_cr_a_int_exp_yr_growth', 'description': '不可使用,仅供参考:Percentage change in interest expense from last year to the current year'} |
||||
{'data_set_name': '可以使用:tech_sector_factor1_group5_score', 'description': '不可使用,仅供参考:First factor score for technology sector, grouped into 5 clusters.'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p10_q50_w2_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 5 groups.'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w2_pca_fact1_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 1st eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:anl44_best_opp_to_sales', 'description': '不可使用,仅供参考:best opp to sales'} |
||||
{'data_set_name': '可以使用:pv87_2_fcfps_af_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Financing Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_2_capex_qf_matrix_p1_b_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Capital Expenditure *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv52_yse_chicago_shares_5_30_min', 'description': '不可使用,仅供参考:Shares from 5 to 30 Minutes'} |
||||
{'data_set_name': '可以使用:pv87_2_roa_qf_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Return On Assets *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_volvegacall4', 'description': '不可使用,仅供参考:vega volume of near call options'} |
||||
{'data_set_name': '可以使用:mdl177_2_deepvaluefactor_ttmsaleev', 'description': '不可使用,仅供参考:TTM Sales-to-Enterprise Value : It is defined as the trailing 12-month sales for a stock divided by the most recent enterprise value (EV)EV = Equity Market Value + Long-term Debt + Short-term Debt + Preferred Stock + Minority Interest - Cash& Cash Equivalents.'} |
||||
{'data_set_name': '可以使用:max_shares_outstanding_guidance', 'description': '不可使用,仅供参考:The maximum guidance for Shares'} |
||||
{'data_set_name': '可以使用:principal_component_score_0_all', 'description': '不可使用,仅供参考:Value of the 1st principal component for all securities in the universe.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_ew_sent_mean_median', 'description': '不可使用,仅供参考:28-day Volume weighted average of Median of Sentiment Average'} |
||||
{'data_set_name': '可以使用:fnd28_annualforeign_value_08725a', 'description': '不可使用,仅供参考:value of annual field: Foreign Sales Growth'} |
||||
{'data_set_name': '可以使用:mdl230_totalcap_cusip_rdsale', 'description': '不可使用,仅供参考:It is defined as the average of the research & development expenses in the trailing 12 months deflated by the sum of total sales in the same period.'} |
||||
{'data_set_name': '可以使用:min_primary_sentiment_score_transfer', 'description': '不可使用,仅供参考:The lowest value of the primary transferred sentiment score for the period.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oiivcallmput5', 'description': '不可使用,仅供参考:Weighted average Implied volatility for in-the-money call and put options with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg60_group_css_revenues', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Revenues'} |
||||
{'data_set_name': '可以使用:mdl264_call_put_ratio_10_day_l2', 'description': "不可使用,仅供参考:The probability that the future trend of '10-day median of Call Volume to Put Volume' will be neutral"} |
||||
{'data_set_name': '可以使用:mdl177_2_managementqualityfactor_aspanratio', 'description': "不可使用,仅供参考:Stock's quarterly operating assets minus its operating liabilities deflated by the lagged total assets"} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_ew_sent_z_tsrank', 'description': '不可使用,仅供参考:7-day Volume weighted average of End-of-day time series rank of Sentiment'} |
||||
{'data_set_name': '可以使用:anl83_numvswordsratioexeqa', 'description': '不可使用,仅供参考:number of numerical/number of all words of executives in Q&A (NA if no Q&A)'} |
||||
{'data_set_name': '可以使用:mdl262_saleq_compustatdeltapredict_funda_predict', 'description': '不可使用,仅供参考:Predict value of Sales/Turnover (Net)'} |
||||
{'data_set_name': '可以使用:pv87_v2_weightedavg60_group_event_sentiment_score_partnerships', 'description': '不可使用,仅供参考:60-day Weighted average of Event Sentiment Score for group Partnerships'} |
||||
{'data_set_name': '可以使用:fnd28_growthratesa_value_08631a', 'description': '不可使用,仅供参考:value of annual field: Net Sales/Revenues Growth'} |
||||
{'data_set_name': '可以使用:pv87_neg_earnings_matrix_event_sentiment_score_median', 'description': '不可使用,仅供参考:Median of Event Sentiment Score for type Negearnings'} |
||||
{'data_set_name': '可以使用:pv87_2_csh_qf_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Common Shares *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oigammacallmput9', 'description': '不可使用,仅供参考:Weighted average Gamma for deep in-the-money call and put options with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_gr_5y_sale_mean', 'description': '不可使用,仅供参考:Historical 5Y revenue growth trend'} |
||||
{'data_set_name': '可以使用:pv87_2_capex_qf_matrix_p1_b_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Capital Expenditure *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:anl69_eqy_split_ratio', 'description': '不可使用,仅供参考:Split Ratio'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_revenue_consensus_mean_numnochange', 'description': '不可使用,仅供参考:Number of no change revisions of Revenue Consensus Mean'} |
||||
{'data_set_name': '可以使用:pv87_webv2_weightedavg60_group_event_sentiment_score_products_services', 'description': '不可使用,仅供参考:60-day Weighted average of Event Sentiment Score for group Products Services'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p10_q50_w3_pca_fact1_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 1st eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:environmental_corr_weighted_subsector_percentile', 'description': '不可使用,仅供参考:Company’s percentile within its subsector based on environmental score weighted by KPIs most correlated to financial returns.'} |
||||
{'data_set_name': '可以使用:min_research_development_expense_guidance', 'description': '不可使用,仅供参考:Minimum guidance value for Research & Development Expense'} |
||||
{'data_set_name': '可以使用:pv87_2_bps_af_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Book Value Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:managed_healthcare_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the managed healthcare sector factor.'} |
||||
{'data_set_name': '可以使用:mdl177_2_globaldevnorthamerica_v502_salerec', 'description': '不可使用,仅供参考:Change in TTM Sales vsAccounts Receivable : It is defined as the difference between the yearly percent change in trailing 12-month sales and the yearly percent change in accounts receivable.'} |
||||
{'data_set_name': '可以使用:pv87_2_sales_af_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_v2_expavg60_group_event_sentiment_score_all', 'description': '不可使用,仅供参考:60-day Exponential average of Event Sentiment Score for group All'} |
||||
{'data_set_name': '可以使用:pv87_2_netdebt_qf_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:mdl77_ohistoricalgrowthfactor_chg3ycfast', 'description': '不可使用,仅供参考:3-yr Change in Assets-adj TTM Cash Flow: It is defined as the most recently reported trailing 12-month operating cash flow minus 12 quarters ago comparable trailing 12-month cash flow scaled by the average total assets in the same period.'} |
||||
{'data_set_name': '可以使用:fnd28_annualgrowth_value_08604a', 'description': '不可使用,仅供参考:Value of annual field: Earnings Per Share - 3 Yr Annual Growth Five Year Averages'} |
||||
{'data_set_name': '可以使用:pv52_yse_arca_shares_0_9_sec', 'description': '不可使用,仅供参考:Shares from 0 to 9 Seconds'} |
||||
{'data_set_name': '可以使用:pv87_webv2_expavg20_group_event_sentiment_score_partnerships', 'description': '不可使用,仅供参考:20-day Exponential average of Event Sentiment Score for group Partnerships'} |
||||
{'data_set_name': '可以使用:pv87_v2item_indrank_item_6030_222', 'description': '不可使用,仅供参考:Industry ranked item score for item 222 in topic Board Structure'} |
||||
{'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_nip_equity_actions', 'description': '不可使用,仅供参考:20-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Equity Actions'} |
||||
{'data_set_name': '可以使用:momentum_rank_by_region_float', 'description': "不可使用,仅供参考:Numeric rank of a security's momentum compared to peers within the same geographic region."} |
||||
{'data_set_name': '可以使用:anl14_median_revenue_fy2', 'description': '不可使用,仅供参考:Median of estimations of revenue - upcoming 2 years'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q50_w3_pca_fact3_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 20 groups.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_simple28d_ew_sent_tsrank', 'description': '不可使用,仅供参考:28-day Simple average of End-of-day time series rank of Sentiment'} |
||||
{'data_set_name': '可以使用:mdl77_growthanalystmodel_qga_fcfroe', 'description': '不可使用,仅供参考:Free Cash Flow ROE'} |
||||
{'data_set_name': '可以使用:mdl109_matrix_ac_5y_sale', 'description': '不可使用,仅供参考:Historical 5Y revenue growth acceleration'} |
||||
{'data_set_name': '可以使用:pv87_2_roa_qf_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Return On Assets *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_sent_std_mean', 'description': '不可使用,仅供参考:7-day Volume weighted average of Average of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_sent_mean_std', 'description': '不可使用,仅供参考:14-day Volume weighted average of Standard deviation of Sentiment Average'} |
||||
{'data_set_name': '可以使用:mws52_expirationtime', 'description': '不可使用,仅供参考:Expiration time of the event'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_capital_expenditure_consensus_mean_numnochangeunfiltered', 'description': '不可使用,仅供参考:Number of no change revisions (unfiltered) of Capital Expenditure Consensus Mean'} |
||||
{'data_set_name': '可以使用:anl14_high_revenue_fy1', 'description': '不可使用,仅供参考:The Highest Estimation of Revenue - upcoming year'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_ew_sent_std_median', 'description': '不可使用,仅供参考:7-day Volume weighted average of Median of Sentiment Standard deviation'} |
||||
{'data_set_name': '可以使用:anl10_dpsrevise_ratio_to_close_fy1_1571', 'description': '不可使用,仅供参考:Ratio of delta consensus to adjusted close for dividends per share FY1'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p50_q50_w3_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 5 groups.'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w5_pca_fact2_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 20 groups.'} |
||||
{'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetacallmput4', 'description': '不可使用,仅供参考:theta of near call minus put options'} |
||||
{'data_set_name': '可以使用:mdl177_pricemomentumfactor_visiratio_alt', 'description': "不可使用,仅供参考:The Visibility Ratio : It equals to a stock's most recent daily trading volume divided by the average daily trading volume in previous 50 trading days."} |
||||
{'data_set_name': '可以使用:oth455_customer_roam_w3_pca_fact2_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using the 2nd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:anl10_ebsinnovation_score_fy1', 'description': '不可使用,仅供参考:Innovation score for earnings before others FY1 (innovate_increase - innovate_decrease)'} |
||||
{'data_set_name': '可以使用:other_cfo_word_share_presentation', 'description': '不可使用,仅供参考:Proportion of words spoken by other CFOs relative to all executive words in the presentation section.'} |
||||
{'data_set_name': '可以使用:pv52_yse_national_tot_cov_shares', 'description': '不可使用,仅供参考:Total Covered Shares'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q50_w2_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oigammacallmput5', 'description': '不可使用,仅供参考:Weighted average Gamma for in-the-money call and put options with open interest used as weight factor'} |
||||
{'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w3_pca_fact1_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 1st eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple14d_ew_sent_mean_tsrank', 'description': '不可使用,仅供参考:14-day Simple average of End-of-day time series rank of Sentiment Average'} |
||||
{'data_set_name': '可以使用:headline_sentiment_score_story', 'description': '不可使用,仅供参考:Overall sentiment score calculated for the headline in the story analysis.'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_matrix_sent_ew_sent_mean_volweightedmean', 'description': '不可使用,仅供参考:Volume weighted mean of Sentiment Average'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w3_pca_fact3_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 3rd eigenvalue of PCA into 5 groups.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volvegacallmput6', 'description': '不可使用,仅供参考:Weighted average Vega for far out-of-the-money call and put options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_sell_sharesdivhold_sum', 'description': '不可使用,仅供参考:Sum of Selling Shares / Holdings'} |
||||
{'data_set_name': '可以使用:headline_negative_score_value', 'description': '不可使用,仅供参考:Score representing the negative sentiment in the news headline.'} |
||||
{'data_set_name': '可以使用:recent_broker_research_document_count', 'description': '不可使用,仅供参考:Number of broker research reports analyzed in the past month.'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volthetacall1', 'description': '不可使用,仅供参考:Weighted average Theta for near in-the-money and out-of-the-money call options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:avg_diversity_inclusion_score', 'description': '不可使用,仅供参考:Average rating for diversity and inclusion.'} |
||||
{'data_set_name': '可以使用:pv87_2_roe_qf_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Return On Equity *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_sent_deviation', 'description': '不可使用,仅供参考:14-day Volume weighted average of Deviation of Sentiment'} |
||||
{'data_set_name': '可以使用:anl49_estdcurrentperatio', 'description': "不可使用,仅供参考:Estimated earnings per share for the 12 months ending 6 months ahead, divided into the stock's price."} |
||||
{'data_set_name': '可以使用:fnd65_us5000_cusip_ocfratio', 'description': "不可使用,仅供参考:It is defined as a stock's most recently reported quarterly cash flow from operations divided by its current liabilities."} |
||||
{'data_set_name': '可以使用:pv48_r3000_shares_new_value', 'description': '不可使用,仅供参考:New value shares for the US 3000 index.'} |
||||
{'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_cash_flow_share_consensus_median_scale', 'description': '不可使用,仅供参考:Scale of Cash Flow / Share Consensus Median'} |
||||
{'data_set_name': '可以使用:sustainability_sector_rank', 'description': '不可使用,仅供参考:Company’s rank within its sector peer group for overall sustainability score.'} |
||||
{'data_set_name': '可以使用:mdl77_2growthanalystmodel2_qga_ltepssurprise', 'description': '不可使用,仅供参考:Long Term EPS Surprise: Long Term EPS Surprise'} |
||||
{'data_set_name': '可以使用:pv87_buy_sharesmulsig_sum', 'description': '不可使用,仅供参考:Sum of Buying Number of shares traded * Trade significance'} |
||||
{'data_set_name': '可以使用:pv87_webv2_simpleavg20_group_event_sentiment_score_analyst_ratings', 'description': '不可使用,仅供参考:20-day Simple average of Event Sentiment Score for group Analyst Ratings'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_sent_mean_mean', 'description': '不可使用,仅供参考:28-day Volume weighted average of Average of Sentiment Average'} |
||||
{'data_set_name': '可以使用:credit_risk_profitability_score', 'description': '不可使用,仅供参考:Percentile score reflecting profitability factors in credit risk assessment.'} |
||||
{'data_set_name': '可以使用:pv87_2_netdebt_af_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:anl10_ebtrevise_ratio_to_consensus_fq1_1026', 'description': '不可使用,仅供参考:Consensus estimate value for earnings before tax Q1'} |
||||
