main
jack
1 month ago
parent
cf6eb8c92a
commit
0d3b279a2e
@ -0,0 +1,171 @@ |
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group_neutralize(rank(log(ts_mean(divide(fnd6_newa2v1300_revt, fnd6_newa2v1300_oancf), 63))), industry) |
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group_zscore(rank(ts_corr(ts_delta(fnd6_newa2v1300_oancf, 5), ts_delta(ts_mean(fnd6_newa2v1300_revt, 20), 5), 63)), industry) |
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ts_rank(signed_power(ts_delta(fnd6_newa2v1300_oancf, 1), 2) * ts_rank(ts_scale(ts_sum(ts_delta(ts_mean(fnd6_newa2v1300_revt, 20), 5), 20), 5), 5), 5) |
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group_neutralize(ts_zscore(divide(fnd6_newa2v1300_oancf, fnd6_newa2v1300_revt), 252), industry) |
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rank(multiply(ts_rank(ts_mean(fnd6_newa2v1300_revt, 5), 5), ts_rank(ts_delta(fnd6_newa2v1300_oancf, 1), 20))) |
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group_neutralize(ts_rank(divide(ts_sum(fnd6_newa2v1300_oancf, 63), ts_sum(fnd6_newa2v1300_revt, 63)), 20), industry) |
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rank(subtract(ts_mean(ts_delta(fnd6_newa2v1300_oancf, 1), 5), ts_std_dev(ts_delta(fnd6_newa2v1300_revt, 1), 20))) |
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group_zscore(rank(divide(ts_sum(ts_backfill(fnd6_newa2v1300_oancf, 5), 20), ts_sum(ts_backfill(fnd6_newa2v1300_revt, 5), 20))), industry) |
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ts_rank(ts_corr(ts_delay(fnd6_newa2v1300_oancf, 5), ts_delay(fnd6_newa2v1300_revt, 5), 20), 5) |
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group_neutralize(rank(ts_scale(ts_sum(fnd6_newa2v1300_oancf, 63), 63) * ts_scale(ts_sum(fnd6_newa2v1300_revt, 63), 63)), industry) |
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rank(multiply(ts_rank(ts_delta(fnd6_newa2v1300_oancf, 2), 10), ts_zscore(ts_sum(fnd6_newa2v1300_revt, 20), 20))) |
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group_zscore(ts_rank(divide(ts_delta(ts_mean(fnd6_newa2v1300_oancf, 10), 5), ts_delta(ts_mean(fnd6_newa2v1300_revt, 10), 5)), 20), industry) |
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ts_rank(ts_sum(ts_delta(signed_power(fnd6_newa2v1300_oancf, 3), 1), 5) - ts_sum(ts_delta(signed_power(fnd6_newa2v1300_revt, 3), 1), 5), 20) |
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group_neutralize(rank(divide(ts_sum(ts_delta(fnd6_newa2v1300_oancf, 1), 63), ts_sum(ts_mean(fnd6_newa2v1300_revt, 5), 63))), industry) |
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rank(subtract(ts_mean(fnd6_newa2v1300_oancf, 10), ts_mean(ts_zscore(fnd6_newa2v1300_revt, 20), 10))) |
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group_zscore(ts_rank(ts_corr(ts_av_diff(fnd6_newa2v1300_oancf, 20), ts_av_diff(fnd6_newa2v1300_revt, 20), 10), 5), industry) |
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rank(multiply(ts_rank(ts_decay_linear(fnd6_newa2v1300_oancf, 5), 5), ts_rank(ts_decay_linear(fnd6_newa2v1300_revt, 5), 5))) |
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group_neutralize(ts_zscore(divide(ts_product(fnd6_newa2v1300_oancf, 5), ts_product(fnd6_newa2v1300_revt, 5)), 20), industry) |
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rank(ts_sum(ts_delta(divide(fnd6_newa2v1300_oancf, ts_delay(fnd6_newa2v1300_oancf, 1)), 1), 10) - ts_sum(ts_delta(divide(fnd6_newa2v1300_revt, ts_delay(fnd6_newa2v1300_revt, 1)), 1), 10)) |
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group_zscore(rank(ts_mean(ts_delta(log(fnd6_newa2v1300_oancf), 2), 10) * ts_mean(ts_delta(log(fnd6_newa2v1300_revt), 2), 10)), industry) |
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ts_rank(ts_corr(ts_backfill(fnd6_newa2v1300_oancf, 5), ts_backfill(fnd6_newa2v1300_revt, 5), 15), 5) |
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group_neutralize(rank(divide(ts_sum(fnd6_newa2v1300_oancf, 20), ts_sum(ts_delay(fnd6_newa2v1300_revt, 5), 20))), industry) |
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rank(ts_mean(ts_delta(ts_scale(fnd6_newa2v1300_oancf, 10), 5), 10) - ts_mean(ts_delta(ts_scale(fnd6_newa2v1300_revt, 10), 5), 10)) |
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group_zscore(ts_rank(divide(ts_sum(ts_zscore(fnd6_newa2v1300_oancf, 10), 5), ts_sum(ts_zscore(fnd6_newa2v1300_revt, 10), 5)), 10), industry) |
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rank(multiply(ts_rank(ts_sum(fnd6_newa2v1300_oancf, 10), 10), ts_rank(ts_sum(fnd6_newa2v1300_revt, 10), 10))) |
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group_neutralize(ts_zscore(divide(ts_delta(ts_mean(fnd6_newa2v1300_oancf, 5), 5), ts_delta(ts_mean(fnd6_newa2v1300_revt, 5), 5)), 20), industry) |
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rank(subtract(ts_mean(divide(fnd6_newa2v1300_oancf, ts_delay(fnd6_newa2v1300_oancf, 1)), 10), ts_mean(divide(fnd6_newa2v1300_revt, ts_delay(fnd6_newa2v1300_revt, 1)), 10))) |
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group_zscore(rank(ts_corr(ts_rank(fnd6_newa2v1300_oancf, 5), ts_rank(fnd6_newa2v1300_revt, 5), 10)), industry) |
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ts_rank(ts_sum(ts_delta(signed_power(ts_mean(fnd6_newa2v1300_oancf, 5), 2), 1), 5) * ts_sum(ts_delta(signed_power(ts_mean(fnd6_newa2v1300_revt, 5), 2), 1), 5), 10) |
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group_neutralize(rank(divide(ts_product(ts_delta(fnd6_newa2v1300_oancf, 2), 5), ts_product(ts_delta(fnd6_newa2v1300_revt, 2), 5))), industry) |
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rank(ts_mean(ts_av_diff(fnd6_newa2v1300_oancf, 10), 5) - ts_mean(ts_av_diff(fnd6_newa2v1300_revt, 10), 5)) |
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group_zscore(ts_rank(divide(ts_sum(ts_backfill(fnd6_newa2v1300_oancf, 3), 10), ts_sum(ts_backfill(fnd6_newa2v1300_revt, 3), 10)), 20), industry) |
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rank(multiply(ts_rank(ts_decay_linear(ts_delta(fnd6_newa2v1300_oancf, 1), 5), 5), ts_rank(ts_decay_linear(ts_delta(fnd6_newa2v1300_revt, 1), 5), 5))) |
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group_neutralize(ts_zscore(divide(ts_scale(ts_sum(fnd6_newa2v1300_oancf, 20), 20), ts_scale(ts_sum(fnd6_newa2v1300_revt, 20), 20)), 10), industry) |
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rank(subtract(ts_sum(ts_delta(log(fnd6_newa2v1300_oancf), 2), 10), ts_sum(ts_delta(log(fnd6_newa2v1300_revt), 2), 10))) |
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group_zscore(rank(ts_corr(ts_delay(fnd6_newa2v1300_oancf, 10), ts_delay(fnd6_newa2v1300_revt, 10), 20)), industry) |
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ts_rank(ts_sum(ts_delta(ts_mean(fnd6_newa2v1300_oancf, 5), 1), 5) * ts_sum(ts_delta(ts_mean(fnd6_newa2v1300_revt, 5), 1), 5), 10) |
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group_neutralize(rank(divide(ts_sum(ts_zscore(fnd6_newa2v1300_oancf, 5), 10), ts_sum(ts_zscore(fnd6_newa2v1300_revt, 5), 10))), industry) |
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rank(ts_mean(ts_delta(divide(fnd6_newa2v1300_oancf, ts_mean(fnd6_newa2v1300_oancf, 5)), 1), 10) - ts_mean(ts_delta(divide(fnd6_newa2v1300_revt, ts_mean(fnd6_newa2v1300_revt, 5)), 1), 10)) |
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group_zscore(ts_rank(divide(ts_product(ts_backfill(fnd6_newa2v1300_oancf, 2), 5), ts_product(ts_backfill(fnd6_newa2v1300_revt, 2), 5)), 15), industry) |
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rank(multiply(ts_rank(ts_sum(ts_delta(fnd6_newa2v1300_oancf, 1), 10), 10), ts_rank(ts_sum(ts_delta(fnd6_newa2v1300_revt, 1), 10), 10))) |
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group_neutralize(ts_zscore(divide(ts_av_diff(fnd6_newa2v1300_oancf, 20), ts_av_diff(fnd6_newa2v1300_revt, 20)), 10), industry) |
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rank(subtract(ts_sum(ts_decay_linear(fnd6_newa2v1300_oancf, 5), 10), ts_sum(ts_decay_linear(fnd6_newa2v1300_revt, 5), 10))) |
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group_zscore(rank(ts_corr(ts_rank(ts_delta(fnd6_newa2v1300_oancf, 2), 5), ts_rank(ts_delta(fnd6_newa2v1300_revt, 2), 5), 10)), industry) |
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ts_rank(ts_sum(ts_delta(signed_power(ts_backfill(fnd6_newa2v1300_oancf, 3), 3), 1), 5) - ts_sum(ts_delta(signed_power(ts_backfill(fnd6_newa2v1300_revt, 3), 3), 1), 5), 20) |
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group_neutralize(rank(divide(ts_mean(ts_scale(fnd6_newa2v1300_oancf, 10), 5), ts_mean(ts_scale(fnd6_newa2v1300_revt, 10), 5))), industry) |
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rank(ts_mean(ts_delta(ts_zscore(fnd6_newa2v1300_oancf, 10), 5), 10) - ts_mean(ts_delta(ts_zscore(fnd6_newa2v1300_revt, 10), 5), 10)) |
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group_zscore(ts_rank(divide(ts_sum(ts_av_diff(fnd6_newa2v1300_oancf, 5), 10), ts_sum(ts_av_diff(fnd6_newa2v1300_revt, 5), 10)), 20), industry) |
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rank(multiply(ts_rank(ts_product(fnd6_newa2v1300_oancf, 5), 5), ts_rank(ts_product(fnd6_newa2v1300_revt, 5), 5))) |
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group_neutralize(ts_zscore(divide(ts_delay(fnd6_newa2v1300_oancf, 5), ts_delay(fnd6_newa2v1300_revt, 5)), 20), industry) |
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rank(subtract(ts_sum(ts_delta(ts_mean(fnd6_newa2v1300_oancf, 10), 2), 10), ts_sum(ts_delta(ts_mean(fnd6_newa2v1300_revt, 10), 2), 10))) |
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group_zscore(rank(ts_corr(ts_backfill(ts_delta(fnd6_newa2v1300_oancf, 1), 5), ts_backfill(ts_delta(fnd6_newa2v1300_revt, 1), 5), 15)), industry) |
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ts_rank(ts_sum(ts_delta(ts_decay_linear(fnd6_newa2v1300_oancf, 5), 1), 5) * ts_sum(ts_delta(ts_decay_linear(fnd6_newa2v1300_revt, 5), 1), 5), 10) |
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group_neutralize(rank(divide(ts_sum(ts_zscore(ts_delta(fnd6_newa2v1300_oancf, 2), 10), 5), ts_sum(ts_zscore(ts_delta(fnd6_newa2v1300_revt, 2), 10), 5))), industry) |
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rank(ts_mean(ts_delta(divide(fnd6_newa2v1300_oancf, ts_sum(fnd6_newa2v1300_oancf, 10)), 1), 10) - ts_mean(ts_delta(divide(fnd6_newa2v1300_revt, ts_sum(fnd6_newa2v1300_revt, 10)), 1), 10)) |
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group_zscore(ts_rank(divide(ts_product(ts_scale(fnd6_newa2v1300_oancf, 5), 5), ts_product(ts_scale(fnd6_newa2v1300_revt, 5), 5)), 15), industry) |
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rank(multiply(ts_rank(ts_sum(ts_av_diff(fnd6_newa2v1300_oancf, 10), 10), 10), ts_rank(ts_sum(ts_av_diff(fnd6_newa2v1300_revt, 10), 10), 10))) |
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group_neutralize(ts_zscore(divide(ts_mean(ts_backfill(fnd6_newa2v1300_oancf, 5), 10), ts_mean(ts_backfill(fnd6_newa2v1300_revt, 5), 10)), 20), industry) |
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rank(subtract(ts_sum(ts_delta(ts_zscore(fnd6_newa2v1300_oancf, 5), 2), 10), ts_sum(ts_delta(ts_zscore(fnd6_newa2v1300_revt, 5), 2), 10))) |
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group_zscore(rank(ts_corr(ts_rank(ts_sum(fnd6_newa2v1300_oancf, 5), 5), ts_rank(ts_sum(fnd6_newa2v1300_revt, 5), 5), 10)), industry) |
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ts_rank(ts_sum(ts_delta(signed_power(ts_mean(ts_delta(fnd6_newa2v1300_oancf, 1), 5), 2), 1), 5) - ts_sum(ts_delta(signed_power(ts_mean(ts_delta(fnd6_newa2v1300_revt, 1), 5), 2), 1), 5), 20) |
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group_neutralize(rank(divide(ts_mean(ts_delay(fnd6_newa2v1300_oancf, 10), 5), ts_mean(ts_delay(fnd6_newa2v1300_revt, 10), 5))), industry) |
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rank(ts_mean(ts_delta(ts_scale(ts_sum(fnd6_newa2v1300_oancf, 10), 10), 5), 10) - ts_mean(ts_delta(ts_scale(ts_sum(fnd6_newa2v1300_revt, 10), 10), 5), 10)) |
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group_zscore(ts_rank(divide(ts_sum(ts_backfill(ts_delta(fnd6_newa2v1300_oancf, 2), 3), 10), ts_sum(ts_backfill(ts_delta(fnd6_newa2v1300_revt, 2), 3), 10)), 20), industry) |
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rank(multiply(ts_rank(ts_sum(ts_decay_linear(ts_delta(fnd6_newa2v1300_oancf, 1), 5), 10), 10), ts_rank(ts_sum(ts_decay_linear(ts_delta(fnd6_newa2v1300_revt, 1), 5), 10), 10))) |
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group_neutralize(ts_zscore(divide(ts_av_diff(ts_sum(fnd6_newa2v1300_oancf, 20), 20), ts_av_diff(ts_sum(fnd6_newa2v1300_revt, 20), 20)), 10), industry) |
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rank(subtract(ts_sum(ts_delta(log(ts_mean(fnd6_newa2v1300_oancf, 5)), 2), 10), ts_sum(ts_delta(log(ts_mean(fnd6_newa2v1300_revt, 5)), 2), 10))) |
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group_zscore(rank(ts_corr(ts_delay(ts_rank(fnd6_newa2v1300_oancf, 5), 10), ts_delay(ts_rank(fnd6_newa2v1300_revt, 5), 10), 20)), industry) |
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ts_rank(ts_sum(ts_delta(ts_mean(ts_backfill(fnd6_newa2v1300_oancf, 3), 5), 1), 5) * ts_sum(ts_delta(ts_mean(ts_backfill(fnd6_newa2v1300_revt, 3), 5), 1), 5), 10) |
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group_neutralize(rank(divide(ts_sum(ts_zscore(ts_sum(fnd6_newa2v1300_oancf, 10), 5), 10), ts_sum(ts_zscore(ts_sum(fnd6_newa2v1300_revt, 10), 5), 10))), industry) |
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rank(ts_mean(ts_delta(divide(fnd6_newa2v1300_oancf, ts_product(fnd6_newa2v1300_oancf, 5)), 1), 10) - ts_mean(ts_delta(divide(fnd6_newa2v1300_revt, ts_product(fnd6_newa2v1300_revt, 5)), 1), 10)) |
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group_zscore(ts_rank(divide(ts_product(ts_scale(ts_delta(fnd6_newa2v1300_oancf, 1), 5), 5), ts_product(ts_scale(ts_delta(fnd6_newa2v1300_revt, 1), 5), 5)), 15), industry) |
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rank(multiply(ts_rank(ts_sum(ts_av_diff(ts_sum(fnd6_newa2v1300_oancf, 10), 10), 10), 10), ts_rank(ts_sum(ts_av_diff(ts_sum(fnd6_newa2v1300_revt, 10), 10), 10), 10))) |