{'data_set_name': '可以使用:pv64_dif_stal_fund_expense_ratio', 'description': '不可使用,仅供参考:The amount investors pay for expenses incurred in operating a mutual fund (after any waivers).'} |
||||
{'data_set_name': '可以使用:anl10_prrrevise_ratio_to_consensus_fy1_2568', 'description': '不可使用,仅供参考:Consensus estimate value for price return ratio FY1'} |
||||
{'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_sent_z_trend', 'description': '不可使用,仅供参考:14-day Volume weighted average of Trend of Sentiment'} |
||||
{'data_set_name': '可以使用:pv87_v2_simpleavg60_group_event_sentiment_score_all', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for group All'} |
||||
{'data_set_name': '可以使用:pv87_2_sales_qf_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_capital_expenditure_consensus_high', 'description': '不可使用,仅供参考:Capital Expenditure Consensus High'} |
||||
{'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volvegacall5', 'description': '不可使用,仅供参考:Weighted average Vega for in-the-money call options with volume used as weight factor'} |
||||
{'data_set_name': '可以使用:pv87_2_grossmargin_af_matrix_all_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Gross Margin *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'data_set_name': '可以使用:pv87_qtr_matrix_capital_expenditure_consensus_mean_numnochange', 'description': '不可使用,仅供参考:Number of no change revisions of Capital Expenditure Consensus Mean'} |
||||
{'data_set_name': '可以使用:mdl230_us5000_cusip_fcfsale', 'description': '不可使用,仅供参考:It is defined as the trailing 12-month free cash flow divided by the trailing 12-month sales.'} |
||||
{'data_set_name': '可以使用:energy_sector_factor2_group20_score', 'description': '不可使用,仅供参考:Second factor score for energy sector, grouped into 20 clusters.'} |
||||
{'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_pctchgocf', 'description': "不可使用,仅供参考:1-yr Growth in TTM Oper Cash Flow : It is defined as the percent change of a stock's most recent trailing 12-month operating cash flow per share (OCF) as compared to the OCF 4 quarters ago."} |
||||
{'data_set_name': '可以使用:oth432_saleq_profitability_profitability8', 'description': '不可使用,仅供参考:8th profitability field of Sales/Turnover (Net)'} |
||||
{'data_set_name': '可以使用:anl83_sent_score_pres', 'description': '不可使用,仅供参考:The Sentiment Score of Presentation'} |
||||
{'data_set_name': '可以使用:fnd72_a2_sales_per_empl', 'description': '不可使用,仅供参考:Measure of net sales per 1,000 employees'} |
||||
{'data_set_name': '可以使用:oth455_partner_n2v_p10_q50_w5_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'data_set_name': '可以使用:mdl230_totalcap_cusip_slope4qsales3y', 'description': '不可使用,仅供参考:It is defined as the slope coefficient between monthly dates and the corresponding trailing 12-month sales per share in the prior 12 quarters.'} |
||||
{'data_set_name': '可以使用:ceo_lix_score_qa', 'description': '不可使用,仅供参考:LIX readability score for CEO in Q&A section.'} |
||||
{'data_set_name': '可以使用:mdl264_power_rank_l2', 'description': '不可使用,仅供参考:The probability that the future trend of "Overall Ranking" will be neutral'} |
||||
========================= 数据字段结束 ======================================= |
||||
|
||||
以上数据字段和操作符, 按照Description说明组合, 但是每一个 alpha 组合的使用的数据字段和操作符不要过于集中, 在符合语法的情况下, 多尝试不同的组合 |
||||
|
||||
你再检查一下, 如果你使用了 |
||||
Operator abs does not support event inputs |
||||
Operator ts_mean does not support event inputs |
||||
Operator ts_scale does not support event inputs |
||||
Operator add does not support event inputs |
||||
Operator sign does not support event inputs |
||||
Operator greater does not support event inputs |
||||
Operator ts_av_diff does not support event inputs |
||||
Operator ts_quantile does not support event inputs |
||||
Operator ts_arg_min does not support event inputs |
||||
Operator divide does not support event inputs |
||||
Operator ts_corr does not support event inputs |
||||
Operator ts_decay_linear does not support event inputs |
||||
Operator ts_sum does not support event inputs |
||||
Operator ts_delay does not support event inputs |
||||
Operator ts_arg_max does not support event inputs |
||||
Operator ts_std_dev does not support event inputs |
||||
Operator ts_regression does not support event inputs |
||||
Operator ts_backfill does not support event inputs |
||||
Operator signed_power does not support event inputs |
||||
Operator ts_product does not support event inputs |
||||
Operator ts_zscore does not support event inputs |
||||
Operator group_rank does not support event inputs |
||||
Operator subtract does not support event inputs |
||||
Operator ts_delta does not support event inputs |
||||
Operator ts_rank does not support event inputs |
||||
Operator ts_count_nans does not support event inputs |
||||
Operator ts_covariance does not support event inputs |
||||
Operator multiply does not support event inputs |
||||
Operator if_else does not support event inputs |
||||
Operator group_neutralize does not support event inputs |
||||
Operator group_zscore does not support event inputs |
||||
Operator winsorize does not support event inputs |
||||
注意, 以上操作符不能使用事件类型的数据集, 以上操作符禁止使用事件类型的数据集!! |
||||
@ -0,0 +1,617 @@ |
||||
跨境技术溢出效应 |
||||
假设 |
||||
在全球化产业链中，若一家公司的海外主要客户或供应商拥有强大的技术创新能力（如高研发投入、高专利质量），则该公司可能通过业务关联，获得隐性的知识外溢与技术扩散益处。这种“技术溢出”能提升该公司的运营效率、产品竞争力或降低其研发风险，从而可能在未来转化为超预期的盈利增长与估值提升。市场对这类隐含的、非线性的增长期权可能存在定价不足。 |
||||
实施方案 |
||||
构建“技术关联强度”因子。识别公司年报或供应链数据中披露的前五大海外客户/供应商，并获取这些关联实体的公开技术创新指标（如人均专利引用量、研发费用增速）。使用加权平均算子，依据交易金额占比为权重，计算公司所关联的海外实体的整体技术强度。使用时序滞后算子，将技术强度数据滞后6-12个月以匹配技术吸收与转化周期，再通过横截面排名评估公司在全市场中的相对技术关联优势。 |
||||
阿尔法因子优化建议 |
||||
技术溢出的效果受公司自身“吸收能力”调节。建议引入公司自身的研发团队质量（如技术人员占比）、内部研发投入强度作为调节变量，通过交互项算子或条件分层处理（例如，仅在自身研发投入超过行业平均的公司样本中，技术关联强度因子才被启用），以更精准地捕捉那些既拥有外部技术源头、又有能力内部化的优质标的。 |
||||
Cross-Border Technology Spillover Effect |
||||
Hypothesis |
||||
In the global industrial chain, if a company's key overseas customers or suppliers possess strong technological innovation capabilities (e.g., high R&D investment, high patent quality), the company may benefit from implicit knowledge spillover and technology diffusion through these business linkages. This "technology spillover" can enhance the company's operational efficiency, product competitiveness, or reduce its R&D risks, potentially translating into unexpected profit growth and valuation appreciation in the future. The market may underprice this implicit, non-linear growth option. |
||||
Implementation Plan |
||||
Construct a "Technology Linkage Intensity" factor. Identify the top five overseas customers/suppliers disclosed in the company's annual reports or supply chain data, and obtain public technological innovation metrics for these linked entities (e.g., patent citations per capita, R&D expense growth rate). Use a weighted average operator, with transaction amount proportion as weights, to calculate the aggregated technological strength of the overseas entities linked to the company. Apply a time-series lag operator to lag the technology strength data by 6-12 months to account for technology absorption and conversion cycles, then assess the company's relative technological linkage advantage across the market via cross-sectional ranking. |
||||
Alpha Factor Optimization Suggestion |
||||
The effect of technology spillover is moderated by the company's own "absorptive capacity." It is suggested to introduce the quality of the company's own R&D team (e.g., proportion of technical staff) and internal R&D intensity as moderating variables. Through interaction term operators or conditional stratification (e.g., enabling the Technology Linkage Intensity factor only within the subsample of companies whose own R&D investment exceeds the industry average), the factor can more precisely identify high-quality targets that possess both external technology sources and the internal capability to assimilate them. |
||||
*=========================================================================================* |
||||
输出格式： |
||||
输出必须是且仅是纯文本。 |
||||
每一行是一个完整、独立、语法正确的WebSim表达式。 |
||||
严禁任何形式的解释、编号、标点包裹（如引号）、Markdown格式或额外文本。 |
||||
===================== !!! 重点(输出方式) !!! ===================== |
||||
现在，请严格遵守以上所有规则，开始生成可立即在WebSim中运行的复合因子表达式。 |
||||
不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 |
||||
**输出格式**(一行一个表达式, 每个表达式中间需要添加一个空行, 只要表达式本身, 不需要赋值, 不要解释, 不需要序号, 也不要输出多余的东西)： |
||||
表达式 |
||||
表达式 |
||||
表达式 |
||||
... |
||||
表达式 |
||||
================================================================= |
||||
重申：请确保所有表达式都使用WorldQuant WebSim平台函数，不要使用pandas、numpy或其他Python库函数。输出必须是一行有效的WQ表达式。 |
||||
以下是我的账号有权限使用的操作符, 请严格按照操作符, 以及我提供的数据集, 进行生成,组合 100 个 alpha： |
||||
不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 |
||||
================================================================= |
||||
ts_product ts_zscore ts_mean ts_scale add sign subtract ts_delta ts_rank greater ts_av_diff ts_quantile ts_count_nans ts_covariance |
||||
ts_arg_min divide ts_corr multiply if_else ts_sum ts_delay group_zscore ts_arg_max ts_std_de ts_backfill |
||||
以上这些操作符不能传入事件类型的数据集, 只能传入时间序列数据集, 不能传入事件数据,不能传入事件数据,不能传入事件数据 |
||||
|
||||
以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子 |
||||
|
||||
========================= 操作符开始 ======================================= |
||||
注意: Operator: 后面的是操作符(是可以使用的), |
||||
Description: 此字段后面的是操作符对应的描述或使用说明(禁止使用, 仅供参考), Description字段后面的内容是使用说明, 不是操作符 |
||||
特别注意!!!! 必须按照操作符字段Operator的使用说明生成 alphaOperator: abs(x) |
||||
Description: Absolute value of x |
||||
Operator: add(x, y, filter = false) |
||||
Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding |
||||
Operator: densify(x) |
||||
Description: Converts a grouping field of many buckets into lesser number of only available buckets so as to make working with grouping fields computationally efficient |
||||
Operator: divide(x, y) |
||||
Description: x / y |
||||
Operator: inverse(x) |
||||
Description: 1 / x |
||||
Operator: log(x) |
||||
Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights. |
||||
Operator: max(x, y, ..) |
||||
Description: Maximum value of all inputs. At least 2 inputs are required |
||||
Operator: min(x, y ..) |
||||
Description: Minimum value of all inputs. At least 2 inputs are required |
||||
Operator: multiply(x ,y, ... , filter=false) |
||||
Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1 |
||||
Operator: power(x, y) |
||||
Description: x ^ y |
||||
Operator: reverse(x) |
||||
Description: - x |
||||
Operator: sign(x) |
||||
Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN; |
||||
Operator: signed_power(x, y) |
||||
Description: x raised to the power of y such that final result preserves sign of x |
||||
Operator: sqrt(x) |
||||
Description: Square root of x |
||||
Operator: subtract(x, y, filter=false) |
||||
Description: x-y. If filter = true, filter all input NaN to 0 before subtracting |
||||
Operator: and(input1, input2) |
||||
Description: Logical AND operator, returns true if both operands are true and returns false otherwise |
||||
Operator: if_else(input1, input2, input 3) |
||||
Description: If input1 is true then return input2 else return input3. |
||||
Operator: input1 < input2 |
||||
Description: If input1 < input2 return true, else return false |
||||
Operator: input1 <= input2 |
||||
Description: Returns true if input1 <= input2, return false otherwise |
||||
Operator: input1 == input2 |
||||
Description: Returns true if both inputs are same and returns false otherwise |
||||
Operator: input1 > input2 |
||||
Description: Logic comparison operators to compares two inputs |
||||
Operator: input1 >= input2 |
||||
Description: Returns true if input1 >= input2, return false otherwise |
||||
Operator: input1!= input2 |
||||
Description: Returns true if both inputs are NOT the same and returns false otherwise |
||||
Operator: is_nan(input) |
||||
Description: If (input == NaN) return 1 else return 0 |
||||
Operator: not(x) |
||||
Description: Returns the logical negation of x. If x is true (1), it returns false (0), and if input is false (0), it returns true (1). |
||||
Operator: or(input1, input2) |
||||
Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise |
||||
Operator: days_from_last_change(x) |
||||
Description: Amount of days since last change of x |
||||
Operator: hump(x, hump = 0.01) |
||||
Description: Limits amount and magnitude of changes in input (thus reducing turnover) |
||||
Operator: kth_element(x, d, k) |
||||
Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1 |
||||
Operator: last_diff_value(x, d) |
||||
Description: Returns last x value not equal to current x value from last d days |
||||
Operator: ts_arg_max(x, d) |
||||
Description: Returns the relative index of the max value in the time series for the past d days. If the current day has the max value for the past d days, it returns 0. If previous day has the max value for the past d days, it returns 1 |
||||
Operator: ts_arg_min(x, d) |
||||
Description: Returns the relative index of the min value in the time series for the past d days; If the current day has the min value for the past d days, it returns 0; If previous day has the min value for the past d days, it returns 1. |
||||
Operator: ts_av_diff(x, d) |
||||
Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation |
||||
Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN") |
||||
Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value) |
||||
Operator: ts_corr(x, y, d) |
||||
Description: Returns correlation of x and y for the past d days |
||||
Operator: ts_count_nans(x ,d) |
||||
Description: Returns the number of NaN values in x for the past d days |
||||
Operator: ts_covariance(y, x, d) |
||||
Description: Returns covariance of y and x for the past d days |
||||
Operator: ts_decay_linear(x, d, dense = false) |
||||
Description: Returns the linear decay on x for the past d days. Dense parameter=false means operator works in sparse mode and we treat NaN as 0. In dense mode we do not. |
||||
Operator: ts_delay(x, d) |
||||
Description: Returns x value d days ago |
||||
Operator: ts_delta(x, d) |
||||
Description: Returns x - ts_delay(x, d) |
||||
Operator: ts_mean(x, d) |
||||
Description: Returns average value of x for the past d days. |
||||
Operator: ts_product(x, d) |
||||
Description: Returns product of x for the past d days |
||||
Operator: ts_quantile(x,d, driver="gaussian" ) |
||||
Description: It calculates ts_rank and apply to its value an inverse cumulative density function from driver distribution. Possible values of driver (optional ) are "gaussian", "uniform", "cauchy" distribution where "gaussian" is the default. |
||||
Operator: ts_rank(x, d, constant = 0) |
||||
Description: Rank the values of x for each instrument over the past d days, then return the rank of the current value + constant. If not specified, by default, constant = 0. |
||||
Operator: ts_regression(y, x, d, lag = 0, rettype = 0) |
||||
Description: Returns various parameters related to regression function |
||||
Operator: ts_scale(x, d, constant = 0) |
||||
Description: Returns (x - ts_min(x, d)) / (ts_max(x, d) - ts_min(x, d)) + constant. This operator is similar to scale down operator but acts in time series space |
||||
Operator: ts_std_dev(x, d) |
||||
Description: Returns standard deviation of x for the past d days |
||||
Operator: ts_step(1) |
||||
Description: Returns days' counter |
||||
Operator: ts_sum(x, d) |
||||
Description: Sum values of x for the past d days. |
||||
Operator: ts_zscore(x, d) |
||||
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean: (x - tsmean(x,d)) / tsstddev(x,d). This operator may help reduce outliers and drawdown. |
||||
Operator: normalize(x, useStd = false, limit = 0.0) |
||||
Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element |
||||
Operator: quantile(x, driver = gaussian, sigma = 1.0) |
||||
Description: Rank the raw vector, shift the ranked Alpha vector, apply distribution (gaussian, cauchy, uniform). If driver is uniform, it simply subtract each Alpha value with the mean of all Alpha values in the Alpha vector |
||||
Operator: rank(x, rate=2) |
||||
Description: Ranks the input among all the instruments and returns an equally distributed number between 0.0 and 1.0. For precise sort, use the rate as 0 |
||||
Operator: scale(x, scale=1, longscale=1, shortscale=1) |
||||
Description: Scales input to booksize. We can also scale the long positions and short positions to separate scales by mentioning additional parameters to the operator |
||||
Operator: winsorize(x, std=4) |
||||
Description: Winsorizes x to make sure that all values in x are between the lower and upper limits, which are specified as multiple of std. |
||||
Operator: zscore(x) |
||||
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean |
||||
Operator: vec_avg(x) |
||||
Description: Taking mean of the vector field x |
||||
Operator: vec_sum(x) |
||||
Description: Sum of vector field x |
||||
Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10") |
||||
Description: Convert float values into indexes for user-specified buckets. Bucket is useful for creating group values, which can be passed to GROUP as input |
||||
Operator: trade_when(x, y, z) |
||||
Description: Used in order to change Alpha values only under a specified condition and to hold Alpha values in other cases. It also allows to close Alpha positions (assign NaN values) under a specified condition |
||||
Operator: group_backfill(x, group, d, std = 4.0) |
||||
Description: If a certain value for a certain date and instrument is NaN, from the set of same group instruments, calculate winsorized mean of all non-NaN values over last d days |
||||
Operator: group_mean(x, weight, group) |
||||
Description: All elements in group equals to the mean |
||||
Operator: group_neutralize(x, group) |
||||
Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant |
||||
Operator: group_rank(x, group) |
||||
Description: Each elements in a group is assigned the corresponding rank in this group |
||||
Operator: group_scale(x, group) |
||||
Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin) |
||||
Operator: group_zscore(x, group) |
||||
Description: Calculates group Z-score - numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. zscore = (data - mean) / stddev of x for each instrument within its group. |
||||
========================= 操作符结束 ======================================= |
||||
|
||||
========================= 数据字段开始 ======================================= |
||||
注意: data_set_name: 后面的是数据字段(可以使用), description: 此字段后面的是数据字段对应的描述或使用说明(不能使用) |
||||
|
||||
{'id': 322779, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_simple14d_ew_sent_mean_tsrank', 'description': '不可使用,仅供参考:14-day Simple average of End-of-day time series rank of Sentiment Average'} |
||||
{'id': 9842, 'data_set_name': '可以使用:retail_lix_score_presentation', 'description': '不可使用,仅供参考:LIX readability score for retail investors in presentation section.'} |
||||
{'id': 1364, 'data_set_name': '可以使用:environmental_positive_corr_score', 'description': '不可使用,仅供参考:Environmental score weighted by KPIs most positively correlated to financial returns.'} |
||||
{'id': 322303, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oithetacallmput1', 'description': '不可使用,仅供参考:Weighted average Theta for near in-the-money and out-of-the-money call and put options with open interest used as weight factor'} |
||||
{'id': 87043, 'data_set_name': '可以使用:fnd72_sales_to_net_fix_asset', 'description': '不可使用,仅供参考:Measures the sales to net fixed assets'} |
||||
{'id': 319501, 'data_set_name': '可以使用:pv7_superrelation_sec_all_score', 'description': '不可使用,仅供参考:Relation scores from SEC report, with backfill'} |
||||
{'id': 322996, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_median', 'description': '不可使用,仅供参考:14-day Volume weighted average of Median of Sentiment'} |
||||
{'id': 324627, 'data_set_name': '可以使用:pv87_revere_customer_transform_similarity_score_float', 'description': '不可使用,仅供参考:Similarity score of related instruments'} |
||||
{'id': 296402, 'data_set_name': '可以使用:oth567score_culture_341', 'description': '不可使用,仅供参考:Culture score'} |
||||
{'id': 79018, 'data_set_name': '可以使用:fn_entity_common_stock_shares_out_q', 'description': "不可使用,仅供参考:Indicate number of shares or other units outstanding of each of registrant's classes of capital or common stock or other ownership interests, if and as stated on cover of related periodic report. Where multiple classes or units exist define each class/interest by adding class of stock items such as Common Class A [Member], Common Class B [Member] or Partnership Interest [Member] onto the Instrument [Domain] of the Entity Listings, Instrument."} |
||||
{'id': 10535, 'data_set_name': '可以使用:mws87_sent_score_all', 'description': '不可使用,仅供参考:The sentiment score of all.'} |
||||
{'id': 1548, 'data_set_name': '可以使用:anl14_actvalue_revenue_fy0', 'description': '不可使用,仅供参考:Revenue - recent last year'} |
||||
{'id': 166286, 'data_set_name': '可以使用:mdl264_call_put_erlanger_ratio_l3', 'description': "不可使用,仅供参考:The probability that the future trend of 'Premium Ratio' will move up"} |
||||
{'id': 318546, 'data_set_name': '可以使用:principal_component_score_10_all', 'description': '不可使用,仅供参考:Value of the 11th principal component for all securities in the universe.'} |
||||
{'id': 321298, 'data_set_name': '可以使用:pv87_daily_ann_matrix_r1_revenue_consensus_mean_numanalystsunfiltered', 'description': '不可使用,仅供参考:Number of analysts (unfiltered) of Revenue Consensus Mean'} |
||||
{'id': 324215, 'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_css_earnings', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Earnings'} |
||||
{'id': 279907, 'data_set_name': '可以使用:nws73_globalsent_uncertaintyscore', 'description': '不可使用,仅供参考:Global Uncertainty'} |
||||
{'id': 162805, 'data_set_name': '可以使用:mdl230_totalcap_cusip_p50_200ratio', 'description': "不可使用,仅供参考:It is defined as the moving average of a stock's prices in last 50 days divided by the moving average of its prices in last 200 days."} |
||||
{'id': 325355, 'data_set_name': '可以使用:pv87_v2_weightedavg20_group_css_insider_trading', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Insider Trading'} |
||||
{'id': 85980, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_ebitda_growth', 'description': '不可使用,仅供参考:Percentage change in earnings before interest, taxes, depreciation, and amortization from last year to the current year'} |
||||
{'id': 6493, 'data_set_name': '可以使用:forecasted_value_dividend_per_share', 'description': '不可使用,仅供参考:Forecasted value for dividend per share for the specified period.'} |
||||
{'id': 319801, 'data_set_name': '可以使用:pv87_2_dps_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Dividends Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 295591, 'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w4_pca_fact2_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 2nd eigenvalue of PCA into 5 groups.'} |
||||
{'id': 159777, 'data_set_name': '可以使用:fnd65_allcap_sedol_irttmsalesev', 'description': "不可使用,仅供参考:It is defined as a stock's trailing 12 month sales-to-enterprise (SEV) value less the average of the SEVs of all stocks in the same industry deflated by the standard deviation of the SEVs of all stocks in the same relative universe."} |
||||
{'id': 168257, 'data_set_name': '可以使用:mdl354_sector_pt2sale_sur', 'description': '不可使用,仅供参考:Revenue surprise (vs consensus)'} |
||||
{'id': 323015, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_z_range', 'description': '不可使用,仅供参考:14-day Volume weighted average of Range of Sentiment'} |
||||
{'id': 323676, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_sent_z_range', 'description': '不可使用,仅供参考:28-day Volume weighted average of Range of Sentiment'} |
||||
{'id': 6683, 'data_set_name': '可以使用:relative_index_return_percentage', 'description': '不可使用,仅供参考:Difference in return percentage between the idea and the index.'} |
||||
{'id': 321436, 'data_set_name': '可以使用:pv87_daily_qtr_matrix_r6_book_value_share_consensus_mean_numdownunfiltered', 'description': '不可使用,仅供参考:Number of down revisions (unfiltered) of Book Value / Share Consensus Mean'} |
||||
{'id': 323309, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_matrix_vol_vol_std_tsrank', 'description': '不可使用,仅供参考:End-of-day time series rank of Volume Standard deviation'} |
||||
{'id': 324833, 'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oiivcall7', 'description': '不可使用,仅供参考:implied volatility of near out call options'} |
||||
{'id': 319083, 'data_set_name': '可以使用:pv52_asdaq_bx_atquote_shares', 'description': '不可使用,仅供参考:At-the Quote Shares'} |
||||
{'id': 316919, 'data_set_name': '可以使用:pv173_ranksmt5yzspreadchgstd20dsbst_200', 'description': '不可使用,仅供参考:It is defined as the 20-day standard deviation of changeIn 5-year mid z-spreadIn the bond z-spread curve'} |
||||
{'id': 84110, 'data_set_name': '可以使用:quarterly_property_plant_equipment_total', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Property, Plant & Equipment'} |
||||
{'id': 170443, 'data_set_name': '可以使用:mdl77_2earningsqualityfactor_epschgetr', 'description': '不可使用,仅供参考:EPS from Change in Effective Tax Rate: It is defined as the trailing 12-month pre-tax income per share times the difference between most recent trailing 12-month effective tax rate and that of 4 quarters ago. The effective tax rate is defined as total tax expense divided by pre-tax income.'} |
||||
{'id': 324229, 'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_event_sentiment_score_labor_issues', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Labor Issues'} |
||||
{'id': 295598, 'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w5_pca_fact1_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 1st eigenvalue of PCA into 10 groups.'} |
||||
{'id': 169384, 'data_set_name': '可以使用:mdl177_2_pricemomemtummodel_relpricestrength_', 'description': "不可使用,仅供参考:Industry-adjusted 12-month Relative Price Strength : It is defined as a stock's 12-month relative price-stength (PS) minus the PSs of all stocks in the same industry deflated by the standard deviation of these PSs."} |
||||
{'id': 320314, 'data_set_name': '可以使用:pv87_2_netdebt_qf_matrix_p1_b_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 319215, 'data_set_name': '可以使用:pv52_yse_national_price_imprvd_shares', 'description': '不可使用,仅供参考:Price-Improved Shares'} |
||||
{'id': 735, 'data_set_name': '可以使用:anl10_netpast_det_excflag_1170', 'description': '不可使用,仅供参考:Exclusion flag for net income estimates'} |
||||
{'id': 168878, 'data_set_name': '可以使用:mdl177_2_earningsqualityfactor_indrelrecd_', 'description': "不可使用,仅供参考:Industry-adjusted Doubtful Account Receivables : It is defined as a stock's asset-adjusted annual doubtful receivables minus the average of the receivables of all stocks in the same industry deflated by the standard deviation of these receivables."} |
||||
{'id': 171347, 'data_set_name': '可以使用:mdl77_historicalgrowthfactor_y3fcq4rqsr', 'description': '不可使用,仅供参考:R-Sqr of 3-yr TTM Cash Flow Trend Line: It is defined as the conditional square of the correlation between monthly dates and the corresponding trailing 12-month cash flow per share in the prior 12 quarters.'} |
||||
{'id': 321093, 'data_set_name': '可以使用:pv87_cash_from_operations_actual', 'description': '不可使用,仅供参考:Cash From Operations Actual'} |
||||
{'id': 295490, 'data_set_name': '可以使用:oth455_customer_roam_w1_pca_fact1_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using the 1st eigenvalue of PCA into 10 groups.'} |
||||
{'id': 295734, 'data_set_name': '可以使用:oth455_partner_n2v_p50_q50_w1_pca_fact2_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 2nd eigenvalue of PCA into 20 groups.'} |
||||
{'id': 323245, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_matrix_sent_sent_mean_tsrank', 'description': '不可使用,仅供参考:End-of-day time series rank of Sentiment Average'} |
||||
{'id': 6786, 'data_set_name': '可以使用:anl49_backfill_3rdfiscalquartersalesorrevenuesindicator', 'description': '不可使用,仅供参考:Third fiscal quarter sales or revenues indicator'} |
||||
{'id': 324251, 'data_set_name': '可以使用:pv87_prv2_weightedavg20_topic_nip_business', 'description': '不可使用,仅供参考:20-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for topic Business'} |
||||
{'id': 324247, 'data_set_name': '可以使用:pv87_prv2_weightedavg20_topic_css_business', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for topic Business'} |
||||
{'id': 295309, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q50_w1_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 5 groups.'} |
||||
{'id': 9830, 'data_set_name': '可以使用:retail_cli_score_qa', 'description': '不可使用,仅供参考:Coleman–Liau Index (CLI) for retail investors in Q&A section.'} |
||||
{'id': 295499, 'data_set_name': '可以使用:oth455_customer_roam_w2_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using K-means into 10 groups.'} |
||||
{'id': 318595, 'data_set_name': '可以使用:principal_component_score_9_top3000_v2', 'description': '不可使用,仅供参考:Ninth principal component value for the top 3000 securities (variant 2).'} |
||||
{'id': 85774, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_cash_ratio', 'description': "不可使用,仅供参考:Ratio which indicates a company's liquidity"} |
||||
{'id': 169324, 'data_set_name': '可以使用:mdl177_2_managementqualityfactor_fixastto', 'description': '不可使用,仅供参考:The trailing 12-month sales divided by the average of the total fixed assets in the same period.'} |
||||
{'id': 323060, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted28d_ew_sent_mean_deviation', 'description': '不可使用,仅供参考:28-day Volume weighted average of Deviation of Sentiment Average'} |
||||
{'id': 78927, 'data_set_name': '可以使用:fn_allocated_share_based_compensation_expense_a', 'description': '不可使用,仅供参考:Represents the expense recognized during the period arising from equity-based compensation arrangements (for example, shares of stock, unit, stock options or other equity instruments) with employees, directors and certain consultants qualifying for treatment as employees.'} |
||||
{'id': 83566, 'data_set_name': '可以使用:fnd3_a_sharesauthorized', 'description': '不可使用,仅供参考:Annual Shares Authorized'} |
||||
{'id': 296409, 'data_set_name': '可以使用:oth567score_mentorship', 'description': '不可使用,仅供参考:Mentorship score'} |
||||
{'id': 325993, 'data_set_name': '可以使用:pv87_webv2_simpleavg60_group_event_sentiment_score_insider_trading', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for group Insider Trading'} |
||||
{'id': 295585, 'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w4_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 5 groups.'} |
||||
{'id': 319811, 'data_set_name': '可以使用:pv87_2_dps_qf_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Dividends Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 168881, 'data_set_name': '可以使用:mdl177_2_earningsqualityfactor_saleeps', 'description': '不可使用,仅供参考:Change in TTM Sales vsEPS : It is defined as the absolute value of the difference between the yearly percent change in trailing 12-month sales per share and the yearly percent change in trailing 12-month diluted earnings per share before extraordinary items.'} |
||||
{'id': 323165, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_sent_deviation', 'description': '不可使用,仅供参考:7-day Volume weighted average of Deviation of Sentiment'} |
||||
{'id': 295306, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w5_pca_fact3_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 5 groups.'} |
||||