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group_neutralize(ts_zscore(divide(ts_mean(ts_backfill(ts_delta(fnd6_newa2v1300_oancf, 2), 5), 10), ts_mean(ts_backfill(ts_delta(fnd6_newa2v1300_revt, 2), 5), 10)), 20), industry) |
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rank(subtract(ts_sum(ts_delta(ts_zscore(ts_sum(fnd6_newa2v1300_oancf, 5), 5), 2), 10), ts_sum(ts_delta(ts_zscore(ts_sum(fnd6_newa2v1300_revt, 5), 5), 2), 10))) |
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group_zscore(rank(ts_corr(ts_rank(ts_sum(ts_delta(fnd6_newa2v1300_oancf, 1), 5), 5), ts_rank(ts_sum(ts_delta(fnd6_newa2v1300_revt, 1), 5), 5), 10)), industry) |
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ts_rank(ts_sum(ts_delta(signed_power(ts_mean(ts_backfill(fnd6_newa2v1300_oancf, 3), 5), 2), 1), 5) - ts_sum(ts_delta(signed_power(ts_mean(ts_backfill(fnd6_newa2v1300_revt, 3), 5), 2), 1), 5), 20) |
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group_neutralize(rank(divide(ts_mean(ts_delay(ts_sum(fnd6_newa2v1300_oancf, 10), 10), 5), ts_mean(ts_delay(ts_sum(fnd6_newa2v1300_revt, 10), 10), 5))), industry) |
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rank(ts_mean(ts_delta(ts_scale(ts_product(fnd6_newa2v1300_oancf, 5), 10), 5), 10) - ts_mean(ts_delta(ts_scale(ts_product(fnd6_newa2v1300_revt, 5), 10), 5), 10)) |
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group_zscore(ts_rank(divide(ts_sum(ts_backfill(ts_zscore(fnd6_newa2v1300_oancf, 10), 3), 10), ts_sum(ts_backfill(ts_zscore(fnd6_newa2v1300_revt, 10), 3), 10)), 20), industry) |
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rank(multiply(ts_rank(ts_sum(ts_decay_linear(ts_av_diff(fnd6_newa2v1300_oancf, 10), 5), 10), 10), ts_rank(ts_sum(ts_decay_linear(ts_av_diff(fnd6_newa2v1300_revt, 10), 5), 10), 10))) |
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group_neutralize(ts_zscore(divide(ts_av_diff(ts_mean(fnd6_newa2v1300_oancf, 20), 20), ts_av_diff(ts_mean(fnd6_newa2v1300_revt, 20), 20)), 10), industry) |
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rank(subtract(ts_sum(ts_delta(log(ts_zscore(fnd6_newa2v1300_oancf, 5)), 2), 10), ts_sum(ts_delta(log(ts_zscore(fnd6_newa2v1300_revt, 5)), 2), 10))) |
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group_zscore(rank(ts_corr(ts_delay(ts_scale(fnd6_newa2v1300_oancf, 10), 10), ts_delay(ts_scale(fnd6_newa2v1300_revt, 10), 10), 20)), industry) |
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ts_rank(ts_sum(ts_delta(ts_mean(ts_scale(fnd6_newa2v1300_oancf, 5), 5), 1), 5) * ts_sum(ts_delta(ts_mean(ts_scale(fnd6_newa2v1300_revt, 5), 5), 1), 5), 10) |
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group_neutralize(rank(divide(ts_sum(ts_zscore(ts_product(fnd6_newa2v1300_oancf, 5), 10), 10), ts_sum(ts_zscore(ts_product(fnd6_newa2v1300_revt, 5), 10), 10))), industry) |
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@ -0,0 +1,201 @@ |
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reverse(ts_mean(divide(multiply(abs(subtract(ts_mean(fscore_total, 5), ts_mean(fscore_total, 10))), ts_mean(multi_factor_acceleration_score_derivative, 5)), abs(add(ts_mean(multi_factor_acceleration_score_derivative, 5), ts_mean(multi_factor_acceleration_score_derivative, 10))))), 20)) |
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reverse(ts_corr(ts_delta(fscore_total, 5), ts_delta(multi_factor_acceleration_score_derivative, 5), 20)) |
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reverse(ts_sum(if_else(ts_delta(fscore_total, 1) > 0, ts_delta(multi_factor_acceleration_score_derivative, 1), 0), 10)) |
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reverse(ts_rank(ts_mean(multiply(fscore_total, multi_factor_acceleration_score_derivative), 5), 20)) |
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reverse(subtract(ts_mean(multiply(ts_zscore(fscore_total, 10), ts_zscore(multi_factor_acceleration_score_derivative, 10)), 20), ts_mean(multiply(ts_zscore(fscore_total, 5), ts_zscore(multi_factor_acceleration_score_derivative, 5)), 20))) |
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reverse(ts_delta(ts_mean(divide(fscore_total, multi_factor_acceleration_score_derivative), 10), "5")) |
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reverse(ts_corr(ts_sum(fscore_total, 5), ts_sum(multi_factor_acceleration_score_derivative, 5), 20)) |
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reverse(ts_mean(multiply(sign(ts_delta(fscore_total, 1)), sign(ts_delta(multi_factor_acceleration_score_derivative, 1))), 10)) |
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reverse(ts_scale(ts_sum(multiply(ts_rank(fscore_total, 10), ts_rank(multi_factor_acceleration_score_derivative, 10)), 5), 10)) |
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reverse(divide(ts_sum(multiply(fscore_total, multi_factor_acceleration_score_derivative), 10), ts_sum(add(fscore_total, multi_factor_acceleration_score_derivative), 10))) |
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|
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reverse(ts_mean(subtract(ts_zscore(fscore_total, 20), ts_zscore(multi_factor_acceleration_score_derivative, 20)), 10)) |
||||
|
||||
reverse(ts_rank(multiply(ts_delta(fscore_total, 5), ts_delta(multi_factor_acceleration_score_derivative, 5)), 20)) |
||||
|
||||
reverse(ts_sum(if_else(ts_delta(fscore_total, 2) > ts_delta(multi_factor_acceleration_score_derivative, 2), 1, -1), 10)) |
||||
|
||||
reverse(ts_corr(ts_decay_linear(fscore_total, 5), ts_decay_linear(multi_factor_acceleration_score_derivative, 5), 10)) |
||||
|
||||
reverse(ts_mean(multiply(power(ts_zscore(fscore_total, 10), 2), power(ts_zscore(multi_factor_acceleration_score_derivative, 10), 2)), 20)) |
||||
|
||||
reverse(ts_delta(ts_corr(ts_mean(fscore_total, 5), ts_mean(multi_factor_acceleration_score_derivative, 5), 10), 5)) |
||||
|
||||
reverse(ts_rank(add(ts_std_dev(fscore_total, 5), ts_std_dev(multi_factor_acceleration_score_derivative, 5)), 20)) |
||||
|
||||
reverse(divide(ts_sum(multiply(ts_rank(fscore_total, 5), multi_factor_acceleration_score_derivative), 10), ts_sum(multi_factor_acceleration_score_derivative, 10))) |
||||
|
||||
reverse(ts_mean(subtract(ts_delta(fscore_total, 3), ts_delta(multi_factor_acceleration_score_derivative, 3)), 15)) |
||||
|
||||
reverse(ts_corr(ts_product(fscore_total, 3), ts_product(multi_factor_acceleration_score_derivative, 3), 15)) |
||||
|
||||
reverse(ts_sum(if_else(ts_zscore(fscore_total, 5) > ts_zscore(multi_factor_acceleration_score_derivative, 5), ts_delta(fscore_total, 1), ts_delta(multi_factor_acceleration_score_derivative, 1)), 10)) |
||||
|
||||
reverse(ts_mean(multiply(ts_scale(fscore_total, 10), ts_scale(multi_factor_acceleration_score_derivative, 10)), 20)) |
||||
|
||||
reverse(ts_delta(ts_rank(multiply(fscore_total, multi_factor_acceleration_score_derivative), 10), 5)) |
||||
|
||||
reverse(ts_corr(ts_zscore(fscore_total, 10), ts_zscore(multi_factor_acceleration_score_derivative, 10), 20)) |
||||
|
||||
reverse(ts_sum(multiply(sign(ts_delta(fscore_total, 2)), abs(ts_delta(multi_factor_acceleration_score_derivative, 2))), 10)) |
||||
|
||||
reverse(ts_rank(subtract(ts_sum(fscore_total, 5), ts_sum(multi_factor_acceleration_score_derivative, 5)), 20)) |
||||
|
||||
reverse(ts_mean(divide(multiply(ts_delta(fscore_total, 1), ts_delta(multi_factor_acceleration_score_derivative, 1)), add(abs(ts_delta(fscore_total, 1)), abs(ts_delta(multi_factor_acceleration_score_derivative, 1)))), 10)) |
||||
|
||||
reverse(ts_corr(ts_backfill(fscore_total, 5), ts_backfill(multi_factor_acceleration_score_derivative, 5), 15)) |
||||
|
||||
reverse(ts_sum(if_else(ts_mean(fscore_total, 3) > ts_mean(multi_factor_acceleration_score_derivative, 3), ts_delta(fscore_total, 1), 0), 10)) |
||||
|
||||
reverse(ts_mean(multiply(signed_power(ts_zscore(fscore_total, 5), 2), signed_power(ts_zscore(multi_factor_acceleration_score_derivative, 5), 2)), 15)) |
||||
|
||||
reverse(ts_delta(ts_corr(ts_decay_linear(fscore_total, 3), ts_decay_linear(multi_factor_acceleration_score_derivative, 3), 10), 5)) |
||||
|
||||
reverse(ts_rank(add(ts_av_diff(fscore_total, 5), ts_av_diff(multi_factor_acceleration_score_derivative, 5)), 20)) |
||||
|
||||
reverse(divide(ts_sum(multiply(fscore_total, ts_rank(multi_factor_acceleration_score_derivative, 5)), 10), ts_sum(fscore_total, 10))) |
||||
|
||||
reverse(ts_mean(subtract(ts_mean(fscore_total, 5), ts_mean(multi_factor_acceleration_score_derivative, 5)), 10)) |
||||
|
||||
reverse(ts_corr(ts_delta(fscore_total, 3), ts_sum(multi_factor_acceleration_score_derivative, 3), 15)) |
||||
|
||||
reverse(ts_sum(if_else(ts_zscore(fscore_total, 10) > 0, ts_delta(multi_factor_acceleration_score_derivative, 1), 0), 10)) |
||||
|
||||
reverse(ts_mean(multiply(ts_rank(fscore_total, 10), ts_delta(multi_factor_acceleration_score_derivative, 2)), 20)) |
||||
|
||||
reverse(ts_delta(ts_mean(multiply(ts_zscore(fscore_total, 5), ts_zscore(multi_factor_acceleration_score_derivative, 5)), 10), 5)) |
||||
|
||||
reverse(ts_corr(ts_sum(fscore_total, 10), ts_delta(multi_factor_acceleration_score_derivative, 10), 20)) |
||||
|
||||
reverse(ts_sum(multiply(sign(ts_delta(fscore_total, 1)), ts_delta(multi_factor_acceleration_score_derivative, 1)), 15)) |
||||
|
||||
reverse(ts_rank(divide(ts_sum(fscore_total, 5), ts_sum(multi_factor_acceleration_score_derivative, 5)), 20)) |
||||
|
||||
reverse(ts_mean(divide(subtract(ts_delta(fscore_total, 2), ts_delta(multi_factor_acceleration_score_derivative, 2)), add(ts_std_dev(fscore_total, 5), ts_std_dev(multi_factor_acceleration_score_derivative, 5))), 10)) |
||||
|
||||
reverse(ts_corr(ts_backfill(fscore_total, 10), ts_backfill(multi_factor_acceleration_score_derivative, 10), 20)) |
||||
|
||||
reverse(ts_sum(if_else(ts_mean(fscore_total, 5) > ts_mean(multi_factor_acceleration_score_derivative, 5), 1, -1), 10)) |
||||
|
||||
reverse(ts_mean(multiply(power(ts_delta(fscore_total, 1), 2), power(ts_delta(multi_factor_acceleration_score_derivative, 1), 2)), 15)) |
||||
|
||||
reverse(ts_delta(ts_corr(ts_zscore(fscore_total, 5), ts_sum(multi_factor_acceleration_score_derivative, 5), 10), 5)) |
||||
|
||||
reverse(ts_rank(add(ts_mean(fscore_total, 3), ts_mean(multi_factor_acceleration_score_derivative, 3)), 20)) |
||||
|
||||
reverse(divide(ts_sum(multiply(ts_zscore(fscore_total, 10), multi_factor_acceleration_score_derivative), 10), ts_sum(multi_factor_acceleration_score_derivative, 10))) |
||||
|
||||
reverse(ts_mean(subtract(ts_zscore(fscore_total, 10), ts_mean(multi_factor_acceleration_score_derivative, 10)), 15)) |
||||
|
||||
reverse(ts_corr(ts_delta(fscore_total, 5), ts_mean(multi_factor_acceleration_score_derivative, 5), 20)) |
||||
|
||||
reverse(ts_sum(if_else(ts_rank(fscore_total, 5) > ts_rank(multi_factor_acceleration_score_derivative, 5), ts_delta(fscore_total, 1), ts_delta(multi_factor_acceleration_score_derivative, 1)), 10)) |
||||
|
||||
reverse(ts_mean(multiply(ts_scale(fscore_total, 5), ts_scale(multi_factor_acceleration_score_derivative, 5)), 15)) |
||||
|
||||
reverse(ts_delta(ts_rank(divide(fscore_total, multi_factor_acceleration_score_derivative), 10), 5)) |
||||
|
||||
reverse(ts_corr(ts_sum(fscore_total, 3), ts_zscore(multi_factor_acceleration_score_derivative, 3), 15)) |
||||
|
||||
reverse(ts_sum(multiply(abs(ts_delta(fscore_total, 2)), sign(ts_delta(multi_factor_acceleration_score_derivative, 2))), 10)) |
||||
|
||||
reverse(ts_rank(subtract(ts_product(fscore_total, 3), ts_product(multi_factor_acceleration_score_derivative, 3)), 20)) |
||||
|
||||
reverse(ts_mean(divide(add(ts_delta(fscore_total, 1), ts_delta(multi_factor_acceleration_score_derivative, 1)), add(ts_std_dev(fscore_total, 5), 1)), 10)) |
||||
|
||||
reverse(ts_corr(ts_backfill(fscore_total, 3), ts_zscore(multi_factor_acceleration_score_derivative, 3), 15)) |
||||
|
||||
reverse(ts_sum(if_else(ts_mean(fscore_total, 10) > ts_mean(multi_factor_acceleration_score_derivative, 10), ts_delta(fscore_total, 2), 0), 10)) |
||||
|
||||
reverse(ts_mean(multiply(signed_power(ts_zscore(fscore_total, 3), 3), signed_power(ts_zscore(multi_factor_acceleration_score_derivative, 3), 3)), 20)) |
||||
|
||||
reverse(ts_delta(ts_corr(ts_decay_linear(fscore_total, 5), ts_mean(multi_factor_acceleration_score_derivative, 5), 10), 5)) |
||||
|
||||
reverse(ts_rank(add(ts_av_diff(fscore_total, 10), ts_av_diff(multi_factor_acceleration_score_derivative, 10)), 20)) |
||||
|
||||
reverse(divide(ts_sum(multiply(fscore_total, ts_zscore(multi_factor_acceleration_score_derivative, 5)), 10), ts_sum(fscore_total, 10))) |
||||
|
||||
reverse(ts_mean(subtract(ts_sum(fscore_total, 5), ts_sum(multi_factor_acceleration_score_derivative, 5)), 15)) |
||||
|
||||
reverse(ts_corr(ts_delta(fscore_total, 2), ts_delta(multi_factor_acceleration_score_derivative, 2), 20)) |
||||
|
||||
reverse(ts_sum(if_else(ts_zscore(fscore_total, 20) > 1, ts_delta(multi_factor_acceleration_score_derivative, 1), -1), 10)) |
||||
|
||||
reverse(ts_mean(multiply(ts_rank(fscore_total, 20), ts_rank(multi_factor_acceleration_score_derivative, 20)), 20)) |
||||
|
||||
reverse(ts_delta(ts_mean(multiply(ts_delta(fscore_total, 1), ts_delta(multi_factor_acceleration_score_derivative, 1)), 10), 5)) |
||||
|
||||
reverse(ts_corr(ts_sum(fscore_total, 20), ts_sum(multi_factor_acceleration_score_derivative, 20), 20)) |
||||
|
||||
reverse(ts_sum(multiply(sign(ts_delta(fscore_total, 3)), abs(ts_delta(multi_factor_acceleration_score_derivative, 3))), 15)) |
||||
|
||||
reverse(ts_rank(divide(ts_mean(fscore_total, 10), ts_mean(multi_factor_acceleration_score_derivative, 10)), 20)) |
||||
|
||||
reverse(ts_mean(divide(subtract(ts_mean(fscore_total, 3), ts_mean(multi_factor_acceleration_score_derivative, 3)), add(ts_std_dev(fscore_total, 10), ts_std_dev(multi_factor_acceleration_score_derivative, 10))), 10)) |
||||
|
||||
reverse(ts_corr(ts_backfill(fscore_total, 20), ts_backfill(multi_factor_acceleration_score_derivative, 20), 20)) |
||||
|
||||
reverse(ts_sum(if_else(ts_rank(fscore_total, 10) > 0.5, ts_delta(fscore_total, 1), ts_delta(multi_factor_acceleration_score_derivative, 1)), 10)) |
||||
|
||||
reverse(ts_mean(multiply(power(ts_delta(fscore_total, 2), 2), power(ts_delta(multi_factor_acceleration_score_derivative, 2), 2)), 15)) |
||||
|
||||
reverse(ts_delta(ts_corr(ts_zscore(fscore_total, 10), ts_mean(multi_factor_acceleration_score_derivative, 10), 10), 5)) |
||||
|
||||
reverse(ts_rank(add(ts_mean(fscore_total, 5), ts_mean(multi_factor_acceleration_score_derivative, 5)), 20)) |
||||
|
||||
reverse(divide(ts_sum(multiply(ts_zscore(fscore_total, 5), ts_rank(multi_factor_acceleration_score_derivative, 10)), 10), ts_sum(multi_factor_acceleration_score_derivative, 10))) |
||||
|
||||
reverse(ts_mean(subtract(ts_zscore(fscore_total, 15), ts_zscore(multi_factor_acceleration_score_derivative, 15)), 10)) |
||||
|
||||
reverse(ts_corr(ts_delta(fscore_total, 10), ts_delta(multi_factor_acceleration_score_derivative, 10), 20)) |
||||
|
||||
reverse(ts_sum(if_else(ts_mean(fscore_total, 20) > ts_mean(multi_factor_acceleration_score_derivative, 20), 1, 0), 10)) |
||||
|
||||
reverse(ts_mean(multiply(ts_scale(fscore_total, 20), ts_scale(multi_factor_acceleration_score_derivative, 20)), 20)) |
||||
|
||||
reverse(ts_delta(ts_rank(multiply(ts_zscore(fscore_total, 5), ts_zscore(multi_factor_acceleration_score_derivative, 5)), 10), 5)) |
||||
|
||||
reverse(ts_corr(ts_sum(fscore_total, 15), ts_sum(multi_factor_acceleration_score_derivative, 15), 20)) |
||||
|
||||
reverse(ts_sum(multiply(sign(ts_delta(fscore_total, 5)), ts_delta(multi_factor_acceleration_score_derivative, 5)), 15)) |
||||
|
||||
reverse(ts_rank(subtract(ts_product(fscore_total, 5), ts_product(multi_factor_acceleration_score_derivative, 5)), 20)) |
||||
|
||||
reverse(ts_mean(divide(add(ts_delta(fscore_total, 3), ts_delta(multi_factor_acceleration_score_derivative, 3)), add(ts_std_dev(fscore_total, 10), 1)), 10)) |
||||
|
||||
reverse(ts_corr(ts_backfill(fscore_total, 15), ts_backfill(multi_factor_acceleration_score_derivative, 15), 20)) |
||||
|
||||
reverse(ts_sum(if_else(ts_zscore(fscore_total, 10) > ts_zscore(multi_factor_acceleration_score_derivative, 10), ts_delta(fscore_total, 2), 0), 10)) |
||||
|
||||
reverse(ts_mean(multiply(signed_power(ts_zscore(fscore_total, 10), 2), signed_power(ts_zscore(multi_factor_acceleration_score_derivative, 10), 2)), 20)) |
||||
|
||||
reverse(ts_delta(ts_corr(ts_decay_linear(fscore_total, 10), ts_decay_linear(multi_factor_acceleration_score_derivative, 10), 10), 5)) |
||||
|
||||
reverse(ts_rank(add(ts_av_diff(fscore_total, 20), ts_av_diff(multi_factor_acceleration_score_derivative, 20)), 20)) |
||||
|
||||
reverse(divide(ts_sum(multiply(fscore_total, ts_delta(multi_factor_acceleration_score_derivative, 2)), 10), ts_sum(fscore_total, 10))) |
||||
|
||||
reverse(ts_mean(subtract(ts_sum(fscore_total, 10), ts_sum(multi_factor_acceleration_score_derivative, 10)), 15)) |
||||
|
||||
reverse(ts_corr(ts_delta(fscore_total, 15), ts_delta(multi_factor_acceleration_score_derivative, 15), 20)) |
||||
|
||||
reverse(ts_sum(if_else(ts_rank(fscore_total, 20) > 0.7, ts_delta(fscore_total, 1), ts_delta(multi_factor_acceleration_score_derivative, 1)), 10)) |
||||
|
||||
reverse(ts_mean(multiply(power(ts_delta(fscore_total, 3), 2), power(ts_delta(multi_factor_acceleration_score_derivative, 3), 2)), 15)) |
||||
|
||||
reverse(ts_delta(ts_corr(ts_zscore(fscore_total, 20), ts_sum(multi_factor_acceleration_score_derivative, 20), 10), 5)) |
||||
|
||||
reverse(ts_rank(add(ts_mean(fscore_total, 10), ts_mean(multi_factor_acceleration_score_derivative, 10)), 20)) |
||||
|
||||
reverse(divide(ts_sum(multiply(ts_zscore(fscore_total, 20), ts_zscore(multi_factor_acceleration_score_derivative, 20)), 10), ts_sum(multi_factor_acceleration_score_derivative, 10))) |
||||
|
||||
reverse(ts_mean(subtract(ts_zscore(fscore_total, 20), ts_mean(multi_factor_acceleration_score_derivative, 20)), 10)) |
||||
@ -0,0 +1,382 @@ |
||||
任务指令 |
||||
1. 损益表与现金流（确认增长质量和动力） |
||||
必需：营业收入、销售额、营收 |
||||
强力推荐：经营性现金流、营业利润、扣非净利润 |
||||
相关：毛利率、销售费用、管理费用、财务费用 |
||||
2. 市场估值与预期（捕捉预期差与市场情绪） |
||||
必需：总市值、流通市值 |
||||
强力推荐：市盈率、市净率、市销率 |
||||
高级推荐：分析师一致预期净利润、盈利预测上调下调次数、目标价 |
||||
3. 财务风险与稳健性（规避财务陷阱） |
||||
必需：总资产、总负债、股东权益 |
||||
强力推荐：资产负债率、流动比率、速动比率 |
||||
相关：利息保障倍数、Z-Score 财务困境指标 |
||||
4. 行业与板块分类（实现行业中性化或行业内选股） |
||||
必需：行业分类代码、行业名称（建议采用申万、中信等标准） |
||||
相关：板块分类（如主板、创业板、科创板） |
||||
5. 量价与市场数据（结合技术面确认趋势） |
||||
必需：收盘价、复权价格 |
||||
强力推荐：成交量、成交额 |
||||
相关：换手率、历史收益率 |
||||
6. 宏观经济与市场基准（控制宏观及市场风险暴露） |
||||
相关：无风险利率、市场收益率、行业指数收益率 |
||||
*=========================================================================================* |
||||
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。 |
||||
**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： |
||||
|
||||
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, |
||||
Description: 此字段后面的是操作符对应的描述或使用说明, 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), description_cn字段后面的内容是中文使用说明(不能使用) |
||||
|
||||
{'id': '81', 'data_set_name': 'cashflow', 'description': 'Cashflow (Annual)', 'description_cn': '现金流(年度)'} |
||||
{'id': '82', 'data_set_name': 'cashflow_dividends', 'description': 'Cash Dividends (Cash Flow)', 'description_cn': '现金股息（现金流）'} |
||||
{'id': '83', 'data_set_name': 'cashflow_fin', 'description': 'Financing Activities - Net Cash Flow', 'description_cn': '融资活动-净现金流量'} |
||||
{'id': '84', 'data_set_name': 'cashflow_invst', 'description': 'Investing Activities - Net Cash Flow', 'description_cn': '投资活动-净现金流量'} |
||||
{'id': '85', 'data_set_name': 'cashflow_op', 'description': 'Operating Activities - Net Cash Flow', 'description_cn': '经营活动-净现金流量'} |
||||
{'id': '118', 'data_set_name': 'fnd6_cibegni', 'description': 'Comp Inc - Beginning Net Income', 'description_cn': 'Comp Inc - 初始净收入'} |
||||
{'id': '139', 'data_set_name': 'fnd6_cptmfmq_oibdpq', 'description': 'Operating Income Before Depreciation - Quarterly', 'description_cn': '营业利润（扣除折旧）- 季度'} |
||||
{'id': '153', 'data_set_name': 'fnd6_cptnewqeventv110_nopiq', 'description': 'Non-Operating Income (Expense) - Total', 'description_cn': '非经营性收益(损失)-总计'} |
||||
{'id': '156', 'data_set_name': 'fnd6_cptnewqeventv110_oibdpq', 'description': 'Operating Income Before Depreciation - Quarterly', 'description_cn': '营业利润（不扣折旧）- 季度'} |
||||
{'id': '172', 'data_set_name': 'fnd6_cptnewqv1300_nopiq', 'description': 'Non-Operating Income (Expense) - Total', 'description_cn': '非经营性收入（支出）总额'} |
||||
{'id': '174', 'data_set_name': 'fnd6_cptnewqv1300_oiadpq', 'description': 'Operating Income After Depreciation - Quarterly', 'description_cn': '营业净利润-季度'} |
||||
{'id': '175', 'data_set_name': 'fnd6_cptnewqv1300_oibdpq', 'description': 'Operating Income Before Depreciation - Quarterly', 'description_cn': '运营收入（扣除折旧）- 季度'} |
||||
{'id': '215', 'data_set_name': 'fnd6_drc', 'description': 'Deferred Revenue - Current', 'description_cn': '未实现收入-当前'} |
||||
{'id': '216', 'data_set_name': 'fnd6_drlt', 'description': 'Deferred Revenue - Long-term', 'description_cn': '未实现收入_长期'} |
||||
{'id': '285', 'data_set_name': 'fnd6_idit', 'description': 'Interest and Related Income - Total', 'description_cn': '利息及关联收入总计'} |
||||
{'id': '286', 'data_set_name': 'fnd6_iints', 'description': 'Interest Income', 'description_cn': '利息收入'} |
||||
{'id': '297', 'data_set_name': 'fnd6_itci', 'description': 'Investment Tax Credit (Income Account)', 'description_cn': '投资税信贷（收入账户）'} |
||||
{'id': '306', 'data_set_name': 'fnd6_lcoxdr', 'description': 'Current Liabilities - Other - Excluding Deferred Revenue', 'description_cn': '当前负债-其他-不包括递延收入'} |
||||
{'id': '311', 'data_set_name': 'fnd6_loxdr', 'description': 'Liabilities - Other - Excluding Deferred Revenue', 'description_cn': '负债-其他-不包括递延收入'} |
||||
{'id': '320', 'data_set_name': 'fnd6_mfma1_dpc', 'description': 'Depreciation and Amortization (Cash Flow)', 'description_cn': '现金流折旧与摊销'} |
||||
{'id': '322', 'data_set_name': 'fnd6_mfma2_oancf', 'description': 'Operating Activities - Net Cash Flow', 'description_cn': '经营活动-净现金流量'} |
||||
{'id': '325', 'data_set_name': 'fnd6_mfma2_revt', 'description': 'Revenue - Total', 'description_cn': '总收入-总金额'} |
||||
{'id': '379', 'data_set_name': 'fnd6_newa1v1300_dpc', 'description': 'Depreciation and Amortization (Cash Flow)', 'description_cn': '折旧与摊销（现金流）'} |
||||
{'id': '380', 'data_set_name': 'fnd6_newa1v1300_dv', 'description': 'Cash Dividends (Cash Flow)', 'description_cn': '现金股息（现金流）'} |
||||
{'id': '391', 'data_set_name': 'fnd6_newa1v1300_fincf', 'description': 'Financing Activities - Net Cash Flow', 'description_cn': '融资活动-净现金流量'} |
||||
{'id': '396', 'data_set_name': 'fnd6_newa1v1300_ibc', 'description': 'Income Before Extraordinary Items (Cash Flow)', 'description_cn': '现金流量前利润'} |
||||
{'id': '402', 'data_set_name': 'fnd6_newa1v1300_ivncf', 'description': 'Investing Activities - Net Cash Flow', 'description_cn': '投资活动-净现金流量'} |
||||
{'id': '411', 'data_set_name': 'fnd6_newa2v1300_nopi', 'description': 'Nonoperating Income (Expense)', 'description_cn': '非经营性收益(支出)'} |
||||
{'id': '412', 'data_set_name': 'fnd6_newa2v1300_oancf', 'description': 'Operating Activities - Net Cash Flow', 'description_cn': '运营活动-净现金流'} |
||||
{'id': '413', 'data_set_name': 'fnd6_newa2v1300_oiadp', 'description': 'Operating Income After Depreciation', 'description_cn': '营业净利润 after depreciation 不变，无需翻译。请提供需要翻译的专业字段名。'} |
||||
{'id': '414', 'data_set_name': 'fnd6_newa2v1300_oibdp', 'description': 'Operating Income Before Depreciation', 'description_cn': '营业利润前折旧'} |
||||
{'id': '429', 'data_set_name': 'fnd6_newa2v1300_revt', 'description': 'Revenue - Total', 'description_cn': '总收入_-_总计'} |
||||
{'id': '445', 'data_set_name': 'fnd6_newa2v1300_xidoc', 'description': 'Extraordinary Items and Discontinued Operations (Cash Flow)', 'description_cn': '非常项目及终止经营（现金流量）'} |
||||
{'id': '498', 'data_set_name': 'fnd6_newqeventv110_drltq', 'description': 'Deferred Revenue - Long-term', 'description_cn': '未实现收入_长期'} |
||||
{'id': '545', 'data_set_name': 'fnd6_newqeventv110_loxdrq', 'description': 'Liabilities - Other - Excluding Deferred Revenue', 'description_cn': '负债-其他-不包括递延收入'} |
||||
{'id': '707', 'data_set_name': 'fnd6_newqv1300_drcq', 'description': 'Deferred Revenue - Current', 'description_cn': '未实现收入-当前'} |
||||
{'id': '708', 'data_set_name': 'fnd6_newqv1300_drltq', 'description': 'Deferred Revenue - Long-term', 'description_cn': '未实现收入_长期'} |
||||
{'id': '720', 'data_set_name': 'fnd6_newqv1300_ibadjq', 'description': 'Income Before Extraordinary Items - Adjusted for Common Stock Equivalents', 'description_cn': '收入剔除非经常性项目后调整普通股等值股前'} |
||||
{'id': '739', 'data_set_name': 'fnd6_newqv1300_loxdrq', 'description': 'Liabilities - Other - Excluding Deferred Revenue', 'description_cn': '负债_其他_不包括递延收入'} |
||||
{'id': '770', 'data_set_name': 'fnd6_newqv1300_revtq', 'description': 'Revenue - Total', 'description_cn': '总收入-总计'} |
||||
{'id': '808', 'data_set_name': 'fnd6_nopio', 'description': 'Nonoperating Income (Expense) - Other', 'description_cn': '非经营性收入（支出）- 其他'} |
||||
{'id': '809', 'data_set_name': 'fnd6_nopxs', 'description': 'Nonoperating Income (Expense) - excluding Interest', 'description_cn': '非经营性收益（损失）-除利息外'} |
||||
{'id': '815', 'data_set_name': 'fnd6_oelim', 'description': 'Other Eliminations (Income)', 'description_cn': '其他消除项（收入）'} |
||||
{'id': '817', 'data_set_name': 'fnd6_oibdps', 'description': 'Operating Income before Depreciation', 'description_cn': '营业利润前折旧'} |
||||
{'id': '866', 'data_set_name': 'fnd6_revts', 'description': 'Total Revenues', 'description_cn': '总收入'} |
||||
{'id': '886', 'data_set_name': 'fnd6_txbco', 'description': 'Excess Tax Benefit Stock Options - Cash Flow Operating', 'description_cn': '超额税盾股票期权-运营现金流'} |
||||
{'id': '887', 'data_set_name': 'fnd6_txbcof', 'description': 'Excess Tax Benefit of Stock Options - Cash Flow Financing', 'description_cn': '股票期权超额税收利益-现金流量融资'} |
||||
{'id': '893', 'data_set_name': 'fnd6_txdc', 'description': 'Deferred Taxes (Cash Flow)', 'description_cn': '延期税项（现金流）'} |
||||
{'id': '896', 'data_set_name': 'fnd6_txdi', 'description': 'Income Taxes - Deferred', 'description_cn': '递延所得税收入'} |
||||
{'id': '980', 'data_set_name': 'cashflow_efficiency_rank_derivative', 'description': 'Change in ranking for cash flow generation and profitability compared to previous period.', 'description_cn': '期权变动对现金流量生成及盈利能力较上一期的变化'} |
||||
{'id': '985', 'data_set_name': 'fscore_bfl_profitability', 'description': 'The purpose of this metric is to rank stock based on their ability to generate cash flows.', 'description_cn': '该指标的目的根据其产生现金流能力对股票进行排名。'} |
||||
{'id': '993', 'data_set_name': 'fscore_profitability', 'description': 'The purpose of this metric is to rank stock based on their ability to generate cash flows.', 'description_cn': '该指标的目的在于根据产生现金流的能力对股票进行排名。'} |
||||
{'id': '1021', 'data_set_name': 'actual_cashflow_per_share_value_quarterly', 'description': 'Cash Flow Per Share - actual value for the quarter', 'description_cn': '每股现金流量-本季度实际值'} |
||||
{'id': '1025', 'data_set_name': 'actual_sales_value_quarterly', 'description': 'Sales - Value in financial services income statement (in millions)', 'description_cn': '销售_金融服务收入表_价值（百万元）'} |
||||
{'id': '1051', 'data_set_name': 'anl4_af_cfps_value', 'description': 'Cash Flow Per Share - Actual Value', 'description_cn': '每股现金流实际值'} |
||||
{'id': '1055', 'data_set_name': 'anl4_afv4_cfps_high', 'description': 'Cash Flow Per Share - The highest estimation for the annual forecast', 'description_cn': '每股现金流-年度预测最高估计值'} |
||||
{'id': '1056', 'data_set_name': 'anl4_afv4_cfps_low', 'description': 'Cash Flow Per Share - The lowest estimation for the upcoming fiscal year', 'description_cn': '每股现金流量-即将到来财年的最低估计值'} |
||||
{'id': '1057', 'data_set_name': 'anl4_afv4_cfps_mean', 'description': 'Cash Flow Per Share - average of estimations for the annual frequency', 'description_cn': '每股现金流量-年度频率下估计值平均'} |
||||
{'id': '1058', 'data_set_name': 'anl4_afv4_cfps_median', 'description': 'Cash Flow Per Share - Median value among forecasts for the annual frequency', 'description_cn': '每股现金流量-年度频率预测中位值'} |
||||
{'id': '1059', 'data_set_name': 'anl4_afv4_cfps_number', 'description': 'Cash Flow Per Share - number of estimations for annual frequency', 'description_cn': '每股现金流量-年度频率估计数量'} |
||||
{'id': '1139', 'data_set_name': 'anl4_cff_flag', 'description': 'Cash Flow From Financing Activities - forecast type (revision/new/...)', 'description_cn': '融资活动现金流量-预测类型（修订版/新版本/...）'} |
||||
{'id': '1140', 'data_set_name': 'anl4_cff_high', 'description': 'Cash Flow From Financing - The highest of forecasted values', 'description_cn': '融资现金流量-最高预测值'} |
||||