{'id': 323608, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_sent_z_tsrank', 'description': '不可使用,仅供参考:14-day Volume weighted average of End-of-day time series rank of Sentiment'} |
||||
{'id': 163832, 'data_set_name': '可以使用:mdl26_rm03_nly_rvs_d_fy1_rnd_30', 'description': '不可使用,仅供参考:number of analysts revising down FYEAR1 earnings: 30 days'} |
||||
{'id': 171113, 'data_set_name': '可以使用:mdl77_curratio', 'description': '不可使用,仅供参考:Current Ratio: It is defined as the reported current assets from most recent quarter divided by the current liabilities from most recent quarter.'} |
||||
{'id': 278854, 'data_set_name': '可以使用:rp_nip_partner', 'description': '不可使用,仅供参考:News impact projection of partnership news'} |
||||
{'id': 323356, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple14d_ew_sent_z_tsrank', 'description': '不可使用,仅供参考:14-day Simple average of End-of-day time series rank of Sentiment'} |
||||
{'id': 324731, 'data_set_name': '可以使用:pv87_scores_uncertaintynormscr_median', 'description': '不可使用,仅供参考:Median of Uncertainity score'} |
||||
{'id': 383398, 'data_set_name': '可以使用:electric_utilities_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the electric utilities sector factor.'} |
||||
{'id': 295446, 'data_set_name': '可以使用:oth455_customer_n2v_p50_q50_w2_pca_fact2_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 20 groups.'} |
||||
{'id': 324864, 'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetacall0', 'description': '不可使用,仅供参考:theta of all call options'} |
||||
{'id': 295561, 'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w2_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 5 groups.'} |
||||
{'id': 295772, 'data_set_name': '可以使用:oth455_partner_n2v_p50_q50_w4_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'id': 318817, 'data_set_name': '可以使用:top2000_factor1_group20_score', 'description': '不可使用,仅供参考:First factor score for top 2000 securities, grouped into 20 clusters.'} |
||||
{'id': 320724, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Sales'} |
||||
{'id': 296414, 'data_set_name': '可以使用:oth567score_perks_309', 'description': '不可使用,仅供参考:Score for perks'} |
||||
{'id': 320646, 'data_set_name': '可以使用:pv87_2_roe_af_matrix_p1_b_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Return On Equity *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 319871, 'data_set_name': '可以使用:pv87_2_ebit_qf_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of EBIT *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 169286, 'data_set_name': '可以使用:mdl177_2_liquidityriskfactor_ocfratio', 'description': "不可使用,仅供参考:Operating Cash Flow Ratio : It is defined as a stock's most recently reported quarterly cash flow from operations divided by its current liabilities."} |
||||
{'id': 166986, 'data_set_name': '可以使用:mdl264_sector_rank_l3', 'description': "不可使用,仅供参考:The probability that the future trend of 'Sector ranking' will move up"} |
||||
{'id': 320732, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_all_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 322615, 'data_set_name': '可以使用:pv87_matrix_nonperiodic_eps_lt_growth_consensus_mean_numdown', 'description': '不可使用,仅供参考:Number of down revisions of EPS LT Growth Consensus Mean (%)'} |
||||
{'id': 83328, 'data_set_name': '可以使用:fnd3_Q_comstk_divpershare', 'description': '不可使用,仅供参考:Quarterly Common Stock Dividends Per Share'} |
||||
{'id': 161668, 'data_set_name': '可以使用:fscore_momentum', 'description': '不可使用,仅供参考:The purpose of this metric is to identify stocks which are currently undergoing either up or downward analyst revisions.'} |
||||
{'id': 326024, 'data_set_name': '可以使用:pv87_webv2_simpleavg60_topic_event_sentiment_score_all', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for topic All'} |
||||
{'id': 170766, 'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_pfcfghc', 'description': '不可使用,仅供参考:The difference between the trailing 12-month free cash flow per share and that of 4 quarters ago for a stock divided by its trading price.'} |
||||
{'id': 174439, 'data_set_name': '可以使用:oth460_power_rank_l2', 'description': '不可使用,仅供参考:The probability that the future trend of Overall Ranking" will be neutral"'} |
||||
{'id': 325379, 'data_set_name': '可以使用:pv87_v2_weightedavg20_group_event_sentiment_score_marketing', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Marketing'} |
||||
{'id': 5690, 'data_set_name': '可以使用:sales_estimate_median_quarterly', 'description': '不可使用,仅供参考:Sales - median of estimations'} |
||||
{'id': 84157, 'data_set_name': '可以使用:unearned_revenue_total_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Deferred Revenue'} |
||||
{'id': 6004, 'data_set_name': '可以使用:anl44_best_sales_hi', 'description': '不可使用,仅供参考:best sales hi'} |
||||
{'id': 324599, 'data_set_name': '可以使用:pv87_revenue_actual_scale', 'description': '不可使用,仅供参考:Scale of Revenue Actual'} |
||||
{'id': 322494, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volvegacallmput2', 'description': '不可使用,仅供参考:Weighted average Vega for near out-of-the-money and in-the-money call and put options with volume used as weight factor'} |
||||
{'id': 324233, 'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_event_sentiment_score_revenues', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Revenues'} |
||||
{'id': 295251, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w1_pca_fact1_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 1st eigenvalue of PCA into 20 groups.'} |
||||
{'id': 319918, 'data_set_name': '可以使用:pv87_2_ebitda_qf_matrix_p1_b_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of EBITDA *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 320361, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 80735, 'data_set_name': '可以使用:share_capital_extraordinary', 'description': '不可使用,仅供参考:Extraordinary share capital reported for the annual period.'} |
||||
{'id': 318291, 'data_set_name': '可以使用:fin_nonreit_method4_group10_score', 'description': '不可使用,仅供参考:Score from the fourth method for financial sector excluding REITs, grouped into 10 clusters.'} |
||||
{'id': 168785, 'data_set_name': '可以使用:latin_america_sales_exposure', 'description': '不可使用,仅供参考:Latin America Sales Exposure'} |
||||
{'id': 170770, 'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_pfcoy3ghc', 'description': '不可使用,仅供参考:The difference between the trailing 12-month operating cash flow per share and that of 12 quarters ago for a stock divided by its trading price.'} |
||||
{'id': 295518, 'data_set_name': '可以使用:oth455_customer_roam_w3_pca_fact2_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using the 2nd eigenvalue of PCA into 20 groups.'} |
||||
{'id': 170449, 'data_set_name': '可以使用:mdl77_2earningsqualityfactor_rau', 'description': "不可使用,仅供参考:Unexpected Change in Accounts Receivable: It is defined as the difference between current accounts receivable and the expected level of accounts receivable (multiplying the prior year's closing account balance by the growth in sales in the trailing 12 months) scaled by the total assets."} |
||||
{'id': 319767, 'data_set_name': '可以使用:pv87_2_cfps_qf_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 323034, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_sent_std', 'description': '不可使用,仅供参考:14-day Volume weighted average of Standard deviation of Sentiment'} |
||||
{'id': 383418, 'data_set_name': '可以使用:net_retail_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the net retail sector factor.'} |
||||
{'id': 158370, 'data_set_name': '可以使用:insd3_holding_holding_share', 'description': '不可使用,仅供参考:Holding Holding Share'} |
||||
{'id': 324917, 'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oivegacallmput5', 'description': '不可使用,仅供参考:vega of in call minus put options'} |
||||
{'id': 81022, 'data_set_name': '可以使用:fnd28_annualforeign_value_08706a', 'description': '不可使用,仅供参考:value of annual field: Foreign Asset Turnover'} |
||||
{'id': 79011, 'data_set_name': '可以使用:fn_eff_income_tax_rate_continuing_operations_a', 'description': '不可使用,仅供参考:Percentage of current income tax expense (benefit) and deferred income tax expense (benefit) pertaining to continuing operations.'} |
||||
{'id': 324097, 'data_set_name': '可以使用:pv87_prv2_simpleavg1_group_event_sentiment_score_dividends', 'description': '不可使用,仅供参考:1-day Simple average of Event Sentiment Score for group Dividends'} |
||||
{'id': 279118, 'data_set_name': '可以使用:streetevents2_expiration_time_fast_d1', 'description': '不可使用,仅供参考:The time of day when the event or record in StreetEvents2 expires.'} |
||||
{'id': 320228, 'data_set_name': '可以使用:pv87_2_nav_qf_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 10435, 'data_set_name': '可以使用:mws87_confcallpart_sent_score_qa', 'description': '不可使用,仅供参考:The sentiment score of conference call participants in Q&A'} |
||||
{'id': 320612, 'data_set_name': '可以使用:pv87_2_roa_qf_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Return On Assets *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 324310, 'data_set_name': '可以使用:pv87_qtr_matrix_book_value_share_consensus_mean_numupunfiltered', 'description': '不可使用,仅供参考:Number of up revisions of Book Value / Share Consensus Mean'} |
||||
{'id': 326035, 'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_css_dividends', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Dividends'} |
||||
{'id': 295700, 'data_set_name': '可以使用:oth455_partner_n2v_p50_q200_w3_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'id': 81058, 'data_set_name': '可以使用:fnd28_annualgrowth_value_08650a', 'description': '不可使用,仅供参考:value of annual field: Operating Income - 5 Yr Annual Growth'} |
||||
{'id': 169232, 'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_slope4qsales3y', 'description': '不可使用,仅供参考:Slope of 3-yr TTM Sales Trend Line'} |
||||
{'id': 322418, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volivcallmput2', 'description': '不可使用,仅供参考:Weighted average Implied volatility for near out-of-the-money and in-the-money call and put options with volume used as weight factor'} |
||||
{'id': 325881, 'data_set_name': '可以使用:pv87_webv2_simpleavg1_group_event_sentiment_score_labor_issues', 'description': '不可使用,仅供参考:1-day Simple average of Event Sentiment Score for group Labor Issues'} |
||||
{'id': 168789, 'data_set_name': '可以使用:long_term_growth_estimate_2', 'description': '不可使用,仅供参考:Long-Term Growth Rate Estimates'} |
||||
{'id': 160910, 'data_set_name': '可以使用:mdl109_log_sale', 'description': '不可使用,仅供参考:Log of revenue'} |
||||
{'id': 326048, 'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_event_sentiment_score_all', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group All'} |
||||
{'id': 318185, 'data_set_name': '可以使用:basicmat_method2_group2_score', 'description': '不可使用,仅供参考:Score from the second method for basic materials sector, grouped into 2 clusters.'} |
||||
{'id': 324683, 'data_set_name': '可以使用:pv87_scores_fin_upmdown_normscr_median', 'description': '不可使用,仅供参考:Median of Financial up minus down score'} |
||||
{'id': 169494, 'data_set_name': '可以使用:mdl177_2_valueanalystmodel_qva_alertrank', 'description': '不可使用,仅供参考:Alert Rank'} |
||||
{'id': 169886, 'data_set_name': '可以使用:mdl177_historicalgrowthfactor_pctchgocf_alt', 'description': "不可使用,仅供参考:1-yr Growth in TTM Oper Cash Flow : It is defined as the percent change of a stock's most recent trailing 12-month operating cash flow per share (OCF) as compared to the OCF 4 quarters ago."} |
||||
{'id': 323962, 'data_set_name': '可以使用:pv87_pos_earnings_matrix_event_sentiment_score_mean', 'description': '不可使用,仅供参考:Mean of Event Sentiment Score for type Posearnings'} |
||||
{'id': 322264, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oiivcallmput0', 'description': '不可使用,仅供参考:Weighted average Implied volatility for all call and put options with open interest used as weight factor'} |
||||
{'id': 170513, 'data_set_name': '可以使用:mdl77_2gdna_cashratio', 'description': '不可使用,仅供参考:Cash & Equivalents-to-Current Liabilities: It is defined as the most recently reported quarterly cash & equivalents divided by current liabilities.'} |
||||
{'id': 295254, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w1_pca_fact2_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 20 groups.'} |
||||
{'id': 321183, 'data_set_name': '可以使用:pv87_daily_ann_matrix_r1_capital_expenditure_consensus_mean_numup', 'description': '不可使用,仅供参考:Number of up revisions of Capital Expenditure Consensus Mean'} |
||||
{'id': 86380, 'data_set_name': '可以使用:fnd72_q2_reinvest_earn_to_net_sales', 'description': '不可使用,仅供参考:Reinvested earnings as a percentage of revenue'} |
||||
{'id': 170442, 'data_set_name': '可以使用:mdl77_2earningsqualityfactor_dpcapex', 'description': '不可使用,仅供参考:Change in TTM Depreciation vs CapEx: It is defined as the absolute value of the difference between the yearly percent change in trailing 12-month depreciation expense and the yearly percent change in trailing 12-month capital expenditure.'} |
||||
{'id': 159826, 'data_set_name': '可以使用:fnd65_allcap_sedol_p50_200ratio', 'description': "不可使用,仅供参考:It is defined as the moving average of a stock's prices in last 50 days divided by the moving average of its prices in last 200 days."} |
||||
{'id': 174681, 'data_set_name': '可以使用:oth460_share_chg_l1', 'description': '不可使用,仅供参考:The probability that the future trend of YoY change in share count" will fall"'} |
||||
{'id': 319502, 'data_set_name': '可以使用:pv7_superrelation_sec_all_score_float', 'description': '不可使用,仅供参考:Float number of relation scores from SEC report, with backfill'} |
||||
{'id': 324217, 'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_css_investor_relations', 'description': '不可使用,仅供参考:20-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Investor Relations'} |
||||
{'id': 86844, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_oper_inc_growth', 'description': '不可使用,仅供参考:A percentage increase or decrease of operating income by comparing the current period with the same period prior year'} |
||||
{'id': 323004, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_ew_sent_std_std', 'description': '不可使用,仅供参考:14-day Volume weighted average of Standard deviation of Sentiment Standard deviation'} |
||||
{'id': 325899, 'data_set_name': '可以使用:pv87_webv2_simpleavg1_group_nip_partnerships', 'description': '不可使用,仅供参考:1-day Simple average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Partnerships'} |
||||
{'id': 158745, 'data_set_name': '可以使用:inst6_value_of_institutional_shares_sold', 'description': '不可使用,仅供参考:Aggregate dollar value of shares sold by institutions'} |
||||
{'id': 295824, 'data_set_name': '可以使用:oth455_partner_roam_w4_kmeans_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using K-means into 20 groups.'} |
||||
{'id': 86386, 'data_set_name': '可以使用:fnd72_q2_retention_ratio', 'description': '不可使用,仅供参考:Proportion of earnings kept back in the business as retained earnings'} |
||||
{'id': 84022, 'data_set_name': '可以使用:quarterly_authorized_shares_count', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Shares Authorized'} |
||||
{'id': 167922, 'data_set_name': '可以使用:regional_momentum_rank_float', 'description': "不可使用,仅供参考:Numeric rank showing a security's momentum relative to others in the same region."} |
||||
{'id': 1356, 'data_set_name': '可以使用:environmental_corr_weighted_sector_position', 'description': '不可使用,仅供参考:Company’s position within its sector based on environmental score weighted by KPIs most correlated to financial returns.'} |
||||
{'id': 295846, 'data_set_name': '可以使用:oth455_partner_roam_w5_pca_fact3_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using the 3rd eigenvalue of PCA into 5 groups.'} |
||||
{'id': 319779, 'data_set_name': '可以使用:pv87_2_csh_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Common Shares *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 318908, 'data_set_name': '可以使用:top300_factor2_group50_score', 'description': '不可使用,仅供参考:Second factor score for top 300 securities, grouped into 50 clusters.'} |
||||
{'id': 319003, 'data_set_name': '可以使用:pv48_dynamic_shares_cur', 'description': '不可使用,仅供参考:Current shares for dynamic index.'} |
||||
{'id': 83168, 'data_set_name': '可以使用:current_unearned_revenue_balance_acctadj', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Deferred Revenue, Current'} |
||||
{'id': 81285, 'data_set_name': '可以使用:fnd28_growthratesa_value_08636a', 'description': '不可使用,仅供参考:value of annual field: Net Income Growth'} |
||||
{'id': 171414, 'data_set_name': '可以使用:mdl77_liquidityriskfactor_si_ratio', 'description': '不可使用,仅供参考:Short Interest Ratio: It is defined as the number of shares sold short divided by the average daily trading volume of the stock over the last 30 trading days.'} |
||||
{'id': 325518, 'data_set_name': '可以使用:pv87_v2item_indrank_item_6030_215', 'description': '不可使用,仅供参考:Industry ranked item score for item 215 in topic Board Structure'} |
||||
{'id': 169928, 'data_set_name': '可以使用:mdl177_historicalgrowthmodel_hgm_composite', 'description': '不可使用,仅供参考:Historical Growth Composite'} |
||||
{'id': 161675, 'data_set_name': '可以使用:growth_potential_rank_derivative', 'description': '不可使用,仅供参考:Change in ranking for medium-term growth potential compared to previous period.'} |
||||
{'id': 319881, 'data_set_name': '可以使用:pv87_2_ebitda_af_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of EBITDA *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 320457, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 323619, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_ew_sent_mean_trend2', 'description': '不可使用,仅供参考:28-day Volume weighted average of Trend of Sentiment Average'} |
||||
{'id': 324925, 'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oivegacallmputs5', 'description': '不可使用,仅供参考:vega of in call minus put options with the same strike prices, which are in the money'} |
||||
{'id': 322421, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volivcallmput5', 'description': '不可使用,仅供参考:Weighted average Implied volatility for in-the-money call and put options with volume used as weight factor'} |
||||
{'id': 158389, 'data_set_name': '可以使用:insd3_whalewisdom_shares', 'description': '不可使用,仅供参考:Whale Wisdom Shares'} |
||||
{'id': 325695, 'data_set_name': '可以使用:pv87_web_weightedavg1_group_v2_0_1_css_earnings', 'description': '不可使用,仅供参考:1-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Earnings'} |
||||
{'id': 324540, 'data_set_name': '可以使用:pv87_qtr_matrix_revenue_consensus_mean_numup', 'description': '不可使用,仅供参考:Number of up revisions of Revenue Consensus Mean'} |
||||
{'id': 321191, 'data_set_name': '可以使用:pv87_daily_ann_matrix_r1_cash_flow_share_consensus_mean_numup', 'description': '不可使用,仅供参考:Number of up revisions of Cash Flow / Share Consensus Mean'} |
||||
{'id': 169919, 'data_set_name': '可以使用:mdl177_historicalgrowthfactor_slope4qsales3y', 'description': '不可使用,仅供参考:Slope of 3-yr TTM Sales Trend Line'} |
||||
{'id': 323138, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_ew_sent_mean_trend2', 'description': '不可使用,仅供参考:7-day Volume weighted average of Trend of Sentiment Average'} |
||||
{'id': 323512, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_simple7d_sent_mean_tsrank', 'description': '不可使用,仅供参考:End-of-day time series rank of Sentiment Average'} |
||||
{'id': 168590, 'data_set_name': '可以使用:global_value_momentum_rank', 'description': "不可使用,仅供参考:Global-relative ranking of a security's value-momentum score."} |
||||
{'id': 278973, 'data_set_name': '可以使用:info10_tone_score_simple_fast_d1', 'description': '不可使用,仅供参考:Overall sentiment score for the event transcript or story in the info10 module (simple version).'} |
||||
{'id': 7300, 'data_set_name': '可以使用:anl69_country', 'description': '不可使用,仅供参考:Country'} |
||||
{'id': 6508, 'data_set_name': '可以使用:latest_annual_period_end_update_dividend_per_share', 'description': '不可使用,仅供参考:Date or timestamp when the annual period end for dividend per share was last updated.'} |
||||
{'id': 325388, 'data_set_name': '可以使用:pv87_v2_weightedavg20_group_nip_analyst_ratings', 'description': '不可使用,仅供参考:20-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Analyst Ratings'} |
||||
{'id': 169458, 'data_set_name': '可以使用:mdl177_2_sensitivityfactor400_apsales', 'description': '不可使用,仅供参考:Asia-Pacific Sales Exposure'} |
||||
{'id': 169307, 'data_set_name': '可以使用:mdl177_2_managementqualityfactor_capacq', 'description': '不可使用,仅供参考:Capital Acquisition Ratio'} |
||||
{'id': 383430, 'data_set_name': '可以使用:road_rail_transport_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the road and rail transportation sector factor.'} |
||||
{'id': 279111, 'data_set_name': '可以使用:se_score', 'description': '不可使用,仅供参考:(number of positive words - number of negative words)/(number of positive words + number of negative words)'} |
||||
{'id': 169901, 'data_set_name': '可以使用:mdl177_historicalgrowthfactor_rsqr4qsales3y', 'description': '不可使用,仅供参考:R-Sqr of 3-yr TTM Sales Trend Line'} |
||||
{'id': 319965, 'data_set_name': '可以使用:pv87_2_ebitdaps_qf_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of EBITDA per share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 174076, 'data_set_name': '可以使用:oth460_erlanger_option_rank_l1', 'description': '不可使用,仅供参考:The probability that the future trend of Option Rank" will be fall"'} |
||||
{'id': 171434, 'data_set_name': '可以使用:mdl77_momemtumanalystmodel_qma_eplinkage', 'description': '不可使用,仅供参考:The equal-weighted average of the Change in Free Cash Flow Rank, the Industry Relative 3-Month Return Rank, the Market Earnings Response Rank, and the Change in Net Working Capital Rank.'} |
||||
{'id': 165223, 'data_set_name': '可以使用:mdl262_saleq_profitability_profitability1', 'description': '不可使用,仅供参考:1st profitability field of Sales/Turnover (Net)'} |
||||
{'id': 78757, 'data_set_name': '可以使用:fnd17_qpayratio', 'description': '不可使用,仅供参考:Payout ratio - most recent quarter'} |
||||
{'id': 319044, 'data_set_name': '可以使用:pv48_ru3000_constituent_sharesout', 'description': '不可使用,仅供参考:ru3000 constituent sharesout related to the US 3000 constituent index.'} |
||||
{'id': 325193, 'data_set_name': '可以使用:pv87_v2_expavg60_group_nip_partnerships', 'description': '不可使用,仅供参考:60-day Exponential average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Partnerships'} |
||||
{'id': 322359, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oivegaput1', 'description': '不可使用,仅供参考:Weighted average Vega for near in-the-money and out-of-the-money put options with open interest used as weight factor'} |
||||
{'id': 295383, 'data_set_name': '可以使用:oth455_customer_n2v_p50_q200_w2_pca_fact1_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 1st eigenvalue of PCA into 20 groups.'} |
||||
{'id': 319741, 'data_set_name': '可以使用:pv87_2_cfps_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 5964, 'data_set_name': '可以使用:anl44_best_opp_to_sales', 'description': '不可使用,仅供参考:best opp to sales'} |
||||
{'id': 169348, 'data_set_name': '可以使用:mdl177_2_managementqualityfactor_rdsale', 'description': '不可使用,仅供参考:R&D Intensity : It is defined as the average of the research & development expenses in the trailing 12-months deflated by the sum of total sales in the same period.'} |
||||
{'id': 295580, 'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w3_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'id': 323191, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_sent_z_daydiff', 'description': '不可使用,仅供参考:7-day Volume weighted average of Daily difference of Sentiment'} |
||||
{'id': 86383, 'data_set_name': '可以使用:fnd72_q2_rel_pe_ratio', 'description': "不可使用,仅供参考:Relative Price/Earnings is a stock's Price/Earnings ratio relative to the Price/Earnings ratio of a relevant index"} |
||||
{'id': 321616, 'data_set_name': '可以使用:pv87_dividends_matrix_event_sentiment_score_mean', 'description': '不可使用,仅供参考:Mean of Event Sentiment Score for type Dividends'} |
||||
{'id': 320656, 'data_set_name': '可以使用:pv87_2_roe_af_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Return On Equity *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 160469, 'data_set_name': '可以使用:fnd65_us5000_cusip_curratio', 'description': '不可使用,仅供参考:It is defined as the reported current assets from most recent quarter divided by the current liabilities from most recent quarter.'} |
||||
{'id': 322220, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oigammacall4', 'description': '不可使用,仅供参考:Weighted average Gamma for near-the-money call options with open interest used as weight factor'} |
||||
{'id': 9508, 'data_set_name': '可以使用:anl83_analyst_sent_score_qa', 'description': '不可使用,仅供参考:The Sentiment Score of Sell Side Analysts in Q_A'} |
||||
{'id': 171104, 'data_set_name': '可以使用:mdl77_aspanratio', 'description': "不可使用,仅供参考:Stock's quarterly operating assets minus its operating liabilities deflated by the lagged total assets"} |
||||
{'id': 973, 'data_set_name': '可以使用:anl10_sal_newpast_det_estflag', 'description': '不可使用,仅供参考:Estimate flag for sales'} |
||||
{'id': 170782, 'data_set_name': '可以使用:mdl77_2historicalgrowthfactor_slope4qfcf3y', 'description': '不可使用,仅供参考:Slope of 3-yr TTM Free Cash Flow Trend Line: It is defined as the slope coefficient between monthly dates and the corresponding trailing 12-month free cash flow per share in the prior 12 quarters.'} |
||||
{'id': 322271, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oiivcallmput7', 'description': '不可使用,仅供参考:Weighted average Implied volatility for near out-of-the-money call and put options with open interest used as weight factor'} |
||||
{'id': 83624, 'data_set_name': '可以使用:fnd3_aacctadj_costofrevenue', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Cost of Revenue'} |
||||
{'id': 295349, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q50_w4_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'id': 324882, 'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetacallmput8', 'description': '不可使用,仅供参考:theta of near in call minus put options'} |
||||
{'id': 279613, 'data_set_name': '可以使用:composite_story_sentiment_score_2', 'description': '不可使用,仅供参考:Combined sentiment score for a news story using multiple analysis techniques.'} |
||||
{'id': 321313, 'data_set_name': '可以使用:pv87_daily_matrix_nonperiodic_eps_lt_growth_consensus_mean_numanalysts', 'description': '不可使用,仅供参考:Number of analysts of EPS LT Growth Consensus Mean (%)'} |
||||
{'id': 169325, 'data_set_name': '可以使用:mdl177_2_managementqualityfactor_fwdroe', 'description': '不可使用,仅供参考:Forward Return on Equity'} |
||||
{'id': 168332, 'data_set_name': '可以使用:credit_risk_sector_percentile_score_2', 'description': '不可使用,仅供参考:Percentile rank of credit risk within the sector group (alternate source).'} |
||||
{'id': 322366, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oivegaput8', 'description': '不可使用,仅供参考:Weighted average Vega for near in-the-money put options with open interest used as weight factor'} |
||||
{'id': 324179, 'data_set_name': '可以使用:pv87_prv2_simpleavg60_group_event_sentiment_score_all', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for group All'} |
||||
{'id': 279765, 'data_set_name': '可以使用:industry_weight_alt_dmgrhchendtnret', 'description': '不可使用,仅供参考:The weight or importance assigned to a specific industry in the alternative module.'} |
||||
{'id': 164125, 'data_set_name': '可以使用:mdl26_v14_prsprise_fq1_revenue', 'description': '不可使用,仅供参考:predicted surprise (actual value - predicted value) FQTR1 revenue'} |
||||
{'id': 164197, 'data_set_name': '可以使用:mdl26_v14_smartestimate_fy1_revenue', 'description': '不可使用,仅供参考:smartestimate FYEAR1 revenue'} |
||||
{'id': 326072, 'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_nip_insider_trading', 'description': '不可使用,仅供参考:20-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Insider Trading'} |
||||
{'id': 318912, 'data_set_name': '可以使用:top300_factor3_group2_score', 'description': '不可使用,仅供参考:Third factor score for top 300 securities, grouped into 2 clusters.'} |
||||
{'id': 320277, 'data_set_name': '可以使用:pv87_2_netdebt_af_matrix_p1_b_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 6476, 'data_set_name': '可以使用:forecast_currency_cash_flow_per_share_second', 'description': '不可使用,仅供参考:Currency in which the cash flow per share forecast is denominated in the second version module.'} |
||||
{'id': 323979, 'data_set_name': '可以使用:pv87_primary_eps_estimate_1_yr_quarterly_growth_scale', 'description': '不可使用,仅供参考:Scale of Primary EPS Estimate - 1 Yr Quarterly Growth %'} |
||||
{'id': 86958, 'data_set_name': '可以使用:fnd72_s_pit_or_is_a_is_foreign_crncy_trans_adj', 'description': '不可使用,仅供参考:Foreign Currency Translation Adjustment'} |
||||
{'id': 171310, 'data_set_name': '可以使用:mdl77_historicalgrowthfactor_pctchg3ycf', 'description': "不可使用,仅供参考:The percent change in a stock's most recent trailing 12-month cash flow per share as compared to itself 12 quarters ago."} |
||||
{'id': 324011, 'data_set_name': '可以使用:pv87_prv2_expavg20_group_event_sentiment_score_equity_actions', 'description': '不可使用,仅供参考:20-day Exponential average of Event Sentiment Score for group Equity Actions'} |
||||
{'id': 167823, 'data_set_name': '可以使用:mdl31_v14_ab1_bv_share_last_qtr', 'description': '不可使用,仅供参考:Last quarter book value per share'} |
||||
{'id': 169180, 'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_chg3ycfp', 'description': '不可使用,仅供参考:The difference between the the trailing 12-month cash flow per share and that of 12-quarter ago comparable trailing 12-month cash flow for a stock divided by its trading price.'} |
||||
{'id': 161555, 'data_set_name': '可以使用:mdl138_pdi3_sale', 'description': '不可使用,仅供参考:PDI-3 Factor based on Sales/Turnover'} |
||||
{'id': 163461, 'data_set_name': '可以使用:mdl26_arm_score_change_60', 'description': '不可使用,仅供参考:score change for days: 60'} |
||||
{'id': 295268, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w2_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'id': 81274, 'data_set_name': '可以使用:fnd28_growthratesa_value_08610a', 'description': '不可使用,仅供参考:value of annual field: Book Value Per Share - 5 Yr Annual Growth Profitability Annual Statistics'} |
||||
{'id': 323946, 'data_set_name': '可以使用:pv87_pos_analyst_matrix_event_sentiment_score_count', 'description': '不可使用,仅供参考:Count of Event Sentiment Score for type Posanalyst'} |
||||
{'id': 323045, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted14d_sent_trend2', 'description': '不可使用,仅供参考:14-day Volume weighted average of Trend of Sentiment'} |
||||
{'id': 85947, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_asset_growth', 'description': '不可使用,仅供参考:A percentage increase or decrease of total assets by comparing current period with same period prior year'} |
||||
{'id': 9480, 'data_set_name': '可以使用:analyst_dcs_score_presentation', 'description': '不可使用,仅供参考:Dale–Chall Score (DCS) for analysts in presentation section.'} |
||||
{'id': 323145, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_ew_sent_std_mean', 'description': '不可使用,仅供参考:7-day Volume weighted average of Average of Sentiment Standard deviation'} |
||||
{'id': 323061, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted28d_ew_sent_mean_mean', 'description': '不可使用,仅供参考:28-day Volume weighted average of Average of Sentiment Average'} |
||||
{'id': 324716, 'data_set_name': '可以使用:pv87_scores_negpartnormscr_median', 'description': '不可使用,仅供参考:Median of Negativity partial score'} |
||||
{'id': 318910, 'data_set_name': '可以使用:top300_factor3_group10_score', 'description': '不可使用,仅供参考:Third factor score for top 300 securities, grouped into 10 clusters.'} |
||||