{'id': '1141', 'data_set_name': 'anl4_cff_low', 'description': 'Cash Flow From Financing - The lowest estimation', 'description_cn': '融资现金流量-最低估计值'} |
||||
{'id': '1142', 'data_set_name': 'anl4_cff_mean', 'description': 'Cash Flow From Financing - mean of estimations', 'description_cn': '融资现金流-估算均值'} |
||||
{'id': '1143', 'data_set_name': 'anl4_cff_median', 'description': 'Cash Flow From Financing Activities - Median value among forecasts', 'description_cn': '现金流从融资活动-预测中值'} |
||||
{'id': '1144', 'data_set_name': 'anl4_cff_number', 'description': 'Cash Flow From Financing - number of estimations', 'description_cn': '融资现金流-估测次数'} |
||||
{'id': '1145', 'data_set_name': 'anl4_cff_value', 'description': 'Cash Flow From Financing - announced financial value', 'description_cn': '现金流从融资-宣布的财务价值'} |
||||
{'id': '1146', 'data_set_name': 'anl4_cfi_flag', 'description': 'Cash Flow From Investing - forecast type (revision/new/...)', 'description_cn': '现金流从投资-预测类型（修订/新...）'} |
||||
{'id': '1147', 'data_set_name': 'anl4_cfi_high', 'description': 'Cash Flow From Investing - The highest estimation', 'description_cn': '现金流入投资-最高估计值'} |
||||
{'id': '1148', 'data_set_name': 'anl4_cfi_low', 'description': 'Cash Flow From Investing - The lowest estimation', 'description_cn': '投资现金流量-最低估计值'} |
||||
{'id': '1149', 'data_set_name': 'anl4_cfi_mean', 'description': 'Cash Flow From Investing - mean of estimations', 'description_cn': '投资现金流量-估算均值'} |
||||
{'id': '1150', 'data_set_name': 'anl4_cfi_median', 'description': 'Cash Flow From Investing - median of estimations', 'description_cn': '投资现金流量-估测中位数'} |
||||
{'id': '1151', 'data_set_name': 'anl4_cfi_number', 'description': 'Cash Flow From Investing - number of estimations', 'description_cn': '投资现金流-估测数量'} |
||||
{'id': '1152', 'data_set_name': 'anl4_cfi_value', 'description': 'Cash Flow From Investing - announced financial value', 'description_cn': '投资现金流-宣布的财务价值'} |
||||
{'id': '1153', 'data_set_name': 'anl4_cfo_flag', 'description': 'Cash Flow From Operations - forecast type (revision/new/...)', 'description_cn': '现金流（运营）- 预测类型（修订/新...）'} |
||||
{'id': '1154', 'data_set_name': 'anl4_cfo_high', 'description': 'Cash Flow From Operations - The highest value among forecasts', 'description_cn': '现金流量从运营-预测中的最高值'} |
||||
{'id': '1155', 'data_set_name': 'anl4_cfo_low', 'description': 'Cash Flow From Operations - The lowest estimation', 'description_cn': '现金流从运营活动-最低估计值'} |
||||
{'id': '1156', 'data_set_name': 'anl4_cfo_mean', 'description': 'Cash Flow From Operations - mean of estimations', 'description_cn': '运营现金流-估测均值'} |
||||
{'id': '1157', 'data_set_name': 'anl4_cfo_median', 'description': 'Cash Flow From Operations - median of estimations', 'description_cn': '运营现金流-估计值中位数'} |
||||
{'id': '1158', 'data_set_name': 'anl4_cfo_number', 'description': 'Cash Flow From Operations - number of estimations', 'description_cn': '现金流-运营活动-估计次数'} |
||||
{'id': '1159', 'data_set_name': 'anl4_cfo_value', 'description': 'Cash Flow From Operations - announced financial value', 'description_cn': '现金流从运营-公告财务值'} |
||||
{'id': '1241', 'data_set_name': 'anl4_fcf_flag', 'description': 'Free cash flow - forecast type (revision/new/...)', 'description_cn': '自由现金流-预测类型（修订/新/...）'} |
||||
{'id': '1242', 'data_set_name': 'anl4_fcf_high', 'description': 'Free cash flow - aggregation on estimations, max', 'description_cn': '自由现金流_估测聚合_最大'} |
||||
{'id': '1243', 'data_set_name': 'anl4_fcf_low', 'description': 'Free Cash Flow - The lowest estimation', 'description_cn': '自由现金流 - 最低估计值'} |
||||
{'id': '1244', 'data_set_name': 'anl4_fcf_mean', 'description': 'Free Cash Flow - mean of estimations', 'description_cn': '自由现金流_估计值平均值'} |
||||
{'id': '1245', 'data_set_name': 'anl4_fcf_median', 'description': 'Free cash flow - aggregation on estimations, 50th percentile', 'description_cn': '自由现金流-估计值聚合_50百分位'} |
||||
{'id': '1246', 'data_set_name': 'anl4_fcf_number', 'description': 'Free Cash Flow - number of estimations', 'description_cn': '自由现金流-估算数量'} |
||||
{'id': '1247', 'data_set_name': 'anl4_fcf_value', 'description': 'Free cash flow- announced financial value', 'description_cn': '自由现金流-公告财务值'} |
||||
{'id': '1248', 'data_set_name': 'anl4_fcfps_flag', 'description': 'Free cash flow per share - forecast type (revision/new/...)', 'description_cn': '每股自由现金流-预测类型（修订/新...）'} |
||||
{'id': '1249', 'data_set_name': 'anl4_fcfps_high', 'description': 'Free Cash Flow Per Share - the highest estimation', 'description_cn': '每股自由现金流-最高估计值'} |
||||
{'id': '1250', 'data_set_name': 'anl4_fcfps_low', 'description': 'Free Cash Flow Per Share - the lowest estimation', 'description_cn': '每股自由现金流量-最低估计值'} |
||||
{'id': '1251', 'data_set_name': 'anl4_fcfps_mean', 'description': 'Free cash flow per share - mean of estimations', 'description_cn': '每股自由现金流-估计值平均数'} |
||||
{'id': '1252', 'data_set_name': 'anl4_fcfps_median', 'description': 'Free cash flow - summary on estimations, 50th-percentile, per share', 'description_cn': '自由现金流_估测摘要_第50百分位_每股'} |
||||
{'id': '1253', 'data_set_name': 'anl4_fcfps_number', 'description': 'Free Cash Flow per Share - number of estimations', 'description_cn': '每股自由现金流-估算次数'} |
||||
{'id': '1277', 'data_set_name': 'anl4_gric_high', 'description': 'Gross income - The highest estimation', 'description_cn': '预计总收入'} |
||||
{'id': '1283', 'data_set_name': 'anl4_gric_value', 'description': 'Gross income- announced financial value', 'description_cn': '总收入-公告财务价值'} |
||||
{'id': '1327', 'data_set_name': 'anl4_qf_az_cfps_mean', 'description': 'Cash Flow Per Share - average of estimations', 'description_cn': '每股现金流量-平均估计值'} |
||||
{'id': '1328', 'data_set_name': 'anl4_qf_az_cfps_median', 'description': 'Cash Flow Per Share - Median value among forecasts', 'description_cn': '每股现金流中位数-预测值'} |
||||
{'id': '1329', 'data_set_name': 'anl4_qf_az_cfps_number', 'description': 'Cash Flow Per Share - number of estimations', 'description_cn': '每股现金流-估算次数'} |
||||
{'id': '1341', 'data_set_name': 'anl4_qf_az_wol_spfc', 'description': 'Cash Flow Per Share - The lowest estimation', 'description_cn': '每股现金流-最低估计值'} |
||||
{'id': '1343', 'data_set_name': 'anl4_qfd1_az_cfps_median', 'description': 'Cash Flow Per Share - Median value among forecasts', 'description_cn': '每股现金流量-预测值中的中位数'} |
||||
{'id': '1344', 'data_set_name': 'anl4_qfd1_az_cfps_number', 'description': 'Cash Flow Per Share - number of estimations', 'description_cn': '每股现金流量-估算次数'} |
||||
{'id': '1353', 'data_set_name': 'anl4_qfd1_az_wol_spfc', 'description': 'Cash Flow Per Share - The lowest estimation', 'description_cn': '每股现金流-最低估计'} |
||||
{'id': '1357', 'data_set_name': 'anl4_qfv4_cfps_high', 'description': 'Cash Flow Per Share - The highest estimation for the quarter', 'description_cn': '每股现金流-该季度最高估计值'} |
||||
{'id': '1358', 'data_set_name': 'anl4_qfv4_cfps_low', 'description': 'Cash Flow Per Share - The lowest estimation', 'description_cn': '每股现金流-最低估计值'} |
||||
{'id': '1359', 'data_set_name': 'anl4_qfv4_cfps_mean', 'description': 'Cash Flow Per Share - average of estimations', 'description_cn': '每股现金流量-估计值平均'} |
||||
{'id': '1360', 'data_set_name': 'anl4_qfv4_cfps_median', 'description': 'Cash Flow Per Share - Median value among forecasts', 'description_cn': '每股现金流量-预测中的中位数值'} |
||||
{'id': '1361', 'data_set_name': 'anl4_qfv4_cfps_number', 'description': 'Cash Flow Per Share - number of estimations', 'description_cn': '每股现金流-估测次数'} |
||||
{'id': '1410', 'data_set_name': 'capital_expenditure_reported_value', 'description': 'Capital Expenditures - Total (Cash Flow/Investing) (Millions)', 'description_cn': '资本支出-总计(现金流/投资)(百万)'} |
||||
{'id': '1411', 'data_set_name': 'cash_flow_financing_max_guidance', 'description': 'Cash Flow From Financing - Maximum guidance value provided annually', 'description_cn': '融资现金流量-每年提供的最大指导值'} |
||||
{'id': '1412', 'data_set_name': 'cash_flow_from_financing', 'description': 'Cash Flow From Financing - Value', 'description_cn': '现金流从融资-价值'} |
||||
{'id': '1413', 'data_set_name': 'cash_flow_from_investing', 'description': 'Cash Flow from Investing - Value', 'description_cn': '投资现金流-价值'} |
||||
{'id': '1414', 'data_set_name': 'cash_flow_from_operations', 'description': 'Cash Flow from Operations - Value for the annual period', 'description_cn': '营业现金流量-年度期间价值'} |
||||
{'id': '1415', 'data_set_name': 'cash_flow_operations_min_guidance', 'description': 'Minimum guidance value for Cash Flow from Operations on an annual basis.', 'description_cn': '年度经营现金流量最低指导值'} |
||||
{'id': '1416', 'data_set_name': 'cashflow_per_share_average', 'description': 'Cash Flow Per Share - average of estimations with a delay of 1 quarter', 'description_cn': '每股现金流量-延迟一个季度的估计平均值'} |
||||
{'id': '1417', 'data_set_name': 'cashflow_per_share_estimate_count', 'description': 'Cash Flow Per Share - number of estimations - delay1', 'description_cn': '每股现金流-估计次数-延迟1'} |
||||
{'id': '1418', 'data_set_name': 'cashflow_per_share_max_guidance', 'description': 'The maximum guidance value for Cash Flow Per Share on an annual basis.', 'description_cn': '每股现金流量年度上限值'} |
||||
{'id': '1419', 'data_set_name': 'cashflow_per_share_max_guidance_quarterly', 'description': 'The maximum guidance value for Cash Flow Per Share.', 'description_cn': '每股现金流量上限值'} |
||||
{'id': '1420', 'data_set_name': 'cashflow_per_share_maximum', 'description': 'Cash Flow - The highest estimation, per share, with a delay of 1 quarter', 'description_cn': '现金流量_每股最高估计_延迟一个季度'} |
||||
{'id': '1421', 'data_set_name': 'cashflow_per_share_median_value', 'description': 'Cash Flow Per Share - Median value among forecasts', 'description_cn': '每股现金流中位值-预测值'} |
||||
{'id': '1422', 'data_set_name': 'cashflow_per_share_min_guidance', 'description': 'Cash Flow Per Share - Minimum guidance value for the annual period', 'description_cn': '每股现金流-年度期间最小指导值'} |
||||
{'id': '1423', 'data_set_name': 'cashflow_per_share_min_guidance_quarterly', 'description': 'Minimum guidance value for Cash Flow Per Share', 'description_cn': '每股现金流最低指导值'} |
||||
{'id': '1424', 'data_set_name': 'cashflow_per_share_minimum', 'description': 'Cash Flow Per Share - The lowest estimation, delay 1 quarter', 'description_cn': '每股现金流量-延迟一个季度的最低估计值'} |
||||
{'id': '1462', 'data_set_name': 'est_cashflow_fin', 'description': 'Cash Flow From Financing - mean of estimations', 'description_cn': '融资现金流-估计值均值'} |
||||
{'id': '1463', 'data_set_name': 'est_cashflow_invst', 'description': 'Cash Flow From Investing - mean of estimations', 'description_cn': '投资现金流-估算值均值'} |
||||
{'id': '1464', 'data_set_name': 'est_cashflow_op', 'description': 'Cash Flow From Operations - mean of estimations', 'description_cn': '运营现金流-估计值均值'} |
||||
{'id': '1465', 'data_set_name': 'est_cashflow_ps', 'description': 'Cash Flow Per Share - average of estimations', 'description_cn': '每股现金流量-估计值平均值'} |
||||
{'id': '1472', 'data_set_name': 'est_fcf', 'description': 'Free Cash Flow - Mean of Estimations', 'description_cn': '自由现金流-估算值平均值'} |
||||
{'id': '1473', 'data_set_name': 'est_fcf_ps', 'description': 'Free Cash Flow Per Share - Mean of Estimations', 'description_cn': '每股自由现金流-估计值平均值'} |
||||
{'id': '1475', 'data_set_name': 'est_grossincome', 'description': 'Gross income - Mean of estimations', 'description_cn': '总收入_估测均值'} |
||||
{'id': '1491', 'data_set_name': 'financing_cashflow_reported_value', 'description': 'Cash Flow From Financing - Value', 'description_cn': '融资现金流量-价值'} |
||||
{'id': '1492', 'data_set_name': 'free_cash_flow_per_share', 'description': 'Free cash flow per share - actual financial value for the annual period', 'description_cn': '每股自由现金流量-年度实际财务值'} |
||||
{'id': '1493', 'data_set_name': 'free_cash_flow_per_share_actual_value', 'description': 'Free cash flow per share- announced financial value', 'description_cn': '每股自由现金流量-宣布财务值'} |
||||
{'id': '1494', 'data_set_name': 'free_cash_flow_per_share_max_guidance', 'description': 'The maximum guidance value for Free Cash Flow Per Share on an annual basis.', 'description_cn': '年度每股自由现金流指导上限'} |
||||
{'id': '1495', 'data_set_name': 'free_cash_flow_per_share_reported_value', 'description': 'Free cash flow per share- announced financial value', 'description_cn': '每股自由现金流-公告财务值'} |
||||
{'id': '1496', 'data_set_name': 'free_cash_flow_reported_value', 'description': 'Free cash flow value for the quarter.', 'description_cn': '季度自由现金流值'} |
||||
{'id': '1497', 'data_set_name': 'free_cash_flow_total', 'description': 'Free Cash Flow value - Annual', 'description_cn': '自由现金流值-年度'} |
||||
{'id': '1500', 'data_set_name': 'gross_income_reported_value', 'description': 'Gross Income value for the quarter', 'description_cn': '季度总收入值'} |
||||
{'id': '1501', 'data_set_name': 'gross_income_total', 'description': 'Gross Income value on an annual basis', 'description_cn': '年度毛收入值'} |
||||
{'id': '1507', 'data_set_name': 'investing_cashflow_reported_value', 'description': 'Cash Flow from Investing - Value', 'description_cn': '投资现金流-价值'} |
||||
{'id': '1511', 'data_set_name': 'max_adjusted_funds_from_operations_adj_guidance', 'description': 'Adjusted funds from operation - Maximum guidance value', 'description_cn': '调整后经营活动净现金流-最大指导值'} |
||||
{'id': '1513', 'data_set_name': 'max_adjusted_funds_from_operations_guidance_2', 'description': 'Adjusted funds from operation - maximum guidance value for the annual period', 'description_cn': '调整后经营现金流-年度期间最大指导值'} |
||||
{'id': '1523', 'data_set_name': 'max_financing_cashflow_guidance', 'description': 'Cash Flow From Financing - Maximum guidance value', 'description_cn': '融资现金流-最大指导值'} |
||||
{'id': '1524', 'data_set_name': 'max_free_cash_flow_guidance', 'description': 'The maximum guidance value for Free Cash Flow on an annual basis.', 'description_cn': '年度自由现金流指导上限'} |
||||
{'id': '1525', 'data_set_name': 'max_free_cashflow_guidance', 'description': 'The maximum guidance value for Free Cash Flow.', 'description_cn': '自由现金流最大指导值'} |
||||
{'id': '1526', 'data_set_name': 'max_free_cashflow_per_share_guidance', 'description': 'The maximum guidance value for free cash flow per share.', 'description_cn': '每股自由现金流指导的最大值'} |
||||
{'id': '1527', 'data_set_name': 'max_gross_income_guidance', 'description': 'The maximum guidance value for Gross Income.', 'description_cn': '最大毛收入指导值'} |
||||
{'id': '1528', 'data_set_name': 'max_gross_income_guidance_2', 'description': 'The maximum guidance for Gross Income on an annual basis.', 'description_cn': '年度毛收入最大指导金额'} |
||||
{'id': '1529', 'data_set_name': 'max_investing_cashflow_guidance', 'description': 'The maximum guidance value for Cash Flow from Investing.', 'description_cn': '现金流从投资的最大指导值'} |
||||
{'id': '1530', 'data_set_name': 'max_investing_cashflow_guidance_2', 'description': 'The maximum guidance value for Cash Flow from Investing activities on an annual basis.', 'description_cn': '年度投资活动现金流量上限指导值'} |
||||
{'id': '1534', 'data_set_name': 'max_operating_cashflow_guidance', 'description': 'The maximum guidance value for Cash Flow from Operations.', 'description_cn': '运营现金流指导值上限'} |
||||
{'id': '1535', 'data_set_name': 'max_operating_cashflow_guidance_2', 'description': 'The maximum guidance value for Cash Flow from Operations on an annual basis.', 'description_cn': '年度运营现金流指导最大值'} |
||||
{'id': '1556', 'data_set_name': 'min_adjusted_funds_from_operations_guidance_2', 'description': 'Adjusted funds from operation - minimum guidance for the annual period', 'description_cn': '调整后经营活动产生的现金流量-年度期最低指导值'} |
||||
{'id': '1567', 'data_set_name': 'min_financing_cashflow_guidance', 'description': 'Minimum guidance value for Cash Flow From Financing', 'description_cn': '现金流从融资的最小指导值'} |
||||
{'id': '1568', 'data_set_name': 'min_financing_cashflow_guidance_2', 'description': 'Minimum guidance value for Cash Flow From Financing on an annual basis', 'description_cn': '年度融资现金流最小指导值'} |
||||
{'id': '1569', 'data_set_name': 'min_free_cash_flow_guidance', 'description': 'The minimum guidance value for Free Cash Flow on an annual basis.', 'description_cn': '年度自由现金流参考值(盈亏平衡点)'} |
||||
{'id': '1570', 'data_set_name': 'min_free_cash_flow_per_share_guidance', 'description': 'Free cash flow per share - minimum guidance value for the annual period', 'description_cn': '每股自由现金流-年度期间最低指导值'} |
||||
{'id': '1571', 'data_set_name': 'min_free_cashflow_guidance', 'description': 'Minimum guidance value for Free Cash Flow', 'description_cn': '自由现金流最低指导值'} |
||||
{'id': '1572', 'data_set_name': 'min_free_cashflow_per_share_guidance', 'description': 'Free cash flow per share - minimum guidance value', 'description_cn': '每股自由现金流-最低指导值'} |
||||
{'id': '1575', 'data_set_name': 'min_gross_income_guidance_2', 'description': 'The minimum guidance for Gross Income on an annual basis.', 'description_cn': '年度毛收入最低指导金额'} |
||||
{'id': '1576', 'data_set_name': 'min_investing_cashflow_guidance', 'description': 'Cash Flow From Investing - Minimum guidance value', 'description_cn': '投资现金流-最小指导值'} |
||||
{'id': '1577', 'data_set_name': 'min_investing_cashflow_guidance_2', 'description': 'Cash Flow From Investing - Minimum guidance value for the annual period', 'description_cn': '投资现金流-当年最低指导值'} |
||||
{'id': '1581', 'data_set_name': 'min_operating_cashflow_guidance', 'description': 'Minimum guidance value for Cash Flow from Operations', 'description_cn': '运营现金流最低指导值'} |
||||
{'id': '1599', 'data_set_name': 'minimum_guidance_value', 'description': 'Minimum guidance value for basic annual financials', 'description_cn': '基本年度财务报表最低指导值'} |
||||
{'id': '1610', 'data_set_name': 'operating_cashflow_reported_value', 'description': 'Cash Flow from Operations - Value', 'description_cn': '运营现金流量-价值'} |
||||
{'id': '2316', 'data_set_name': 'fn_accum_oth_income_loss_fx_adj_net_of_tax_a', 'description': 'Accumulated adjustment, net of tax, that results from the process of translating subsidiary financial statements and foreign equity investments into the reporting currency from the functional currency of the reporting entity, net of reclassification of realized foreign currency translation gains or losses.', 'description_cn': '累计折算净损益，减去税收影响，源自将附属财务报表及外币股权投资自报告实体的功能货币翻译为报导货币的过程，并减去重分类实现的外币折算收益或损失。'} |
||||
{'id': '2317', 'data_set_name': 'fn_accum_oth_income_loss_fx_adj_net_of_tax_q', 'description': 'Accumulated adjustment, net of tax, that results from the process of translating subsidiary financial statements and foreign equity investments into the reporting currency from the functional currency of the reporting entity, net of reclassification of realized foreign currency translation gains or losses.', 'description_cn': '累积折算调整，扣税后净额，源自将附属公司财务报表及外币投资从报告实体的功能货币转换为报告货币的过程，扣除重分类实现的外币折算损益净额。'} |
||||
{'id': '2318', 'data_set_name': 'fn_accum_oth_income_loss_net_of_tax_a', 'description': '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.', 'description_cn': '期末非业主来源交易及其他事件和情况引起的所有者权益累计变动，扣除税影响。不包括净利润（亏损），以及因所有者投资和向所有者分配引起的权益累计变动。包括外币折算项目、某些养老金调整、特定债务和股权证券未实现损益、除信贷损失外其他因素导致的持有至到期日和可供出售债务证券暂时性减值损失，以及与有效部分指定现金流量对冲相关的衍生工具公允价值变动。'} |
||||
{'id': '2319', 'data_set_name': 'fn_accum_oth_income_loss_net_of_tax_q', 'description': '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.', 'description_cn': '期末非股东来源交易及其他事件和情况引起的权益累计变动净额，扣税后，不包括净利润（亏损）、股东投资交易导致的权益累计变动及分配。包含外币折算项目、特定养老金调整、特定债权和股权证券未实现盈亏、除信用损失外其他暂时性减值（OTTI）亏损，以及指定现金流量对冲有效部分相关衍生工具公允价值变动。'} |
||||
{'id': '2412', 'data_set_name': 'fn_excess_tax_benefit_from_share_based_comp_fin_activities_a', 'description': "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.", 'description_cn': '现金流入实现税项利益金额（权益工具可扣除薪酬成本超出财务报告确认成本的税务回报）'} |
||||
{'id': '2413', 'data_set_name': 'fn_excess_tax_benefit_from_share_based_comp_fin_activities_q', 'description': "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.", 'description_cn': '实现的与权益工具可抵扣薪酬费用相关的税收利益现金流入超出财务报告目的确认薪酬费用的差额金额'} |
||||
{'id': '2427', 'data_set_name': 'fn_income_taxes_paid_q', 'description': 'The amount of cash paid during the current period to foreign, federal, state, and local authorities as taxes on income.', 'description_cn': '当前期间支付给外国、联邦、州和地方政府的应税收入现金金额'} |
||||
{'id': '2458', 'data_set_name': 'fn_op_lease_rent_exp_a', 'description': 'Rental expense for the reporting period incurred under operating leases, including minimum and any contingent rent expense, net of related sublease income.', 'description_cn': '报告期内按经营租赁计入的租金支出，包括最低及任何或有租金支出，并扣除相关次级租赁收入后的净额'} |
||||
{'id': '2465', 'data_set_name': 'fn_oth_income_loss_derivatives_qualifying_as_hedges_of_tax_a', 'description': "Amount after tax and reclassification adjustments, of increase (decrease) in accumulated gain (loss) from derivative instruments designated and qualifying as the effective portion of cash flow hedges and an entity's share of an equity investee's increase (decrease) in deferred hedging gain (loss).", 'description_cn': '税后调整后的累计衍生工具公允价值变动净额，及权益法核算下被投资单位累积盈亏变动调整后的现金流量套期有效部分及企业享有份额'} |
||||
{'id': '2466', 'data_set_name': 'fn_oth_income_loss_derivatives_qualifying_as_hedges_of_tax_q', 'description': "Amount after tax and reclassification adjustments, of increase (decrease) in accumulated gain (loss) from derivative instruments designated and qualifying as the effective portion of cash flow hedges and an entity's share of an equity investee's increase (decrease) in deferred hedging gain (loss).", 'description_cn': '税后调整后的衍生工具指定并符合条件的现金流量套期有效部分累计收益（损失）变动及实体对权益法投资企业累积未实现套期收益（损失）变动额'} |
||||
{'id': '2471', 'data_set_name': 'fn_payments_for_repurchase_of_common_stock_a', 'description': 'Value reported on Cash Flow Statement. May include shares repurchased as part of a buyback plan, as well as shares purchased for employee compensation, etc.', 'description_cn': '现金流量表报告的价值。可能包括作为回购计划一部分回购的股票，以及用于员工补偿等购买的股票等。- 盈亏平衡点'} |
||||
{'id': '2472', 'data_set_name': 'fn_payments_for_repurchase_of_common_stock_q', 'description': 'Value reported on Cash Flow Statement. May include shares repurchased as part of a buyback plan, as well as shares purchased for employee compensation, etc.', 'description_cn': '现金流量表中报告的价值。可能包括作为回购计划一部分回购的股票，以及用于员工补偿等购买的股票等。- 盈亏平衡点'} |
||||
{'id': '2473', 'data_set_name': 'fn_payments_to_acquire_businesses_net_of_cash_acquired_a', 'description': 'The cash outflow associated with the acquisition of a business, net of the cash acquired from the purchase.', 'description_cn': '并购现金流出净额'} |
||||
{'id': '2474', 'data_set_name': 'fn_payments_to_acquire_businesses_net_of_cash_acquired_q', 'description': 'The cash outflow associated with the acquisition of a business, net of the cash acquired from the purchase.', 'description_cn': '并购现金流出净额'} |
||||
{'id': '2479', 'data_set_name': 'fn_proceeds_from_issuance_of_common_stock_a', 'description': 'The cash inflow from the additional capital contribution to the entity.', 'description_cn': '额外资本贡献带来的现金流入'} |
||||
{'id': '2480', 'data_set_name': 'fn_proceeds_from_issuance_of_common_stock_q', 'description': 'The cash inflow from the additional capital contribution to the entity.', 'description_cn': '额外资本贡献现金流入'} |
||||
{'id': '2481', 'data_set_name': 'fn_proceeds_from_issuance_of_debt_a', 'description': 'The cash inflow during the period from additional borrowings in aggregate debt. Includes proceeds from short-term and long-term debt.', 'description_cn': '期间额外借款在内的现金流入总额。包括短期和长期债务的筹集资金。'} |
||||
{'id': '2482', 'data_set_name': 'fn_proceeds_from_issuance_of_debt_q', 'description': 'The cash inflow during the period from additional borrowings in aggregate debt. Includes proceeds from short-term and long-term debt.', 'description_cn': '额外债务合计借款期间的现金流入，包括短期和长期债务的收益。'} |
||||
{'id': '2485', 'data_set_name': 'fn_proceeds_from_stock_options_exercised_a', 'description': 'The cash inflow associated with the amount received from holders exercising their stock options. This item inherently excludes any excess tax benefit, which the entity may have realized and reported separately.', 'description_cn': '与持有人行权收到的股票期权金额相关的现金流入。此项目本质上不包括任何单独列报和报告的超额税收利益。'} |
||||
{'id': '2486', 'data_set_name': 'fn_proceeds_from_stock_options_exercised_q', 'description': 'The cash inflow associated with the amount received from holders exercising their stock options. This item inherently excludes any excess tax benefit, which the entity may have realized and reported separately.', 'description_cn': '与持有人行权收到的股票期权金额相关的现金流入。此项目本质上不包括任何单独列报和报告的超额税务收益。'} |
||||
{'id': '2489', 'data_set_name': 'fn_repayments_of_debt_a', 'description': 'The cash outflow during the period from the repayment of aggregate short-term and long-term debt. Excludes payment of capital lease obligations.', 'description_cn': '偿还短期及长期债务期间的现金流出（不包括资本租赁付款）'} |
||||
{'id': '2490', 'data_set_name': 'fn_repayments_of_debt_q', 'description': 'The cash outflow during the period from the repayment of aggregate short-term and long-term debt. Excludes payment of capital lease obligations.', 'description_cn': '短期及长期债务偿还期间的现金流出（不包括资本租赁付款）'} |
||||
{'id': '2491', 'data_set_name': 'fn_repayments_of_lines_of_credit_a', 'description': 'Amount of cash outflow for payment of an obligation from a lender, including but not limited to, letter of credit, standby letter of credit and revolving credit arrangements.', 'description_cn': '贷款义务支付的现金流出金额，包括但不限于信用证、备用信用证和循环信贷安排。- 贷款义务支付现金流出金额'} |
||||
{'id': '2492', 'data_set_name': 'fn_repayments_of_lines_of_credit_q', 'description': 'Amount of cash outflow for payment of an obligation from a lender, including but not limited to, letter of credit, standby letter of credit and revolving credit arrangements.', 'description_cn': '贷款义务支付的现金流出金额，包括但不限于信用证、备用信用证和循环信贷安排。- 贷款义务现金流出金额'} |
||||
{'id': '2493', 'data_set_name': 'fn_repayments_of_lt_debt_a', 'description': 'The cash outflow for debt initially having maturity due after 1 year or beyond the normal operating cycle, if longer.', 'description_cn': '债务初始到期日超过1年或正常经营周期（取较长者）的现金流出量'} |
||||
{'id': '2494', 'data_set_name': 'fn_repayments_of_lt_debt_q', 'description': 'The cash outflow for debt initially having maturity due after 1 year or beyond the normal operating cycle, if longer.', 'description_cn': '债务初始到期日在一年或正常经营周期以上现金流出'} |
||||
{'id': '2499', 'data_set_name': 'fn_taxes_payable_a', 'description': 'Carrying value as of the balance sheet date of obligations incurred and payable for statutory income, sales, use, payroll, excise, real, property, and other taxes. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).', 'description_cn': '履约价值_报表日_应付税费_法定利润_销售收入_销售税_使用税_工资税_特定消费税_房地产税及其他税费_盈亏平衡点_分类资产负债表_流动负债_未分类资产负债表_总负债_无到期日限制'} |
||||
{'id': '2504', 'data_set_name': 'fnd2_a_acmopclcchngcfectnt', 'description': "Accumulated change, net of tax, in accumulated gains and losses from derivative instruments designated and qualifying as the effective portion of cash flow hedges. Includes an entity's share of an equity investee's Increase or Decrease in deferred hedging gains or losses.", 'description_cn': '期权衍生工具指定并符合现金流量套期有效部分的累计净损益变动，包括实体对权益法核算长期股权投资的累积未实现套期收益或损失的变化。'} |
||||
{'id': '2510', 'data_set_name': 'fnd2_a_bnsacqproformarvn', 'description': 'The pro forma revenue for a period as if the business combination or combinations had been completed at the beginning of the period.', 'description_cn': '会计期初完成企业合并时的预期收入'} |
||||
{'id': '2523', 'data_set_name': 'fnd2_a_excesstxbnffsbcpnoprat', 'description': "Amount of cash outflow for 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.", 'description_cn': '税前补偿成本可抵扣金额超出财务报告中认可金额并在实体税务申报表中实现的税收利益现金流出量'} |
||||
{'id': '2549', 'data_set_name': 'fnd2_a_ptoacqbnsesg', 'description': 'The cash outflow associated with the acquisition of business during the period. The cash portion only of the acquisition price.', 'description_cn': '期权行权期间企业收购相关的现金流出（仅现金部分）收购价格'} |
||||
{'id': '2551', 'data_set_name': 'fnd2_a_rvndm', 'description': 'Revenue, Domestic', 'description_cn': '国内收入'} |
||||
{'id': '2600', 'data_set_name': 'fnd2_itxreclnondeductibleexp', 'description': '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.', 'description_cn': '报告的所得税费用（收益）与预期所得税费用（收益）之间的差额计算方法：将继续经营业务产生的应税收入（亏损）中不可抵扣费用部分应用国内联邦法定所得税率计算得出的预期所得税费用（收益）。'} |
||||
{'id': '2601', 'data_set_name': 'fnd2_itxreclstatelocalitxes', 'description': '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 state and local income tax expense (benefit).', 'description_cn': '差额所得税费用（ benefit ）与按国内联邦法定所得税率计算的预计所得税费用（ benefit ）金额（从持续经营业务税前利润中归属于州及地方政府所得税费用（ benefit ）部分）'} |
||||
{'id': '2602', 'data_set_name': 'fnd2_itxreexftfedstyitxrt', 'description': 'Income tax amount computed at the federal tax rate, before any adjustments', 'description_cn': '联邦税率计算的收入税金额（未调整前）'} |
||||
{'id': '2611', 'data_set_name': 'fnd2_q_bnsacqproformarvn', 'description': 'The pro forma revenue for a period as if the business combination or combinations had been completed at the beginning of the period.', 'description_cn': '预计合并期间的收入'} |