{'id': 8967, 'data_set_name': '可以使用:growth', 'description': '不可使用,仅供参考:Historical 5-year growth'} |
||||
{'id': 295290, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w4_pca_fact2_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 20 groups.'} |
||||
{'id': 324654, 'data_set_name': '可以使用:pv87_sale_asset_fy1_mean', 'description': '不可使用,仅供参考:Asset turnover, FY1'} |
||||
{'id': 325099, 'data_set_name': '可以使用:pv87_v2_expavg20_group_event_sentiment_score_insider_trading', 'description': '不可使用,仅供参考:20-day Exponential average of Event Sentiment Score for group Insider Trading'} |
||||
{'id': 169329, 'data_set_name': '可以使用:mdl177_2_managementqualityfactor_min1ygrossmargin', 'description': '不可使用,仅供参考:1-Year Trough Gross Margin'} |
||||
{'id': 319976, 'data_set_name': '可以使用:pv87_2_ebitdaps_qf_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of EBITDA per share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 295553, 'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w1_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'id': 318768, 'data_set_name': '可以使用:technology_pca_factor2_grouping20', 'description': '不可使用,仅供参考:Second principal component grouping for technology sector with 20 clusters.'} |
||||
{'id': 318769, 'data_set_name': '可以使用:technology_pca_factor2_grouping5', 'description': '不可使用,仅供参考:Second principal component grouping for technology sector with 5 clusters.'} |
||||
{'id': 322297, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_oithetacall5', 'description': '不可使用,仅供参考:Weighted average Theta for in-the-money call options with open interest used as weight factor'} |
||||
{'id': 319708, 'data_set_name': '可以使用:pv87_2_capex_qf_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Capital Expenditure *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 1448, 'data_set_name': '可以使用:social_score_industry_position', 'description': '不可使用,仅供参考:Company’s position within industry peer group for social score.'} |
||||
{'id': 86868, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_revenue_per_sh', 'description': '不可使用,仅供参考:Ratio that computes the total revenue earned per share over the reporting period'} |
||||
{'id': 324892, 'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetaput0', 'description': '不可使用,仅供参考:theta of all put options'} |
||||
{'id': 168345, 'data_set_name': '可以使用:mdl37_bk_broker_research', 'description': "不可使用,仅供参考:The global 1-100 rank of a company's credit riskiness based on textual data in broker research documents"} |
||||
{'id': 319975, 'data_set_name': '可以使用:pv87_2_ebitdaps_qf_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of EBITDA per share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 160722, 'data_set_name': '可以使用:fnd65_us5000_cusip_slope4qsales3y', 'description': '不可使用,仅供参考:It is defined as the slope coefficient between monthly dates and the corresponding trailing 12-month sales per share in the prior 12 quarters.'} |
||||
{'id': 161467, 'data_set_name': '可以使用:percentage_volume_oscillator_5d', 'description': '不可使用,仅供参考:Percentage Volume Oscillator value over 5 days.'} |
||||
{'id': 171326, 'data_set_name': '可以使用:mdl77_historicalgrowthfactor_pfcy3ghc', 'description': '不可使用,仅供参考:The difference between the trailing 12-month cash flow per share and that of 12 quarters ago comparable trailing 12-month cash flow for a stock divided by its trading price.'} |
||||
{'id': 83167, 'data_set_name': '可以使用:current_unearned_revenue_balance', 'description': '不可使用,仅供参考:Amount of deferred revenue classified as current.'} |
||||
{'id': 168639, 'data_set_name': '可以使用:mdl44_previousscore', 'description': '不可使用,仅供参考:Company level participant score from previous week, null values are negative'} |
||||
{'id': 320082, 'data_set_name': '可以使用:pv87_2_fcfps_af_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Financing Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 324536, 'data_set_name': '可以使用:pv87_qtr_matrix_revenue_consensus_mean_numdown', 'description': '不可使用,仅供参考:Number of down revisions of Revenue Consensus Mean'} |
||||
{'id': 320216, 'data_set_name': '可以使用:pv87_2_nav_af_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 295469, 'data_set_name': '可以使用:oth455_customer_n2v_p50_q50_w4_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'id': 324329, 'data_set_name': '可以使用:pv87_qtr_matrix_cash_flow_share_consensus_mean_numdownunfiltered', 'description': '不可使用,仅供参考:Number of down revisions (unfiltered) of Cash Flow / Share Consensus Mean'} |
||||
{'id': 325883, 'data_set_name': '可以使用:pv87_webv2_simpleavg1_group_event_sentiment_score_partnerships', 'description': '不可使用,仅供参考:1-day Simple average of Event Sentiment Score for group Partnerships'} |
||||
{'id': 295798, 'data_set_name': '可以使用:oth455_partner_roam_w1_pca_fact3_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with partner data and then clustered using the 3rd eigenvalue of PCA into 5 groups.'} |
||||
{'id': 325722, 'data_set_name': '可以使用:pv87_web_weightedavg60_topic_css_business', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for topic Business'} |
||||
{'id': 169846, 'data_set_name': '可以使用:mdl177_historicalgrowthfactor_chgnpm_alt', 'description': '不可使用,仅供参考:1-Yr Change in Net Profit Margin : It is defined as the most recent quarterly net profit margin (NPM) minus the NPM 4 quarters agoNet profit margin is net income divided by total sales.'} |
||||
{'id': 160056, 'data_set_name': '可以使用:fnd65_totalcap_cusip_curratio', 'description': '不可使用,仅供参考:It is defined as the reported current assets from most recent quarter divided by the current liabilities from most recent quarter.'} |
||||
{'id': 295390, 'data_set_name': '可以使用:oth455_customer_n2v_p50_q200_w2_pca_fact3_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 5 groups.'} |
||||
{'id': 87585, 'data_set_name': '可以使用:fnd90_us_game_optimism_sale', 'description': '不可使用,仅供参考:Analyst Optimism Sales [ Descending] - [Quality.Profitability]'} |
||||
{'id': 324661, 'data_set_name': '可以使用:pv87_score_count', 'description': '不可使用,仅供参考:Count of Sentiment Score'} |
||||
{'id': 326181, 'data_set_name': '可以使用:pv87_weightedavg1_topic_ess_all', 'description': '不可使用,仅供参考:1-day Weighted average of ESS - Event Sentiment Score for topic All'} |
||||
{'id': 320849, 'data_set_name': '可以使用:pv87_ann_matrix_book_value_share_estimate_high', 'description': '不可使用,仅供参考:High of Book Value / Share Estimate'} |
||||
{'id': 6805, 'data_set_name': '可以使用:anl49_backfill_bookvaluepershare', 'description': '不可使用,仅供参考:Total assets minus liabilities, minus any equity issues that have a prior claim divided by the number of common shares outstanding at the fiscal year end.'} |
||||
{'id': 6715, 'data_set_name': '可以使用:treynor_performance_ratio', 'description': '不可使用,仅供参考:Risk-adjusted return measure relative to the risk-free rate.'} |
||||
{'id': 5593, 'data_set_name': '可以使用:max_shares_outstanding_guidance', 'description': '不可使用,仅供参考:The maximum guidance for Shares'} |
||||
{'id': 6895, 'data_set_name': '可以使用:anl49_cashflowpershare', 'description': '不可使用,仅供参考:Cash flow less preferred dividends (if any) divided by common shares outstanding at year end.'} |
||||
{'id': 169304, 'data_set_name': '可以使用:mdl177_2_managementqualityfactor_app', 'description': '不可使用,仅供参考:Average Payable Period : It is defined as the average of the trailing 12-month accounts payable times 365 divided by the trailing 12-month cost of goods sold.'} |
||||
{'id': 318577, 'data_set_name': '可以使用:principal_component_score_4_top500_513', 'description': '不可使用,仅供参考:Value of the 5th principal component for the top 500 securities in group 513.'} |
||||
{'id': 278491, 'data_set_name': '可以使用:news_ratio_vol', 'description': '不可使用,仅供参考:Curr_Vol / Mov_Vol'} |
||||
{'id': 319063, 'data_set_name': '可以使用:pv48_usa_russell_rgs_shares', 'description': '不可使用,仅供参考:No field description'} |
||||
{'id': 324853, 'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oiivcallmputs9', 'description': '不可使用,仅供参考:implied volatility of deep in call minus put options with the same strike prices, which are in the money'} |
||||
{'id': 171886, 'data_set_name': '可以使用:projected_two_year_eps_growth_2', 'description': '不可使用,仅供参考:2-Year Ahead EPS Growth'} |
||||
{'id': 322593, 'data_set_name': '可以使用:pv87_marketimpactscore_mean', 'description': '不可使用,仅供参考:Mean of Market impact score - The estimated risk-adjusted 1 minute forward return for a given article as measured by stock return minus the stock beta multiplied market return, -5 being most negative impact and +5 most positive'} |
||||
{'id': 1350, 'data_set_name': '可以使用:employee_training_subsector_percentile', 'description': '不可使用,仅供参考:Percentile ranking within subsector peer group for employee training, safety, and well-being.'} |
||||
{'id': 318963, 'data_set_name': '可以使用:utilities_method1_group5_score', 'description': '不可使用,仅供参考:Score from the first method for utilities sector, grouped into 5 clusters.'} |
||||
{'id': 168935, 'data_set_name': '可以使用:mdl177_2_globaldevnorthamerica_v502_cashratio', 'description': '不可使用,仅供参考:Cash & Equivalents-to-Current Liabilities : It is defined as the most recently reported quarterly cash & equivalents divided by current liabilities.'} |
||||
{'id': 167876, 'data_set_name': '可以使用:mdl31_v14_ab1_pricesales_current', 'description': '不可使用,仅供参考:Current price to sales ratio'} |
||||
{'id': 323543, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_ew_sent_mean_median', 'description': '不可使用,仅供参考:14-day Volume weighted average of Median of Sentiment Average'} |
||||
{'id': 279617, 'data_set_name': '可以使用:editorial_commentary_sentiment_score_2', 'description': '不可使用,仅供参考:Sentiment score for short commentary and editorials on equity markets.'} |
||||
{'id': 169872, 'data_set_name': '可以使用:mdl177_historicalgrowthfactor_pctchg3yeps_alt', 'description': "不可使用,仅供参考:The percent change in a stock's most recent trailing 12-month earnings per share as compared to itself 12 quarters ago."} |
||||
{'id': 169685, 'data_set_name': '可以使用:mdl177_earningsqualityfactor_salerec', 'description': '不可使用,仅供参考:Change in TTM Sales vsAccounts Receivable : It is defined as the difference between the yearly percent change in trailing 12-month sales and the yearly percent change in accounts receivable.'} |
||||
{'id': 323622, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_ew_sent_range', 'description': '不可使用,仅供参考:28-day Volume weighted average of Range of Sentiment'} |
||||
{'id': 167913, 'data_set_name': '可以使用:industry_momentum_score_float', 'description': '不可使用,仅供参考:Numeric value representing the momentum component based on industry-level returns.'} |
||||
{'id': 325331, 'data_set_name': '可以使用:pv87_v2_simpleavg60_group_nip_partnerships', 'description': '不可使用,仅供参考:60-day Simple average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Partnerships'} |
||||
{'id': 318816, 'data_set_name': '可以使用:top2000_factor1_group10_score', 'description': '不可使用,仅供参考:First factor score for top 2000 securities, grouped into 10 clusters.'} |
||||
{'id': 295527, 'data_set_name': '可以使用:oth455_customer_roam_w4_pca_fact1_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using the 1st eigenvalue of PCA into 20 groups.'} |
||||
{'id': 323576, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_sent_mean_daydiff', 'description': '不可使用,仅供参考:14-day Volume weighted average of Daily difference of Sentiment Average'} |
||||
{'id': 320370, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 163306, 'data_set_name': '可以使用:mdl230_us5000_cusip_salesurp', 'description': '不可使用,仅供参考:It is defined as the most recent reported quarterly sales minus consensus sales forecasts, divided by the standard deviation of sales forecasts.'} |
||||
{'id': 741, 'data_set_name': '可以使用:anl10_netrevise_ratio_to_consensus_fq1_2525', 'description': '不可使用,仅供参考:Consensus estimate value for net income Q1'} |
||||
{'id': 322441, 'data_set_name': '可以使用:pv87_ivy_opprc_matrix_weightavg_volivput7', 'description': '不可使用,仅供参考:Weighted average Implied volatility for near out-of-the-money put options with volume used as weight factor'} |
||||
{'id': 325692, 'data_set_name': '可以使用:pv87_web_weightedavg1_group_css_revenues', 'description': '不可使用,仅供参考:1-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Revenues'} |
||||
{'id': 295584, 'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w4_kmeans_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 20 groups.'} |
||||
{'id': 2218, 'data_set_name': '可以使用:anl14_numofests_revenue_fp4', 'description': '不可使用,仅供参考:Num of Estimations of Revenue - upcoming 4 quarters'} |
||||
{'id': 883, 'data_set_name': '可以使用:anl10_prrrevise_ratio_to_close_fy1_2559', 'description': '不可使用,仅供参考:Ratio of delta consensus to adjusted close for price return ratio FY1'} |
||||
{'id': 170300, 'data_set_name': '可以使用:mdl177_valuemomemtummodel_earningsqualitymodule', 'description': '不可使用,仅供参考:Earnings Quality Module'} |
||||
{'id': 86040, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_low_px_to_book_ratio', 'description': "不可使用,仅供参考:Equal to the ratio of a stock's low price divided by the book value per share"} |
||||
{'id': 321103, 'data_set_name': '可以使用:pv87_cash_from_operations_of_estimates', 'description': '不可使用,仅供参考:Cash From Operations - # of Estimates'} |
||||
{'id': 326056, 'data_set_name': '可以使用:pv87_webv2_weightedavg20_group_event_sentiment_score_investor_relations', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Investor Relations'} |
||||
{'id': 323558, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted14d_ew_sent_std_trend', 'description': '不可使用,仅供参考:14-day Volume weighted average of Trend of Sentiment Standard deviation'} |
||||
{'id': 168344, 'data_set_name': '可以使用:legal_obligation_language_score_2', 'description': '不可使用,仅供参考:Score based on language about legal responsibilities and agreements (alternate source).'} |
||||
{'id': 322077, 'data_set_name': '可以使用:pv87_indrank_item_5030_364', 'description': '不可使用,仅供参考:Industry ranked item score for item 364 in topic Management Of The Legal Regulatory Environment'} |
||||
{'id': 9720, 'data_set_name': '可以使用:buyside_gfi_score_presentation', 'description': '不可使用,仅供参考:Gunning Fog Index (GFI) for buy-side investors in presentation section.'} |
||||
{'id': 159759, 'data_set_name': '可以使用:fnd65_allcap_sedol_flowratio', 'description': '不可使用,仅供参考:It is defined as the difference between current assets and cash & equivalents divided by the difference between current liabilities and short-term debt. All items are from the most recent quarter.'} |
||||
{'id': 295744, 'data_set_name': '可以使用:oth455_partner_n2v_p50_q50_w2_pca_fact1_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using the 1st eigenvalue of PCA into 5 groups.'} |
||||
{'id': 159820, 'data_set_name': '可以使用:fnd65_allcap_sedol_ohlsonscore', 'description': "不可使用,仅供参考:It is a model assessing a company's probability of bankruptcy by considering firm size,capital structure, financial performance, and liquidity. It is derived from Ohlson (1980)."} |
||||
{'id': 323197, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_sent_z_trend', 'description': '不可使用,仅供参考:7-day Volume weighted average of Trend of Sentiment'} |
||||
{'id': 167954, 'data_set_name': '可以使用:mdl354_group_pt1ac_5y_sale', 'description': '不可使用,仅供参考:Historical 5Y revenue growth acceleration'} |
||||
{'id': 294864, 'data_set_name': '可以使用:oth335_hc_combined_all_region_shield', 'description': '不可使用,仅供参考:Score from the SHIELD model'} |
||||
{'id': 324741, 'data_set_name': '可以使用:pv87_sell_shares_sum', 'description': '不可使用,仅供参考:Sum of Selling Number of shares traded'} |
||||
{'id': 168616, 'data_set_name': '可以使用:region_value_momentum_rank_float', 'description': '不可使用,仅供参考:Precise region-relative value-momentum ranking as a floating-point value.'} |
||||