||||
========================= 数据字段结束 ======================================= |
||||
|
||||
@ -0,0 +1,382 @@ |
||||
任务指令 |
||||
1. 损益表与现金流（确认增长质量和动力） |
||||
必需：营业收入、销售额、营收 |
||||
强力推荐：经营性现金流、营业利润、扣非净利润 |
||||
相关：毛利率、销售费用、管理费用、财务费用 |
||||
2. 市场估值与预期（捕捉预期差与市场情绪） |
||||
必需：总市值、流通市值 |
||||
强力推荐：市盈率、市净率、市销率 |
||||
高级推荐：分析师一致预期净利润、盈利预测上调下调次数、目标价 |
||||
3. 财务风险与稳健性（规避财务陷阱） |
||||
必需：总资产、总负债、股东权益 |
||||
强力推荐：资产负债率、流动比率、速动比率 |
||||
相关：利息保障倍数、Z-Score 财务困境指标 |
||||
4. 行业与板块分类（实现行业中性化或行业内选股） |
||||
必需：行业分类代码、行业名称（建议采用申万、中信等标准） |
||||
相关：板块分类（如主板、创业板、科创板） |
||||
5. 量价与市场数据（结合技术面确认趋势） |
||||
必需：收盘价、复权价格 |
||||
强力推荐：成交量、成交额 |
||||
相关：换手率、历史收益率 |
||||
6. 宏观经济与市场基准（控制宏观及市场风险暴露） |
||||
相关：无风险利率、市场收益率、行业指数收益率 |
||||
*=========================================================================================* |
||||
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。 |
||||
**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： |
||||
|
||||
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, |
||||
Description: 此字段后面的是操作符对应的描述或使用说明, 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), description_cn字段后面的内容是中文使用说明(不能使用) |
||||
|
||||
{'id': '81', 'data_set_name': 'cashflow', 'description': 'Cashflow (Annual)', 'description_cn': '现金流(年度)'} |
||||
{'id': '82', 'data_set_name': 'cashflow_dividends', 'description': 'Cash Dividends (Cash Flow)', 'description_cn': '现金股息（现金流）'} |
||||
{'id': '83', 'data_set_name': 'cashflow_fin', 'description': 'Financing Activities - Net Cash Flow', 'description_cn': '融资活动-净现金流量'} |
||||
{'id': '84', 'data_set_name': 'cashflow_invst', 'description': 'Investing Activities - Net Cash Flow', 'description_cn': '投资活动-净现金流量'} |
||||
{'id': '85', 'data_set_name': 'cashflow_op', 'description': 'Operating Activities - Net Cash Flow', 'description_cn': '经营活动-净现金流量'} |
||||
{'id': '118', 'data_set_name': 'fnd6_cibegni', 'description': 'Comp Inc - Beginning Net Income', 'description_cn': 'Comp Inc - 初始净收入'} |
||||
{'id': '139', 'data_set_name': 'fnd6_cptmfmq_oibdpq', 'description': 'Operating Income Before Depreciation - Quarterly', 'description_cn': '营业利润（扣除折旧）- 季度'} |
||||
{'id': '153', 'data_set_name': 'fnd6_cptnewqeventv110_nopiq', 'description': 'Non-Operating Income (Expense) - Total', 'description_cn': '非经营性收益(损失)-总计'} |
||||
{'id': '156', 'data_set_name': 'fnd6_cptnewqeventv110_oibdpq', 'description': 'Operating Income Before Depreciation - Quarterly', 'description_cn': '营业利润（不扣折旧）- 季度'} |
||||
{'id': '172', 'data_set_name': 'fnd6_cptnewqv1300_nopiq', 'description': 'Non-Operating Income (Expense) - Total', 'description_cn': '非经营性收入（支出）总额'} |
||||
{'id': '174', 'data_set_name': 'fnd6_cptnewqv1300_oiadpq', 'description': 'Operating Income After Depreciation - Quarterly', 'description_cn': '营业净利润-季度'} |
||||
{'id': '175', 'data_set_name': 'fnd6_cptnewqv1300_oibdpq', 'description': 'Operating Income Before Depreciation - Quarterly', 'description_cn': '运营收入（扣除折旧）- 季度'} |
||||
{'id': '215', 'data_set_name': 'fnd6_drc', 'description': 'Deferred Revenue - Current', 'description_cn': '未实现收入-当前'} |
||||
{'id': '216', 'data_set_name': 'fnd6_drlt', 'description': 'Deferred Revenue - Long-term', 'description_cn': '未实现收入_长期'} |
||||
{'id': '285', 'data_set_name': 'fnd6_idit', 'description': 'Interest and Related Income - Total', 'description_cn': '利息及关联收入总计'} |
||||
{'id': '286', 'data_set_name': 'fnd6_iints', 'description': 'Interest Income', 'description_cn': '利息收入'} |
||||
{'id': '297', 'data_set_name': 'fnd6_itci', 'description': 'Investment Tax Credit (Income Account)', 'description_cn': '投资税信贷（收入账户）'} |
||||
{'id': '306', 'data_set_name': 'fnd6_lcoxdr', 'description': 'Current Liabilities - Other - Excluding Deferred Revenue', 'description_cn': '当前负债-其他-不包括递延收入'} |
||||
{'id': '311', 'data_set_name': 'fnd6_loxdr', 'description': 'Liabilities - Other - Excluding Deferred Revenue', 'description_cn': '负债-其他-不包括递延收入'} |
||||
{'id': '320', 'data_set_name': 'fnd6_mfma1_dpc', 'description': 'Depreciation and Amortization (Cash Flow)', 'description_cn': '现金流折旧与摊销'} |
||||
{'id': '322', 'data_set_name': 'fnd6_mfma2_oancf', 'description': 'Operating Activities - Net Cash Flow', 'description_cn': '经营活动-净现金流量'} |
||||
{'id': '325', 'data_set_name': 'fnd6_mfma2_revt', 'description': 'Revenue - Total', 'description_cn': '总收入-总金额'} |
||||
{'id': '379', 'data_set_name': 'fnd6_newa1v1300_dpc', 'description': 'Depreciation and Amortization (Cash Flow)', 'description_cn': '折旧与摊销（现金流）'} |
||||
{'id': '380', 'data_set_name': 'fnd6_newa1v1300_dv', 'description': 'Cash Dividends (Cash Flow)', 'description_cn': '现金股息（现金流）'} |
||||
{'id': '391', 'data_set_name': 'fnd6_newa1v1300_fincf', 'description': 'Financing Activities - Net Cash Flow', 'description_cn': '融资活动-净现金流量'} |
||||
{'id': '396', 'data_set_name': 'fnd6_newa1v1300_ibc', 'description': 'Income Before Extraordinary Items (Cash Flow)', 'description_cn': '现金流量前利润'} |
||||
{'id': '402', 'data_set_name': 'fnd6_newa1v1300_ivncf', 'description': 'Investing Activities - Net Cash Flow', 'description_cn': '投资活动-净现金流量'} |
||||
{'id': '411', 'data_set_name': 'fnd6_newa2v1300_nopi', 'description': 'Nonoperating Income (Expense)', 'description_cn': '非经营性收益(支出)'} |
||||
{'id': '412', 'data_set_name': 'fnd6_newa2v1300_oancf', 'description': 'Operating Activities - Net Cash Flow', 'description_cn': '运营活动-净现金流'} |
||||
{'id': '413', 'data_set_name': 'fnd6_newa2v1300_oiadp', 'description': 'Operating Income After Depreciation', 'description_cn': '营业净利润 after depreciation 不变，无需翻译。请提供需要翻译的专业字段名。'} |
||||
{'id': '414', 'data_set_name': 'fnd6_newa2v1300_oibdp', 'description': 'Operating Income Before Depreciation', 'description_cn': '营业利润前折旧'} |
||||
{'id': '429', 'data_set_name': 'fnd6_newa2v1300_revt', 'description': 'Revenue - Total', 'description_cn': '总收入_-_总计'} |
||||
{'id': '445', 'data_set_name': 'fnd6_newa2v1300_xidoc', 'description': 'Extraordinary Items and Discontinued Operations (Cash Flow)', 'description_cn': '非常项目及终止经营（现金流量）'} |
||||
{'id': '498', 'data_set_name': 'fnd6_newqeventv110_drltq', 'description': 'Deferred Revenue - Long-term', 'description_cn': '未实现收入_长期'} |
||||
{'id': '545', 'data_set_name': 'fnd6_newqeventv110_loxdrq', 'description': 'Liabilities - Other - Excluding Deferred Revenue', 'description_cn': '负债-其他-不包括递延收入'} |
||||
{'id': '707', 'data_set_name': 'fnd6_newqv1300_drcq', 'description': 'Deferred Revenue - Current', 'description_cn': '未实现收入-当前'} |
||||
{'id': '708', 'data_set_name': 'fnd6_newqv1300_drltq', 'description': 'Deferred Revenue - Long-term', 'description_cn': '未实现收入_长期'} |
||||
{'id': '720', 'data_set_name': 'fnd6_newqv1300_ibadjq', 'description': 'Income Before Extraordinary Items - Adjusted for Common Stock Equivalents', 'description_cn': '收入剔除非经常性项目后调整普通股等值股前'} |
||||
{'id': '739', 'data_set_name': 'fnd6_newqv1300_loxdrq', 'description': 'Liabilities - Other - Excluding Deferred Revenue', 'description_cn': '负债_其他_不包括递延收入'} |
||||
{'id': '770', 'data_set_name': 'fnd6_newqv1300_revtq', 'description': 'Revenue - Total', 'description_cn': '总收入-总计'} |
||||
{'id': '808', 'data_set_name': 'fnd6_nopio', 'description': 'Nonoperating Income (Expense) - Other', 'description_cn': '非经营性收入（支出）- 其他'} |
||||
{'id': '809', 'data_set_name': 'fnd6_nopxs', 'description': 'Nonoperating Income (Expense) - excluding Interest', 'description_cn': '非经营性收益（损失）-除利息外'} |
||||
{'id': '815', 'data_set_name': 'fnd6_oelim', 'description': 'Other Eliminations (Income)', 'description_cn': '其他消除项（收入）'} |
||||
{'id': '817', 'data_set_name': 'fnd6_oibdps', 'description': 'Operating Income before Depreciation', 'description_cn': '营业利润前折旧'} |
||||
{'id': '866', 'data_set_name': 'fnd6_revts', 'description': 'Total Revenues', 'description_cn': '总收入'} |
||||
{'id': '886', 'data_set_name': 'fnd6_txbco', 'description': 'Excess Tax Benefit Stock Options - Cash Flow Operating', 'description_cn': '超额税盾股票期权-运营现金流'} |
||||
{'id': '887', 'data_set_name': 'fnd6_txbcof', 'description': 'Excess Tax Benefit of Stock Options - Cash Flow Financing', 'description_cn': '股票期权超额税收利益-现金流量融资'} |
||||
{'id': '893', 'data_set_name': 'fnd6_txdc', 'description': 'Deferred Taxes (Cash Flow)', 'description_cn': '延期税项（现金流）'} |
||||
{'id': '896', 'data_set_name': 'fnd6_txdi', 'description': 'Income Taxes - Deferred', 'description_cn': '递延所得税收入'} |
||||
{'id': '980', 'data_set_name': 'cashflow_efficiency_rank_derivative', 'description': 'Change in ranking for cash flow generation and profitability compared to previous period.', 'description_cn': '期权变动对现金流量生成及盈利能力较上一期的变化'} |
||||
{'id': '985', 'data_set_name': 'fscore_bfl_profitability', 'description': 'The purpose of this metric is to rank stock based on their ability to generate cash flows.', 'description_cn': '该指标的目的根据其产生现金流能力对股票进行排名。'} |
||||
{'id': '993', 'data_set_name': 'fscore_profitability', 'description': 'The purpose of this metric is to rank stock based on their ability to generate cash flows.', 'description_cn': '该指标的目的在于根据产生现金流的能力对股票进行排名。'} |
||||
{'id': '1021', 'data_set_name': 'actual_cashflow_per_share_value_quarterly', 'description': 'Cash Flow Per Share - actual value for the quarter', 'description_cn': '每股现金流量-本季度实际值'} |
||||
{'id': '1025', 'data_set_name': 'actual_sales_value_quarterly', 'description': 'Sales - Value in financial services income statement (in millions)', 'description_cn': '销售_金融服务收入表_价值（百万元）'} |
||||
{'id': '1051', 'data_set_name': 'anl4_af_cfps_value', 'description': 'Cash Flow Per Share - Actual Value', 'description_cn': '每股现金流实际值'} |
||||
{'id': '1055', 'data_set_name': 'anl4_afv4_cfps_high', 'description': 'Cash Flow Per Share - The highest estimation for the annual forecast', 'description_cn': '每股现金流-年度预测最高估计值'} |
||||
{'id': '1056', 'data_set_name': 'anl4_afv4_cfps_low', 'description': 'Cash Flow Per Share - The lowest estimation for the upcoming fiscal year', 'description_cn': '每股现金流量-即将到来财年的最低估计值'} |
||||
{'id': '1057', 'data_set_name': 'anl4_afv4_cfps_mean', 'description': 'Cash Flow Per Share - average of estimations for the annual frequency', 'description_cn': '每股现金流量-年度频率下估计值平均'} |
||||
{'id': '1058', 'data_set_name': 'anl4_afv4_cfps_median', 'description': 'Cash Flow Per Share - Median value among forecasts for the annual frequency', 'description_cn': '每股现金流量-年度频率预测中位值'} |
||||
{'id': '1059', 'data_set_name': 'anl4_afv4_cfps_number', 'description': 'Cash Flow Per Share - number of estimations for annual frequency', 'description_cn': '每股现金流量-年度频率估计数量'} |
||||
{'id': '1139', 'data_set_name': 'anl4_cff_flag', 'description': 'Cash Flow From Financing Activities - forecast type (revision/new/...)', 'description_cn': '融资活动现金流量-预测类型（修订版/新版本/...）'} |
||||
{'id': '1140', 'data_set_name': 'anl4_cff_high', 'description': 'Cash Flow From Financing - The highest of forecasted values', 'description_cn': '融资现金流量-最高预测值'} |
||||
{'id': '1141', 'data_set_name': 'anl4_cff_low', 'description': 'Cash Flow From Financing - The lowest estimation', 'description_cn': '融资现金流量-最低估计值'} |
||||
{'id': '1142', 'data_set_name': 'anl4_cff_mean', 'description': 'Cash Flow From Financing - mean of estimations', 'description_cn': '融资现金流-估算均值'} |
||||
{'id': '1143', 'data_set_name': 'anl4_cff_median', 'description': 'Cash Flow From Financing Activities - Median value among forecasts', 'description_cn': '现金流从融资活动-预测中值'} |
||||
{'id': '1144', 'data_set_name': 'anl4_cff_number', 'description': 'Cash Flow From Financing - number of estimations', 'description_cn': '融资现金流-估测次数'} |
||||
{'id': '1145', 'data_set_name': 'anl4_cff_value', 'description': 'Cash Flow From Financing - announced financial value', 'description_cn': '现金流从融资-宣布的财务价值'} |
||||
{'id': '1146', 'data_set_name': 'anl4_cfi_flag', 'description': 'Cash Flow From Investing - forecast type (revision/new/...)', 'description_cn': '现金流从投资-预测类型（修订/新...）'} |
||||
{'id': '1147', 'data_set_name': 'anl4_cfi_high', 'description': 'Cash Flow From Investing - The highest estimation', 'description_cn': '现金流入投资-最高估计值'} |
||||
{'id': '1148', 'data_set_name': 'anl4_cfi_low', 'description': 'Cash Flow From Investing - The lowest estimation', 'description_cn': '投资现金流量-最低估计值'} |
||||
{'id': '1149', 'data_set_name': 'anl4_cfi_mean', 'description': 'Cash Flow From Investing - mean of estimations', 'description_cn': '投资现金流量-估算均值'} |
||||
{'id': '1150', 'data_set_name': 'anl4_cfi_median', 'description': 'Cash Flow From Investing - median of estimations', 'description_cn': '投资现金流量-估测中位数'} |
||||
{'id': '1151', 'data_set_name': 'anl4_cfi_number', 'description': 'Cash Flow From Investing - number of estimations', 'description_cn': '投资现金流-估测数量'} |
||||
{'id': '1152', 'data_set_name': 'anl4_cfi_value', 'description': 'Cash Flow From Investing - announced financial value', 'description_cn': '投资现金流-宣布的财务价值'} |
||||
{'id': '1153', 'data_set_name': 'anl4_cfo_flag', 'description': 'Cash Flow From Operations - forecast type (revision/new/...)', 'description_cn': '现金流（运营）- 预测类型（修订/新...）'} |
||||
{'id': '1154', 'data_set_name': 'anl4_cfo_high', 'description': 'Cash Flow From Operations - The highest value among forecasts', 'description_cn': '现金流量从运营-预测中的最高值'} |
||||
{'id': '1155', 'data_set_name': 'anl4_cfo_low', 'description': 'Cash Flow From Operations - The lowest estimation', 'description_cn': '现金流从运营活动-最低估计值'} |
||||
{'id': '1156', 'data_set_name': 'anl4_cfo_mean', 'description': 'Cash Flow From Operations - mean of estimations', 'description_cn': '运营现金流-估测均值'} |
||||
{'id': '1157', 'data_set_name': 'anl4_cfo_median', 'description': 'Cash Flow From Operations - median of estimations', 'description_cn': '运营现金流-估计值中位数'} |
||||
{'id': '1158', 'data_set_name': 'anl4_cfo_number', 'description': 'Cash Flow From Operations - number of estimations', 'description_cn': '现金流-运营活动-估计次数'} |
||||
{'id': '1159', 'data_set_name': 'anl4_cfo_value', 'description': 'Cash Flow From Operations - announced financial value', 'description_cn': '现金流从运营-公告财务值'} |
||||
{'id': '1241', 'data_set_name': 'anl4_fcf_flag', 'description': 'Free cash flow - forecast type (revision/new/...)', 'description_cn': '自由现金流-预测类型（修订/新/...）'} |
||||
{'id': '1242', 'data_set_name': 'anl4_fcf_high', 'description': 'Free cash flow - aggregation on estimations, max', 'description_cn': '自由现金流_估测聚合_最大'} |
||||
{'id': '1243', 'data_set_name': 'anl4_fcf_low', 'description': 'Free Cash Flow - The lowest estimation', 'description_cn': '自由现金流 - 最低估计值'} |
||||
{'id': '1244', 'data_set_name': 'anl4_fcf_mean', 'description': 'Free Cash Flow - mean of estimations', 'description_cn': '自由现金流_估计值平均值'} |
||||
{'id': '1245', 'data_set_name': 'anl4_fcf_median', 'description': 'Free cash flow - aggregation on estimations, 50th percentile', 'description_cn': '自由现金流-估计值聚合_50百分位'} |
||||
{'id': '1246', 'data_set_name': 'anl4_fcf_number', 'description': 'Free Cash Flow - number of estimations', 'description_cn': '自由现金流-估算数量'} |
||||
{'id': '1247', 'data_set_name': 'anl4_fcf_value', 'description': 'Free cash flow- announced financial value', 'description_cn': '自由现金流-公告财务值'} |
||||
{'id': '1248', 'data_set_name': 'anl4_fcfps_flag', 'description': 'Free cash flow per share - forecast type (revision/new/...)', 'description_cn': '每股自由现金流-预测类型（修订/新...）'} |
||||
{'id': '1249', 'data_set_name': 'anl4_fcfps_high', 'description': 'Free Cash Flow Per Share - the highest estimation', 'description_cn': '每股自由现金流-最高估计值'} |
||||
{'id': '1250', 'data_set_name': 'anl4_fcfps_low', 'description': 'Free Cash Flow Per Share - the lowest estimation', 'description_cn': '每股自由现金流量-最低估计值'} |
||||
{'id': '1251', 'data_set_name': 'anl4_fcfps_mean', 'description': 'Free cash flow per share - mean of estimations', 'description_cn': '每股自由现金流-估计值平均数'} |
||||
{'id': '1252', 'data_set_name': 'anl4_fcfps_median', 'description': 'Free cash flow - summary on estimations, 50th-percentile, per share', 'description_cn': '自由现金流_估测摘要_第50百分位_每股'} |
||||
{'id': '1253', 'data_set_name': 'anl4_fcfps_number', 'description': 'Free Cash Flow per Share - number of estimations', 'description_cn': '每股自由现金流-估算次数'} |
||||
{'id': '1277', 'data_set_name': 'anl4_gric_high', 'description': 'Gross income - The highest estimation', 'description_cn': '预计总收入'} |
||||
{'id': '1283', 'data_set_name': 'anl4_gric_value', 'description': 'Gross income- announced financial value', 'description_cn': '总收入-公告财务价值'} |
||||
{'id': '1327', 'data_set_name': 'anl4_qf_az_cfps_mean', 'description': 'Cash Flow Per Share - average of estimations', 'description_cn': '每股现金流量-平均估计值'} |
||||
{'id': '1328', 'data_set_name': 'anl4_qf_az_cfps_median', 'description': 'Cash Flow Per Share - Median value among forecasts', 'description_cn': '每股现金流中位数-预测值'} |
||||
{'id': '1329', 'data_set_name': 'anl4_qf_az_cfps_number', 'description': 'Cash Flow Per Share - number of estimations', 'description_cn': '每股现金流-估算次数'} |
||||
{'id': '1341', 'data_set_name': 'anl4_qf_az_wol_spfc', 'description': 'Cash Flow Per Share - The lowest estimation', 'description_cn': '每股现金流-最低估计值'} |
||||
{'id': '1343', 'data_set_name': 'anl4_qfd1_az_cfps_median', 'description': 'Cash Flow Per Share - Median value among forecasts', 'description_cn': '每股现金流量-预测值中的中位数'} |
||||
{'id': '1344', 'data_set_name': 'anl4_qfd1_az_cfps_number', 'description': 'Cash Flow Per Share - number of estimations', 'description_cn': '每股现金流量-估算次数'} |
||||
{'id': '1353', 'data_set_name': 'anl4_qfd1_az_wol_spfc', 'description': 'Cash Flow Per Share - The lowest estimation', 'description_cn': '每股现金流-最低估计'} |
||||
{'id': '1357', 'data_set_name': 'anl4_qfv4_cfps_high', 'description': 'Cash Flow Per Share - The highest estimation for the quarter', 'description_cn': '每股现金流-该季度最高估计值'} |
||||
{'id': '1358', 'data_set_name': 'anl4_qfv4_cfps_low', 'description': 'Cash Flow Per Share - The lowest estimation', 'description_cn': '每股现金流-最低估计值'} |
||||
{'id': '1359', 'data_set_name': 'anl4_qfv4_cfps_mean', 'description': 'Cash Flow Per Share - average of estimations', 'description_cn': '每股现金流量-估计值平均'} |
||||
{'id': '1360', 'data_set_name': 'anl4_qfv4_cfps_median', 'description': 'Cash Flow Per Share - Median value among forecasts', 'description_cn': '每股现金流量-预测中的中位数值'} |
||||
{'id': '1361', 'data_set_name': 'anl4_qfv4_cfps_number', 'description': 'Cash Flow Per Share - number of estimations', 'description_cn': '每股现金流-估测次数'} |
||||
{'id': '1410', 'data_set_name': 'capital_expenditure_reported_value', 'description': 'Capital Expenditures - Total (Cash Flow/Investing) (Millions)', 'description_cn': '资本支出-总计(现金流/投资)(百万)'} |
||||
{'id': '1411', 'data_set_name': 'cash_flow_financing_max_guidance', 'description': 'Cash Flow From Financing - Maximum guidance value provided annually', 'description_cn': '融资现金流量-每年提供的最大指导值'} |
||||
{'id': '1412', 'data_set_name': 'cash_flow_from_financing', 'description': 'Cash Flow From Financing - Value', 'description_cn': '现金流从融资-价值'} |
||||
{'id': '1413', 'data_set_name': 'cash_flow_from_investing', 'description': 'Cash Flow from Investing - Value', 'description_cn': '投资现金流-价值'} |
||||
{'id': '1414', 'data_set_name': 'cash_flow_from_operations', 'description': 'Cash Flow from Operations - Value for the annual period', 'description_cn': '营业现金流量-年度期间价值'} |
||||
{'id': '1415', 'data_set_name': 'cash_flow_operations_min_guidance', 'description': 'Minimum guidance value for Cash Flow from Operations on an annual basis.', 'description_cn': '年度经营现金流量最低指导值'} |
||||
{'id': '1416', 'data_set_name': 'cashflow_per_share_average', 'description': 'Cash Flow Per Share - average of estimations with a delay of 1 quarter', 'description_cn': '每股现金流量-延迟一个季度的估计平均值'} |
||||
{'id': '1417', 'data_set_name': 'cashflow_per_share_estimate_count', 'description': 'Cash Flow Per Share - number of estimations - delay1', 'description_cn': '每股现金流-估计次数-延迟1'} |
||||
{'id': '1418', 'data_set_name': 'cashflow_per_share_max_guidance', 'description': 'The maximum guidance value for Cash Flow Per Share on an annual basis.', 'description_cn': '每股现金流量年度上限值'} |
||||
{'id': '1419', 'data_set_name': 'cashflow_per_share_max_guidance_quarterly', 'description': 'The maximum guidance value for Cash Flow Per Share.', 'description_cn': '每股现金流量上限值'} |
||||
{'id': '1420', 'data_set_name': 'cashflow_per_share_maximum', 'description': 'Cash Flow - The highest estimation, per share, with a delay of 1 quarter', 'description_cn': '现金流量_每股最高估计_延迟一个季度'} |
||||
{'id': '1421', 'data_set_name': 'cashflow_per_share_median_value', 'description': 'Cash Flow Per Share - Median value among forecasts', 'description_cn': '每股现金流中位值-预测值'} |
||||
{'id': '1422', 'data_set_name': 'cashflow_per_share_min_guidance', 'description': 'Cash Flow Per Share - Minimum guidance value for the annual period', 'description_cn': '每股现金流-年度期间最小指导值'} |
||||
{'id': '1423', 'data_set_name': 'cashflow_per_share_min_guidance_quarterly', 'description': 'Minimum guidance value for Cash Flow Per Share', 'description_cn': '每股现金流最低指导值'} |
||||
{'id': '1424', 'data_set_name': 'cashflow_per_share_minimum', 'description': 'Cash Flow Per Share - The lowest estimation, delay 1 quarter', 'description_cn': '每股现金流量-延迟一个季度的最低估计值'} |
||||
{'id': '1462', 'data_set_name': 'est_cashflow_fin', 'description': 'Cash Flow From Financing - mean of estimations', 'description_cn': '融资现金流-估计值均值'} |
||||
{'id': '1463', 'data_set_name': 'est_cashflow_invst', 'description': 'Cash Flow From Investing - mean of estimations', 'description_cn': '投资现金流-估算值均值'} |
||||
{'id': '1464', 'data_set_name': 'est_cashflow_op', 'description': 'Cash Flow From Operations - mean of estimations', 'description_cn': '运营现金流-估计值均值'} |
||||
{'id': '1465', 'data_set_name': 'est_cashflow_ps', 'description': 'Cash Flow Per Share - average of estimations', 'description_cn': '每股现金流量-估计值平均值'} |
||||
{'id': '1472', 'data_set_name': 'est_fcf', 'description': 'Free Cash Flow - Mean of Estimations', 'description_cn': '自由现金流-估算值平均值'} |
||||
{'id': '1473', 'data_set_name': 'est_fcf_ps', 'description': 'Free Cash Flow Per Share - Mean of Estimations', 'description_cn': '每股自由现金流-估计值平均值'} |
||||
{'id': '1475', 'data_set_name': 'est_grossincome', 'description': 'Gross income - Mean of estimations', 'description_cn': '总收入_估测均值'} |
||||
{'id': '1491', 'data_set_name': 'financing_cashflow_reported_value', 'description': 'Cash Flow From Financing - Value', 'description_cn': '融资现金流量-价值'} |
||||
{'id': '1492', 'data_set_name': 'free_cash_flow_per_share', 'description': 'Free cash flow per share - actual financial value for the annual period', 'description_cn': '每股自由现金流量-年度实际财务值'} |
||||
{'id': '1493', 'data_set_name': 'free_cash_flow_per_share_actual_value', 'description': 'Free cash flow per share- announced financial value', 'description_cn': '每股自由现金流量-宣布财务值'} |
||||
{'id': '1494', 'data_set_name': 'free_cash_flow_per_share_max_guidance', 'description': 'The maximum guidance value for Free Cash Flow Per Share on an annual basis.', 'description_cn': '年度每股自由现金流指导上限'} |
||||
{'id': '1495', 'data_set_name': 'free_cash_flow_per_share_reported_value', 'description': 'Free cash flow per share- announced financial value', 'description_cn': '每股自由现金流-公告财务值'} |
||||
{'id': '1496', 'data_set_name': 'free_cash_flow_reported_value', 'description': 'Free cash flow value for the quarter.', 'description_cn': '季度自由现金流值'} |
||||
{'id': '1497', 'data_set_name': 'free_cash_flow_total', 'description': 'Free Cash Flow value - Annual', 'description_cn': '自由现金流值-年度'} |
||||
{'id': '1500', 'data_set_name': 'gross_income_reported_value', 'description': 'Gross Income value for the quarter', 'description_cn': '季度总收入值'} |
||||
{'id': '1501', 'data_set_name': 'gross_income_total', 'description': 'Gross Income value on an annual basis', 'description_cn': '年度毛收入值'} |
||||
{'id': '1507', 'data_set_name': 'investing_cashflow_reported_value', 'description': 'Cash Flow from Investing - Value', 'description_cn': '投资现金流-价值'} |
||||
{'id': '1511', 'data_set_name': 'max_adjusted_funds_from_operations_adj_guidance', 'description': 'Adjusted funds from operation - Maximum guidance value', 'description_cn': '调整后经营活动净现金流-最大指导值'} |
||||
{'id': '1513', 'data_set_name': 'max_adjusted_funds_from_operations_guidance_2', 'description': 'Adjusted funds from operation - maximum guidance value for the annual period', 'description_cn': '调整后经营现金流-年度期间最大指导值'} |
||||
{'id': '1523', 'data_set_name': 'max_financing_cashflow_guidance', 'description': 'Cash Flow From Financing - Maximum guidance value', 'description_cn': '融资现金流-最大指导值'} |
||||
{'id': '1524', 'data_set_name': 'max_free_cash_flow_guidance', 'description': 'The maximum guidance value for Free Cash Flow on an annual basis.', 'description_cn': '年度自由现金流指导上限'} |
||||
{'id': '1525', 'data_set_name': 'max_free_cashflow_guidance', 'description': 'The maximum guidance value for Free Cash Flow.', 'description_cn': '自由现金流最大指导值'} |
||||
{'id': '1526', 'data_set_name': 'max_free_cashflow_per_share_guidance', 'description': 'The maximum guidance value for free cash flow per share.', 'description_cn': '每股自由现金流指导的最大值'} |
||||
{'id': '1527', 'data_set_name': 'max_gross_income_guidance', 'description': 'The maximum guidance value for Gross Income.', 'description_cn': '最大毛收入指导值'} |
||||
{'id': '1528', 'data_set_name': 'max_gross_income_guidance_2', 'description': 'The maximum guidance for Gross Income on an annual basis.', 'description_cn': '年度毛收入最大指导金额'} |
||||
{'id': '1529', 'data_set_name': 'max_investing_cashflow_guidance', 'description': 'The maximum guidance value for Cash Flow from Investing.', 'description_cn': '现金流从投资的最大指导值'} |
||||
{'id': '1530', 'data_set_name': 'max_investing_cashflow_guidance_2', 'description': 'The maximum guidance value for Cash Flow from Investing activities on an annual basis.', 'description_cn': '年度投资活动现金流量上限指导值'} |
||||
{'id': '1534', 'data_set_name': 'max_operating_cashflow_guidance', 'description': 'The maximum guidance value for Cash Flow from Operations.', 'description_cn': '运营现金流指导值上限'} |
||||
{'id': '1535', 'data_set_name': 'max_operating_cashflow_guidance_2', 'description': 'The maximum guidance value for Cash Flow from Operations on an annual basis.', 'description_cn': '年度运营现金流指导最大值'} |
||||
{'id': '1556', 'data_set_name': 'min_adjusted_funds_from_operations_guidance_2', 'description': 'Adjusted funds from operation - minimum guidance for the annual period', 'description_cn': '调整后经营活动产生的现金流量-年度期最低指导值'} |
||||
{'id': '1567', 'data_set_name': 'min_financing_cashflow_guidance', 'description': 'Minimum guidance value for Cash Flow From Financing', 'description_cn': '现金流从融资的最小指导值'} |
||||
{'id': '1568', 'data_set_name': 'min_financing_cashflow_guidance_2', 'description': 'Minimum guidance value for Cash Flow From Financing on an annual basis', 'description_cn': '年度融资现金流最小指导值'} |
||||
{'id': '1569', 'data_set_name': 'min_free_cash_flow_guidance', 'description': 'The minimum guidance value for Free Cash Flow on an annual basis.', 'description_cn': '年度自由现金流参考值(盈亏平衡点)'} |
||||
{'id': '1570', 'data_set_name': 'min_free_cash_flow_per_share_guidance', 'description': 'Free cash flow per share - minimum guidance value for the annual period', 'description_cn': '每股自由现金流-年度期间最低指导值'} |
||||
{'id': '1571', 'data_set_name': 'min_free_cashflow_guidance', 'description': 'Minimum guidance value for Free Cash Flow', 'description_cn': '自由现金流最低指导值'} |
||||
{'id': '1572', 'data_set_name': 'min_free_cashflow_per_share_guidance', 'description': 'Free cash flow per share - minimum guidance value', 'description_cn': '每股自由现金流-最低指导值'} |
||||
{'id': '1575', 'data_set_name': 'min_gross_income_guidance_2', 'description': 'The minimum guidance for Gross Income on an annual basis.', 'description_cn': '年度毛收入最低指导金额'} |
||||
{'id': '1576', 'data_set_name': 'min_investing_cashflow_guidance', 'description': 'Cash Flow From Investing - Minimum guidance value', 'description_cn': '投资现金流-最小指导值'} |
||||
{'id': '1577', 'data_set_name': 'min_investing_cashflow_guidance_2', 'description': 'Cash Flow From Investing - Minimum guidance value for the annual period', 'description_cn': '投资现金流-当年最低指导值'} |
||||
{'id': '1581', 'data_set_name': 'min_operating_cashflow_guidance', 'description': 'Minimum guidance value for Cash Flow from Operations', 'description_cn': '运营现金流最低指导值'} |
||||
{'id': '1599', 'data_set_name': 'minimum_guidance_value', 'description': 'Minimum guidance value for basic annual financials', 'description_cn': '基本年度财务报表最低指导值'} |
||||
{'id': '1610', 'data_set_name': 'operating_cashflow_reported_value', 'description': 'Cash Flow from Operations - Value', 'description_cn': '运营现金流量-价值'} |
||||