{'id': 164, 'data_set_name': '可以使用:anl10_dpspast_det_estflag_1230', 'description': '不可使用,仅供参考:Estimate flag for dividends per share'} |
||||
{'id': 383391, 'data_set_name': '可以使用:construction_materials_exposure_score', 'description': '不可使用,仅供参考:Exposure or sensitivity to the construction materials sector factor.'} |
||||
{'id': 1806, 'data_set_name': '可以使用:anl14_low_revenue_fp1', 'description': '不可使用,仅供参考:The lowest estimation of revenue - upcoming quarter'} |
||||
{'id': 323730, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_sent_range', 'description': '不可使用,仅供参考:7-day Volume weighted average of Range of Sentiment'} |
||||
{'id': 404, 'data_set_name': '可以使用:anl10_entpast_det_excflag', 'description': '不可使用,仅供参考:Exclusion flag for earnings net taxes estimates'} |
||||
{'id': 323225, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_matrix_sent_ew_sent_tsrank', 'description': '不可使用,仅供参考:tsrank of Sentiment'} |
||||
{'id': 322063, 'data_set_name': '可以使用:pv87_indrank_item_1070_363', 'description': '不可使用,仅供参考:Industry ranked item score for item 363 in topic Environmental Social Impacts On Assets Operation'} |
||||
{'id': 324157, 'data_set_name': '可以使用:pv87_prv2_simpleavg20_group_nip_revenues', 'description': '不可使用,仅供参考:20-day Simple average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Revenues'} |
||||
{'id': 324285, 'data_set_name': '可以使用:pv87_prv2_weightedavg60_group_nip_equity_actions', 'description': '不可使用,仅供参考:60-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Equity Actions'} |
||||
{'id': 318569, 'data_set_name': '可以使用:principal_component_score_2_all', 'description': '不可使用,仅供参考:Value of the 3rd principal component for all securities in the universe.'} |
||||
{'id': 319732, 'data_set_name': '可以使用:pv87_2_cfps_af_matrix_p1_b_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Cash Flow Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 325515, 'data_set_name': '可以使用:pv87_v2item_indrank_item_6020_200', 'description': '不可使用,仅供参考:Industry ranked item score for item 200 in topic Shareholder Rights'} |
||||
{'id': 325432, 'data_set_name': '可以使用:pv87_v2_weightedavg60_group_css_revenues', 'description': '不可使用,仅供参考:60-day Weighted average of CSS score that represents the news sentiment of a given story by combining various sentiment analysis techniques for group Revenues'} |
||||
{'id': 321330, 'data_set_name': '可以使用:pv87_daily_qtr_matrix_book_value_share_consensus_mean_numanalystsunfiltered', 'description': '不可使用,仅供参考:Number of analysts (unfiltered) of Book Value / Share Consensus Mean'} |
||||
{'id': 321065, 'data_set_name': '可以使用:pv87_capital_expenditure_consensus_low', 'description': '不可使用,仅供参考:Capital Expenditure Consensus Low'} |
||||
{'id': 80537, 'data_set_name': '可以使用:fully_paid_shares_outstanding', 'description': '不可使用,仅供参考:Total number of shares that have been fully paid and are currently outstanding.'} |
||||
{'id': 320253, 'data_set_name': '可以使用:pv87_2_nav_qf_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Net Asset Value (NAV) *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 295572, 'data_set_name': '可以使用:oth455_partner_n2v_p10_q200_w3_kmeans_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with partner data and then clustered using K-means into 20 groups.'} |
||||
{'id': 171088, 'data_set_name': '可以使用:mdl77_400_p50_200ratio', 'description': "不可使用,仅供参考:50-200 Day Stock Price Ratio: It is defined as the moving average of a stock's prices in last 50 days divided by the moving average of its prices in last 200 days."} |
||||
{'id': 10493, 'data_set_name': '可以使用:mws87_numvswordsratiocfoqa', 'description': '不可使用,仅供参考:Number of numerical/number of all words of CFO in Q&A (NA if CFO not attended or no speech in Q&A).'} |
||||
{'id': 87488, 'data_set_name': '可以使用:contingent_liabilities_equity_ratio', 'description': '不可使用,仅供参考:Ratio of potential liabilities to shareholders’ equity.'} |
||||
{'id': 319849, 'data_set_name': '可以使用:pv87_2_ebit_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of EBIT *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 174768, 'data_set_name': '可以使用:oth460_tech_rank_l2', 'description': '不可使用,仅供参考:The probability that the future trend of Relative Strength Ranking Value" will be neutral"'} |
||||
{'id': 319985, 'data_set_name': '可以使用:pv87_2_eps_af_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Earnings Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 167114, 'data_set_name': '可以使用:mdl264_technical_dma_high_class', 'description': '不可使用,仅供参考:Predicted trend of "6-Day Moving Average of the stock\'s daily high value" (1: fall, 2: neutral, 3: move-up)'} |
||||
{'id': 325996, 'data_set_name': '可以使用:pv87_webv2_simpleavg60_group_event_sentiment_score_legal', 'description': '不可使用,仅供参考:60-day Simple average of Event Sentiment Score for group Legal'} |
||||
{'id': 324868, 'data_set_name': '可以使用:pv87_tradealert_options_weightavg_oithetacall4', 'description': '不可使用,仅供参考:theta of near call options'} |
||||
{'id': 169608, 'data_set_name': '可以使用:mdl177_earningmomentumfactor_lagegp_alt', 'description': '不可使用,仅供参考:Lagged Inverse of PEG Ratio : It is defined as the trailing 12-month earnings per share before extraordinary items times the change in yearly trailing 12-month sales per share growth rate, divided by trading price.'} |
||||
{'id': 165468, 'data_set_name': '可以使用:mdl262_trkdpitpredictivetotrevenue_mad_act', 'description': '不可使用,仅供参考:Mean Absolute Deviation of scaled actual value of Total Revenue'} |
||||
{'id': 5633, 'data_set_name': '可以使用:min_research_development_expense_guidance', 'description': '不可使用,仅供参考:Minimum guidance value for Research & Development Expense'} |
||||
{'id': 85069, 'data_set_name': '可以使用:fnd6_ranks', 'description': '不可使用,仅供参考:Ranking'} |
||||
{'id': 323172, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_sent_mean_std', 'description': '不可使用,仅供参考:7-day Volume weighted average of Standard deviation of Sentiment Average'} |
||||
{'id': 83561, 'data_set_name': '可以使用:fnd3_a_rnd_fast_d1', 'description': '不可使用,仅供参考:Annual Research & Development Expense'} |
||||
{'id': 324050, 'data_set_name': '可以使用:pv87_prv2_expavg60_group_event_sentiment_score_all', 'description': '不可使用,仅供参考:60-day Exponential average of Event Sentiment Score for group All'} |
||||
{'id': 321095, 'data_set_name': '可以使用:pv87_cash_from_operations_consensus_high', 'description': '不可使用,仅供参考:Cash From Operations Consensus High'} |
||||
{'id': 83833, 'data_set_name': '可以使用:fnd3_q_sharesauthorized_fast_d1', 'description': '不可使用,仅供参考:Quarterly Shares Authorized'} |
||||
{'id': 324243, 'data_set_name': '可以使用:pv87_prv2_weightedavg20_group_nip_partnerships', 'description': '不可使用,仅供参考:20-day Weighted average of NIP score that represents the degree of impact a news flash has on the market over the following two-hour period for group Partnerships'} |
||||
{'id': 279911, 'data_set_name': '可以使用:mws76_score', 'description': '不可使用,仅供参考:For SENTIMENT and SENTIMENT_SMEDIA, an array of integer values {-1,0,1} represents the assigned Analytics Score for each ticker. -1 is negative, 0 neutral and 1 positive For MMN and MMN_1STPASS, an array of 1 for each ticker'} |
||||
{'id': 296272, 'data_set_name': '可以使用:oth567_deltascore_work_life_balance_399', 'description': '不可使用,仅供参考:Score of work life balance'} |
||||
{'id': 170985, 'data_set_name': '可以使用:mdl77_2pricemomentumfactor_visiratio', 'description': "不可使用,仅供参考:The Visibility Ratio: It equals a stock's most recent daily trading volume divided by the average daily trading volume in the previous 50 trading days."} |
||||
{'id': 78422, 'data_set_name': '可以使用:fnd14_latestqu_incmst_revenue_ttm', 'description': '不可使用,仅供参考:TTM total revenue from the income statement for the four quarters ending with this reported quarter. This includes the previous three quarters summed with this quarter. Depending on the Q or A indicator QUARTER_ENDS_A_FISCAL_YEAR (see description above), if this quarter also ends a fiscal year, then this field is fiscal year earnings for the fiscal year ending with this quarter'} |
||||
{'id': 158748, 'data_set_name': '可以使用:quantity_institutional_shares_acquired', 'description': '不可使用,仅供参考:Number of shares bought by institutions during the reporting period.'} |
||||
{'id': 295439, 'data_set_name': '可以使用:oth455_customer_n2v_p50_q50_w2_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 10 groups.'} |
||||
{'id': 325368, 'data_set_name': '可以使用:pv87_v2_weightedavg20_group_event_sentiment_score_analyst_ratings', 'description': '不可使用,仅供参考:20-day Weighted average of Event Sentiment Score for group Analyst Ratings'} |
||||
{'id': 295314, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q50_w1_pca_fact2_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 2nd eigenvalue of PCA into 20 groups.'} |
||||
{'id': 323693, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_ew_sent_median', 'description': '不可使用,仅供参考:7-day Volume weighted average of Median of Sentiment'} |
||||
{'id': 323678, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_sent_z_trend', 'description': '不可使用,仅供参考:28-day Volume weighted average of Trend of Sentiment'} |
||||
{'id': 325504, 'data_set_name': '可以使用:pv87_v2item_indrank_item_4020_153', 'description': '不可使用,仅供参考:Industry ranked item score for item 153 in topic Business Model Resilience'} |
||||
{'id': 9766, 'data_set_name': '可以使用:other_ceo_word_share_presentation', 'description': '不可使用,仅供参考:Proportion of words spoken by other CEOs relative to all executive words in the presentation section.'} |
||||
{'id': 295341, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q50_w3_pca_fact3_cluster_20', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using the 3rd eigenvalue of PCA into 20 groups.'} |
||||
{'id': 323707, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted7d_ew_sent_tsrank', 'description': '不可使用,仅供参考:7-day Volume weighted average of End-of-day time series rank of Sentiment'} |
||||
{'id': 1815, 'data_set_name': '可以使用:anl14_low_revenue_fy5', 'description': '不可使用,仅供参考:The Lowest Estimation of Revenue - upcoming 5 years'} |
||||
{'id': 169810, 'data_set_name': '可以使用:mdl177_growthanalystmodel_qga_opmarginsales_alt', 'description': '不可使用,仅供参考:Op Margin to Sales Link'} |
||||
{'id': 160418, 'data_set_name': '可以使用:fnd65_us5000_cusip_capexsale', 'description': '不可使用,仅供参考:It is defined as trailing 12-month capital expenditures divided by trailing 12-month sales.'} |
||||
{'id': 83750, 'data_set_name': '可以使用:fnd3_q_comstk_divpershare', 'description': '不可使用,仅供参考:Quarterly Common Stock Dividends Per Share'} |
||||
{'id': 6003, 'data_set_name': '可以使用:anl44_best_sales_chg_pct', 'description': '不可使用,仅供参考:best sales chg pct'} |
||||
{'id': 737, 'data_set_name': '可以使用:anl10_netrevise_ratio_to_close_fq1_2529', 'description': '不可使用,仅供参考:Ratio of delta consensus to adjusted close for net income Q1'} |
||||
{'id': 320012, 'data_set_name': '可以使用:pv87_2_eps_qf_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Earnings Per Share *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 63, 'data_set_name': '可以使用:anl10_cpsrevise_ratio_to_consensus_fy1', 'description': '不可使用,仅供参考:Consensus estimate value for cash per share FY1'} |
||||
{'id': 169665, 'data_set_name': '可以使用:mdl177_earningsqualityfactor_chgshare', 'description': "不可使用,仅供参考:Percent Change in Shares Outstanding : It is defined as the percent change in a company's current number of outstanding shares as compared to the number of shares outstanding one year ago."} |
||||
{'id': 169206, 'data_set_name': '可以使用:mdl177_2_historicalgrowthfactor_fcfequity', 'description': '不可使用,仅供参考:TTM Free Cash Flow to Equity : It is defined as the trailing 12-month free cash flow divided by the average book equity value in the same period.'} |
||||
{'id': 295271, 'data_set_name': '可以使用:oth455_customer_n2v_p10_q200_w3_kmeans_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 10 groups.'} |
||||
{'id': 78165, 'data_set_name': '可以使用:role_tenure_duration', 'description': "不可使用,仅供参考:Duration of the director's current role."} |
||||
{'id': 323175, 'data_set_name': '可以使用:pv87_ocialmarketanalytics2_fullweek_matrix_sent_volweighted7d_sent_mean_tsrank', 'description': '不可使用,仅供参考:7-day Volume weighted average of End-of-day time series rank of Sentiment Average'} |
||||
{'id': 323613, 'data_set_name': '可以使用:pv87_ocialmarketanalytics3_fullweek_matrix_sent_volweighted28d_ew_sent_mean_deviation', 'description': '不可使用,仅供参考:28-day Volume weighted average of Deviation of Sentiment Average'} |
||||
{'id': 6359, 'data_set_name': '可以使用:anl44_sales_prevalue', 'description': '不可使用,仅供参考:Sales d0 prevalue'} |
||||
{'id': 279755, 'data_set_name': '可以使用:headline_positive_sentiment_score', 'description': '不可使用,仅供参考:Positive sentiment score derived from the news headline.'} |
||||
{'id': 320455, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} |
||||
{'id': 295405, 'data_set_name': '可以使用:oth455_customer_n2v_p50_q200_w4_kmeans_cluster_5', 'description': '不可使用,仅供参考:Grouping data. Embedded using N2V with customer data and then clustered using K-means into 5 groups.'} |
||||
{'id': 295532, 'data_set_name': '可以使用:oth455_customer_roam_w4_pca_fact3_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using the 3rd eigenvalue of PCA into 10 groups.'} |
||||
{'id': 295505, 'data_set_name': '可以使用:oth455_customer_roam_w2_pca_fact2_cluster_10', 'description': '不可使用,仅供参考:Grouping data. Embedded using ROAM with customer data and then clustered using the 2nd eigenvalue of PCA into 10 groups.'} |
||||
{'id': 294548, 'data_set_name': '可以使用:cashflow_negative_score_fast_d1', 'description': '不可使用,仅供参考:Negative sentiment score for cash flow in a transcript chunk.'} |
||||
========================= 数据字段结束 ======================================= |
||||
|
||||
以上数据字段和操作符, 按照Description说明组合, 但是每一个 alpha 组合的使用的数据字段和操作符不要过于集中, 在符合语法的情况下, 多尝试不同的组合 |
||||
|
||||
你再检查一下, 如果你使用了 |
||||
Operator abs does not support event inputs |
||||
Operator ts_mean does not support event inputs |
||||
Operator ts_scale does not support event inputs |
||||
Operator add does not support event inputs |
||||
Operator sign does not support event inputs |
||||
Operator greater does not support event inputs |
||||
Operator ts_av_diff does not support event inputs |
||||
Operator ts_quantile does not support event inputs |
||||
Operator ts_arg_min does not support event inputs |
||||
Operator divide does not support event inputs |
||||
Operator ts_corr does not support event inputs |
||||
Operator ts_decay_linear does not support event inputs |
||||
Operator ts_sum does not support event inputs |
||||
Operator ts_delay does not support event inputs |
||||
Operator ts_arg_max does not support event inputs |
||||
Operator ts_std_dev does not support event inputs |
||||
Operator ts_regression does not support event inputs |
||||
Operator ts_backfill does not support event inputs |
||||
Operator signed_power does not support event inputs |
||||
Operator ts_product does not support event inputs |
||||
Operator ts_zscore does not support event inputs |
||||
Operator group_rank does not support event inputs |
||||
Operator subtract does not support event inputs |
||||
Operator ts_delta does not support event inputs |
||||
Operator ts_rank does not support event inputs |
||||
Operator ts_count_nans does not support event inputs |
||||
Operator ts_covariance does not support event inputs |
||||
Operator multiply does not support event inputs |
||||
Operator if_else does not support event inputs |
||||
Operator group_neutralize does not support event inputs |
||||
Operator group_zscore does not support event inputs |
||||
Operator winsorize does not support event inputs |
||||
注意, 以上操作符不能使用事件类型的数据集, 以上操作符禁止使用事件类型的数据集!! |
||||
Binary file not shown.
@ -1,14 +1 @@ |
||||
Name |
||||
Dynamic Adjustment Factor of Supplier Concentration |
||||
Hypothesis |
||||
The dynamic change in supplier concentration (measured by the proportion of purchases from the top 5 suppliers to total purchases) directly reflects an enterprise's ability to control supply chain risks. If a company's supplier concentration continues to decline from a high level, it indicates that it is actively diversifying supply chain dependence risks, which can effectively reduce operational shocks caused by default, price increase or supply disruption of a single supplier, thereby improving profit stability and risk resistance. Such enterprises deserve a valuation premium and are suitable for establishing long positions. Conversely, if supplier concentration continues to rise from a low level, the enterprise's dependence on a few suppliers deepens, supply chain vulnerability increases, and operational uncertainty rises, making it suitable for establishing short positions. In addition, the speed and magnitude of concentration adjustment are positively correlated with excess returns—fast and reasonable diversification adjustments have higher signal value than slow adjustments. |
||||
Implementation Plan |
||||
Calculate core indicators: Based on enterprise procurement data, measure the supplier concentration ratio (CR5 = purchase amount from top 5 suppliers / total purchase amount); |
||||
Time-series trend analysis: Use the time-series trend operator (ts_trend) to fit the change slope of CR5 over the past 12 months, and classify targets into three categories: "continuous decline (negative slope with absolute value greater than threshold)", "continuous rise (positive slope with absolute value greater than threshold)", and "stable fluctuation"; |
||||
Scale and industry calibration: Divide CR5 by the logarithm of the enterprise's total purchase amount to eliminate scale effects, and calculate the deviation of the target's CR5 from the industry average; |
||||
Construct long-short strategy: Establish long positions on targets with "continuously declining CR5 + current CR5 below industry average"; establish short positions on targets with "continuously rising CR5 + current CR5 above industry average"; exclude targets with stable CR5 fluctuation and small deviation from industry average to reduce noise. |
||||
Alpha Factor Optimization Suggestions |
||||
Introduce industry-differentiated thresholds: There are significant differences in the benchmark values of supplier concentration across industries (e.g., the concentration of core material suppliers in the semiconductor industry is naturally high, while that in the consumer goods industry is low). It is recommended to use the industry quantile operator instead of fixed thresholds to judge the rationality of concentration adjustment by stratification within the industry; |
||||
Superimpose supplier quality verification: Integrate data such as supplier credit ratings and cooperation years. When the decline in concentration is accompanied by "the credit rating of new suppliers being higher than that of original suppliers", strengthen the weight of long signals; if the rise in concentration stems from "exclusive cooperation with high-quality suppliers", weaken the short signals; |
||||
Event-driven weight adjustment: Use the event trigger operator to increase the allocation weight of this factor during industry-wide supply chain crises (such as raw material price surges, material supply disruptions caused by geopolitics), capturing excess returns of supply chain-robust enterprises during crises; |
||||
Tiered weighting optimization: Use the stratification operator to divide the concentration adjustment range into three tiers: "significant adjustment", "moderate adjustment" and "minor adjustment", and set differentiated position weights for different tiers to improve the risk-return ratio of the strategy. |
||||
["customer", "supplier", "overseas", "foreign", "revenue", "patent", "citation", "rnd", "research", "development", "innovation", "tech", "technical", "linkage", "export", "import", "intellectual", "property", "license", "royalty", "collaboration", "partner", "affiliate", "segment", "geographic", "region", "country", "transaction", "sale", "purchase", "expenditure", "spending", "intensity", "employee", "staff", "scientist", "engineer", "personnel", "capability", "absorptive", "rank", "score", "strength", "quality", "weight", "share", "percentage", "ratio", "growth", "lag", "delay", "temporal"] |
||||
@ -1,127 +0,0 @@ |
||||
group_zscore(ts_std_dev(fnd6_newqv1300_invoq, 504), pv13_hierarchy_f3_513_sector) |
||||
|
||||
group_zscore(ts_mean(fnd6_newqv1300_invoq, 504), pv13_hierarchy_f3_513_sector) |
||||
|
||||
subtract(group_zscore(ts_mean(fnd6_newqv1300_invoq, 504), pv13_hierarchy_f3_513_sector), group_zscore(ts_std_dev(fnd6_newqv1300_invoq, 504), pv13_hierarchy_f3_513_sector)) |
||||
|
||||
ts_rank(ts_std_dev(fnd6_newqv1300_invoq, 504), 126) |
||||
|
||||
ts_rank(ts_mean(fnd6_newqv1300_invoq, 504), 126) |
||||
|
||||
subtract(ts_rank(ts_mean(fnd6_newqv1300_invoq, 504), 126), ts_rank(ts_std_dev(fnd6_newqv1300_invoq, 504), 126)) |
||||
|
||||
ts_zscore(ts_std_dev(fnd6_newqv1300_invoq, 504), 252) |
||||
|
||||
ts_zscore(ts_mean(fnd6_newqv1300_invoq, 504), 252) |
||||
|
||||
subtract(ts_zscore(ts_mean(fnd6_newqv1300_invoq, 504), 252), ts_zscore(ts_std_dev(fnd6_newqv1300_invoq, 504), 252)) |
||||
|
||||
ts_delta(ts_mean(fnd6_newqv1300_invoq, 504), 63) |
||||
|
||||
ts_delta(ts_std_dev(fnd6_newqv1300_invoq, 504), 63) |
||||
|
||||
subtract(ts_delta(ts_mean(fnd6_newqv1300_invoq, 504), 63), ts_delta(ts_std_dev(fnd6_newqv1300_invoq, 504), 63)) |
||||
|
||||
ts_corr(ts_mean(fnd6_newqv1300_invoq, 504), ts_std_dev(fnd6_newqv1300_invoq, 504), 252) |
||||
|
||||
ts_covariance(ts_mean(fnd6_newqv1300_invoq, 504), ts_std_dev(fnd6_newqv1300_invoq, 504), 252) |
||||
|
||||
divide(ts_mean(fnd6_newqv1300_invoq, 504), ts_std_dev(fnd6_newqv1300_invoq, 504)) |
||||
|
||||
ts_av_diff(ts_mean(fnd6_newqv1300_invoq, 504), 504) |
||||
|
||||
ts_av_diff(ts_std_dev(fnd6_newqv1300_invoq, 504), 504) |
||||
|
||||
subtract(ts_av_diff(ts_mean(fnd6_newqv1300_invoq, 504), 504), ts_av_diff(ts_std_dev(fnd6_newqv1300_invoq, 504), 504)) |
||||
|
||||
ts_quantile(ts_mean(fnd6_newqv1300_invoq, 504), 504) |
||||
|
||||
ts_quantile(ts_std_dev(fnd6_newqv1300_invoq, 504), 504) |
||||
|
||||
subtract(ts_quantile(ts_mean(fnd6_newqv1300_invoq, 504), 504), ts_quantile(ts_std_dev(fnd6_newqv1300_invoq, 504), 504)) |
||||
|
||||
ts_sum(ts_mean(fnd6_newqv1300_invoq, 504), 126) |
||||
|
||||
ts_sum(ts_std_dev(fnd6_newqv1300_invoq, 504), 126) |
||||
|
||||
subtract(ts_sum(ts_mean(fnd6_newqv1300_invoq, 504), 126), ts_sum(ts_std_dev(fnd6_newqv1300_invoq, 504), 126)) |
||||
|
||||
ts_product(ts_mean(fnd6_newqv1300_invoq, 504), 63) |
||||
|
||||
ts_product(ts_std_dev(fnd6_newqv1300_invoq, 504), 63) |
||||
|
||||
divide(ts_product(ts_mean(fnd6_newqv1300_invoq, 504), 63), ts_product(ts_std_dev(fnd6_newqv1300_invoq, 504), 63)) |
||||
|
||||
ts_arg_min(ts_mean(fnd6_newqv1300_invoq, 504), 504) |
||||
|
||||
ts_arg_max(ts_std_dev(fnd6_newqv1300_invoq, 504), 504) |
||||
|
||||
subtract(ts_arg_min(ts_mean(fnd6_newqv1300_invoq, 504), 504), ts_arg_max(ts_std_dev(fnd6_newqv1300_invoq, 504), 504)) |
||||
|
||||
ts_count_nans(fnd6_newqv1300_invoq, 504) |
||||
|
||||
ts_backfill(fnd6_newqv1300_invoq, 504) |
||||
|
||||
subtract(ts_backfill(fnd6_newqv1300_invoq, 504), ts_count_nans(fnd6_newqv1300_invoq, 504)) |
||||
|
||||
group_zscore(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), pv13_hierarchy_f3_513_sector) |
||||
|
||||
group_neutralize(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), pv13_hierarchy_f3_513_sector) |
||||
|
||||
ts_zscore(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504) |
||||
|
||||
ts_rank(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504) |
||||
|
||||
group_rank(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), pv13_hierarchy_f3_513_sector) |
||||
|
||||
ts_mean(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504) |
||||
|
||||
ts_std_dev(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504) |
||||
|
||||
divide(ts_std_dev(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504), ts_mean(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504)) |
||||
|
||||
ts_delta(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 63) |
||||
|
||||
ts_regression(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), ts_step(1), 504, 0, 1) |
||||
|
||||
ts_av_diff(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504) |
||||
|
||||
group_zscore(ts_mean(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504), pv13_hierarchy_f3_513_sector) |
||||
|
||||
group_neutralize(ts_std_dev(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504), pv13_hierarchy_f3_513_sector) |
||||
|
||||
multiply(group_zscore(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), pv13_hierarchy_f3_513_sector), -1) |
||||
|
||||
ts_zscore(ts_delta(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 63), 504) |
||||
|
||||
group_zscore(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), pv13_hierarchy_min2_focused_pureplay_3000_513_sector) |
||||
|
||||
multiply(divide(fnd6_newqv1300_invoq, est_sales), 365) |
||||
|
||||
group_zscore(fnd6_newqv1300_invoq, pv13_hierarchy_f3_513_sector) |
||||
|
||||
ts_zscore(fnd6_newqv1300_invoq, 504) |
||||
|
||||
divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt) |
||||
|
||||
group_zscore(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), pv13_hierarchy_f3_513_sector) |
||||
|
||||
ts_mean(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 504) |
||||
|
||||
ts_std_dev(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 504) |
||||
|
||||
multiply(ts_rank(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 504), -1) |
||||
|
||||
ts_quantile(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 504) |
||||
|
||||
group_scale(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), pv13_hierarchy_f3_513_sector) |
||||
|
||||
normalize(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25)) |
||||
|
||||
quantile(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25)) |
||||
|
||||
scale(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25)) |
||||
|
||||
winsorize(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25), 4) |
||||
|
||||
zscore(multiply(divide(fnd6_newqv1300_invoq, fnd6_newa1v1300_revt), 91.25)) |
||||
Loading…
Reference in new issue