{'id': '2316', 'data_set_name': 'fn_accum_oth_income_loss_fx_adj_net_of_tax_a', 'description': 'Accumulated adjustment, net of tax, that results from the process of translating subsidiary financial statements and foreign equity investments into the reporting currency from the functional currency of the reporting entity, net of reclassification of realized foreign currency translation gains or losses.', 'description_cn': '累计折算净损益，减去税收影响，源自将附属财务报表及外币股权投资自报告实体的功能货币翻译为报导货币的过程，并减去重分类实现的外币折算收益或损失。'} |
||||
{'id': '2317', 'data_set_name': 'fn_accum_oth_income_loss_fx_adj_net_of_tax_q', 'description': 'Accumulated adjustment, net of tax, that results from the process of translating subsidiary financial statements and foreign equity investments into the reporting currency from the functional currency of the reporting entity, net of reclassification of realized foreign currency translation gains or losses.', 'description_cn': '累积折算调整，扣税后净额，源自将附属公司财务报表及外币投资从报告实体的功能货币转换为报告货币的过程，扣除重分类实现的外币折算损益净额。'} |
||||
{'id': '2318', 'data_set_name': 'fn_accum_oth_income_loss_net_of_tax_a', 'description': '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.', 'description_cn': '期末非业主来源交易及其他事件和情况引起的所有者权益累计变动，扣除税影响。不包括净利润（亏损），以及因所有者投资和向所有者分配引起的权益累计变动。包括外币折算项目、某些养老金调整、特定债务和股权证券未实现损益、除信贷损失外其他因素导致的持有至到期日和可供出售债务证券暂时性减值损失，以及与有效部分指定现金流量对冲相关的衍生工具公允价值变动。'} |
||||
{'id': '2319', 'data_set_name': 'fn_accum_oth_income_loss_net_of_tax_q', 'description': '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.', 'description_cn': '期末非股东来源交易及其他事件和情况引起的权益累计变动净额，扣税后，不包括净利润（亏损）、股东投资交易导致的权益累计变动及分配。包含外币折算项目、特定养老金调整、特定债权和股权证券未实现盈亏、除信用损失外其他暂时性减值（OTTI）亏损，以及指定现金流量对冲有效部分相关衍生工具公允价值变动。'} |
||||
{'id': '2412', 'data_set_name': 'fn_excess_tax_benefit_from_share_based_comp_fin_activities_a', 'description': "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.", 'description_cn': '现金流入实现税项利益金额（权益工具可扣除薪酬成本超出财务报告确认成本的税务回报）'} |
||||
{'id': '2413', 'data_set_name': 'fn_excess_tax_benefit_from_share_based_comp_fin_activities_q', 'description': "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.", 'description_cn': '实现的与权益工具可抵扣薪酬费用相关的税收利益现金流入超出财务报告目的确认薪酬费用的差额金额'} |
||||
{'id': '2427', 'data_set_name': 'fn_income_taxes_paid_q', 'description': 'The amount of cash paid during the current period to foreign, federal, state, and local authorities as taxes on income.', 'description_cn': '当前期间支付给外国、联邦、州和地方政府的应税收入现金金额'} |
||||
{'id': '2458', 'data_set_name': 'fn_op_lease_rent_exp_a', 'description': 'Rental expense for the reporting period incurred under operating leases, including minimum and any contingent rent expense, net of related sublease income.', 'description_cn': '报告期内按经营租赁计入的租金支出，包括最低及任何或有租金支出，并扣除相关次级租赁收入后的净额'} |
||||
{'id': '2465', 'data_set_name': 'fn_oth_income_loss_derivatives_qualifying_as_hedges_of_tax_a', 'description': "Amount after tax and reclassification adjustments, of increase (decrease) in accumulated gain (loss) from derivative instruments designated and qualifying as the effective portion of cash flow hedges and an entity's share of an equity investee's increase (decrease) in deferred hedging gain (loss).", 'description_cn': '税后调整后的累计衍生工具公允价值变动净额，及权益法核算下被投资单位累积盈亏变动调整后的现金流量套期有效部分及企业享有份额'} |
||||
{'id': '2466', 'data_set_name': 'fn_oth_income_loss_derivatives_qualifying_as_hedges_of_tax_q', 'description': "Amount after tax and reclassification adjustments, of increase (decrease) in accumulated gain (loss) from derivative instruments designated and qualifying as the effective portion of cash flow hedges and an entity's share of an equity investee's increase (decrease) in deferred hedging gain (loss).", 'description_cn': '税后调整后的衍生工具指定并符合条件的现金流量套期有效部分累计收益（损失）变动及实体对权益法投资企业累积未实现套期收益（损失）变动额'} |
||||
{'id': '2471', 'data_set_name': 'fn_payments_for_repurchase_of_common_stock_a', 'description': 'Value reported on Cash Flow Statement. May include shares repurchased as part of a buyback plan, as well as shares purchased for employee compensation, etc.', 'description_cn': '现金流量表报告的价值。可能包括作为回购计划一部分回购的股票，以及用于员工补偿等购买的股票等。- 盈亏平衡点'} |
||||
{'id': '2472', 'data_set_name': 'fn_payments_for_repurchase_of_common_stock_q', 'description': 'Value reported on Cash Flow Statement. May include shares repurchased as part of a buyback plan, as well as shares purchased for employee compensation, etc.', 'description_cn': '现金流量表中报告的价值。可能包括作为回购计划一部分回购的股票，以及用于员工补偿等购买的股票等。- 盈亏平衡点'} |
||||
{'id': '2473', 'data_set_name': 'fn_payments_to_acquire_businesses_net_of_cash_acquired_a', 'description': 'The cash outflow associated with the acquisition of a business, net of the cash acquired from the purchase.', 'description_cn': '并购现金流出净额'} |
||||
{'id': '2474', 'data_set_name': 'fn_payments_to_acquire_businesses_net_of_cash_acquired_q', 'description': 'The cash outflow associated with the acquisition of a business, net of the cash acquired from the purchase.', 'description_cn': '并购现金流出净额'} |
||||
{'id': '2479', 'data_set_name': 'fn_proceeds_from_issuance_of_common_stock_a', 'description': 'The cash inflow from the additional capital contribution to the entity.', 'description_cn': '额外资本贡献带来的现金流入'} |
||||
{'id': '2480', 'data_set_name': 'fn_proceeds_from_issuance_of_common_stock_q', 'description': 'The cash inflow from the additional capital contribution to the entity.', 'description_cn': '额外资本贡献现金流入'} |
||||
{'id': '2481', 'data_set_name': 'fn_proceeds_from_issuance_of_debt_a', 'description': 'The cash inflow during the period from additional borrowings in aggregate debt. Includes proceeds from short-term and long-term debt.', 'description_cn': '期间额外借款在内的现金流入总额。包括短期和长期债务的筹集资金。'} |
||||
{'id': '2482', 'data_set_name': 'fn_proceeds_from_issuance_of_debt_q', 'description': 'The cash inflow during the period from additional borrowings in aggregate debt. Includes proceeds from short-term and long-term debt.', 'description_cn': '额外债务合计借款期间的现金流入，包括短期和长期债务的收益。'} |
||||
{'id': '2485', 'data_set_name': 'fn_proceeds_from_stock_options_exercised_a', 'description': 'The cash inflow associated with the amount received from holders exercising their stock options. This item inherently excludes any excess tax benefit, which the entity may have realized and reported separately.', 'description_cn': '与持有人行权收到的股票期权金额相关的现金流入。此项目本质上不包括任何单独列报和报告的超额税收利益。'} |
||||
{'id': '2486', 'data_set_name': 'fn_proceeds_from_stock_options_exercised_q', 'description': 'The cash inflow associated with the amount received from holders exercising their stock options. This item inherently excludes any excess tax benefit, which the entity may have realized and reported separately.', 'description_cn': '与持有人行权收到的股票期权金额相关的现金流入。此项目本质上不包括任何单独列报和报告的超额税务收益。'} |
||||
{'id': '2489', 'data_set_name': 'fn_repayments_of_debt_a', 'description': 'The cash outflow during the period from the repayment of aggregate short-term and long-term debt. Excludes payment of capital lease obligations.', 'description_cn': '偿还短期及长期债务期间的现金流出（不包括资本租赁付款）'} |
||||
{'id': '2490', 'data_set_name': 'fn_repayments_of_debt_q', 'description': 'The cash outflow during the period from the repayment of aggregate short-term and long-term debt. Excludes payment of capital lease obligations.', 'description_cn': '短期及长期债务偿还期间的现金流出（不包括资本租赁付款）'} |
||||
{'id': '2491', 'data_set_name': 'fn_repayments_of_lines_of_credit_a', 'description': 'Amount of cash outflow for payment of an obligation from a lender, including but not limited to, letter of credit, standby letter of credit and revolving credit arrangements.', 'description_cn': '贷款义务支付的现金流出金额，包括但不限于信用证、备用信用证和循环信贷安排。- 贷款义务支付现金流出金额'} |
||||
{'id': '2492', 'data_set_name': 'fn_repayments_of_lines_of_credit_q', 'description': 'Amount of cash outflow for payment of an obligation from a lender, including but not limited to, letter of credit, standby letter of credit and revolving credit arrangements.', 'description_cn': '贷款义务支付的现金流出金额，包括但不限于信用证、备用信用证和循环信贷安排。- 贷款义务现金流出金额'} |
||||
{'id': '2493', 'data_set_name': 'fn_repayments_of_lt_debt_a', 'description': 'The cash outflow for debt initially having maturity due after 1 year or beyond the normal operating cycle, if longer.', 'description_cn': '债务初始到期日超过1年或正常经营周期（取较长者）的现金流出量'} |
||||
{'id': '2494', 'data_set_name': 'fn_repayments_of_lt_debt_q', 'description': 'The cash outflow for debt initially having maturity due after 1 year or beyond the normal operating cycle, if longer.', 'description_cn': '债务初始到期日在一年或正常经营周期以上现金流出'} |
||||
{'id': '2499', 'data_set_name': 'fn_taxes_payable_a', 'description': 'Carrying value as of the balance sheet date of obligations incurred and payable for statutory income, sales, use, payroll, excise, real, property, and other taxes. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).', 'description_cn': '履约价值_报表日_应付税费_法定利润_销售收入_销售税_使用税_工资税_特定消费税_房地产税及其他税费_盈亏平衡点_分类资产负债表_流动负债_未分类资产负债表_总负债_无到期日限制'} |
||||
{'id': '2504', 'data_set_name': 'fnd2_a_acmopclcchngcfectnt', 'description': "Accumulated change, net of tax, in accumulated gains and losses from derivative instruments designated and qualifying as the effective portion of cash flow hedges. Includes an entity's share of an equity investee's Increase or Decrease in deferred hedging gains or losses.", 'description_cn': '期权衍生工具指定并符合现金流量套期有效部分的累计净损益变动，包括实体对权益法核算长期股权投资的累积未实现套期收益或损失的变化。'} |
||||
{'id': '2510', 'data_set_name': 'fnd2_a_bnsacqproformarvn', 'description': 'The pro forma revenue for a period as if the business combination or combinations had been completed at the beginning of the period.', 'description_cn': '会计期初完成企业合并时的预期收入'} |
||||
{'id': '2523', 'data_set_name': 'fnd2_a_excesstxbnffsbcpnoprat', 'description': "Amount of cash outflow for 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.", 'description_cn': '税前补偿成本可抵扣金额超出财务报告中认可金额并在实体税务申报表中实现的税收利益现金流出量'} |
||||
{'id': '2549', 'data_set_name': 'fnd2_a_ptoacqbnsesg', 'description': 'The cash outflow associated with the acquisition of business during the period. The cash portion only of the acquisition price.', 'description_cn': '期权行权期间企业收购相关的现金流出（仅现金部分）收购价格'} |
||||
{'id': '2551', 'data_set_name': 'fnd2_a_rvndm', 'description': 'Revenue, Domestic', 'description_cn': '国内收入'} |
||||
{'id': '2600', 'data_set_name': 'fnd2_itxreclnondeductibleexp', 'description': '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.', 'description_cn': '报告的所得税费用（收益）与预期所得税费用（收益）之间的差额计算方法：将继续经营业务产生的应税收入（亏损）中不可抵扣费用部分应用国内联邦法定所得税率计算得出的预期所得税费用（收益）。'} |
||||
{'id': '2601', 'data_set_name': 'fnd2_itxreclstatelocalitxes', 'description': '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 state and local income tax expense (benefit).', 'description_cn': '差额所得税费用（ benefit ）与按国内联邦法定所得税率计算的预计所得税费用（ benefit ）金额（从持续经营业务税前利润中归属于州及地方政府所得税费用（ benefit ）部分）'} |
||||
{'id': '2602', 'data_set_name': 'fnd2_itxreexftfedstyitxrt', 'description': 'Income tax amount computed at the federal tax rate, before any adjustments', 'description_cn': '联邦税率计算的收入税金额（未调整前）'} |
||||
{'id': '2611', 'data_set_name': 'fnd2_q_bnsacqproformarvn', 'description': 'The pro forma revenue for a period as if the business combination or combinations had been completed at the beginning of the period.', 'description_cn': '预计合并期间的收入'} |
||||
========================= 数据字段结束 ======================================= |
||||
|
||||
@ -0,0 +1,206 @@ |
||||
任务指令 |
||||
1. 损益表与现金流（确认增长质量和动力） |
||||
必需：营业收入、销售额、营收 |
||||
强力推荐：经营性现金流、营业利润、扣非净利润 |
||||
相关：毛利率、销售费用、管理费用、财务费用 |
||||
2. 市场估值与预期（捕捉预期差与市场情绪） |
||||
必需：总市值、流通市值 |
||||
强力推荐：市盈率、市净率、市销率 |
||||
高级推荐：分析师一致预期净利润、盈利预测上调下调次数、目标价 |
||||
3. 财务风险与稳健性（规避财务陷阱） |
||||
必需：总资产、总负债、股东权益 |
||||
强力推荐：资产负债率、流动比率、速动比率 |
||||
相关：利息保障倍数、Z-Score 财务困境指标 |
||||
4. 行业与板块分类（实现行业中性化或行业内选股） |
||||
必需：行业分类代码、行业名称（建议采用申万、中信等标准） |
||||
相关：板块分类（如主板、创业板、科创板） |
||||
5. 量价与市场数据（结合技术面确认趋势） |
||||
必需：收盘价、复权价格 |
||||
强力推荐：成交量、成交额 |
||||
相关：换手率、历史收益率 |
||||
6. 宏观经济与市场基准（控制宏观及市场风险暴露） |
||||
相关：无风险利率、市场收益率、行业指数收益率 |
||||
*=========================================================================================* |
||||
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。 |
||||
**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： |
||||
|
||||
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, |
||||
Description: 此字段后面的是操作符对应的描述或使用说明, 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), description_cn字段后面的内容是中文使用说明(不能使用) |
||||
|
||||
{'id': '240', 'data_set_name': 'fnd6_eventv110_gdwlieps12', 'description': 'Impairment of Goodwill Basic EPS Effect 12MM', 'description_cn': 'goodwill_impairment_basic_eps_effect_12m'} |
||||
{'id': '241', 'data_set_name': 'fnd6_eventv110_gdwliepsq', 'description': 'Impairment of Goodwill Basic EPS Effect', 'description_cn': 'goodwill impairment basic_eps_effect'} |
||||
{'id': '473', 'data_set_name': 'fnd6_newqeventv110_cibegniq', 'description': 'Comp Inc - Beginning Net Income', 'description_cn': 'comp_inc_beginning_net_income'} |
||||
{'id': '624', 'data_set_name': 'fnd6_newqeventv110_spcedq', 'description': 'S&P Core Earnings EPS Diluted', 'description_cn': 'SPCE earnings per share diluted'} |
||||
{'id': '691', 'data_set_name': 'fnd6_newqv1300_cipenq', 'description': 'Comp Inc - Minimum Pension Adj', 'description_cn': '-comp_inc_min_pension_adj'} |
||||
{'id': '997', 'data_set_name': 'fscore_total', 'description': 'The final score M-Score is a weighted average of both the Pentagon surface score and the Pentagon acceleration score.', 'description_cn': '最终得分M-Score是pentagon表面分数和pentagon加速度分数的加权平均值。'} |
||||
{'id': '1000', 'data_set_name': 'multi_factor_acceleration_score_derivative', 'description': 'Change in the acceleration of multi-factor score compared to previous period.', 'description_cn': '多因子评分加速度变化 Compared_to_Previous_Period_Multi_Factor_Score_Acceleration_Change'} |
||||
{'id': '1931', 'data_set_name': 'news_mins_10_pct_up', 'description': 'Number of minutes that elapsed before price went up 10 percentage points', 'description_cn': '价格上升10个百分点前elapsed分钟数'} |
||||
{'id': '1933', 'data_set_name': 'news_mins_1_pct_dn', 'description': 'Number of minutes that elapsed before price went down 1 percentage point', 'description_cn': '价格下跌1个百分点前elapsed分钟数'} |
||||
{'id': '1934', 'data_set_name': 'news_mins_1_pct_up', 'description': 'Number of minutes that elapsed before price went up 1 percentage point', 'description_cn': '价格上升1个百分点前elapsed的分钟数'} |
||||
{'id': '1942', 'data_set_name': 'news_mins_3_pct_dn', 'description': 'Number of minutes that elapsed before price went down 3 percentage points', 'description_cn': '价格下跌3个百分点前 elapsed_分钟数'} |
||||
{'id': '1945', 'data_set_name': 'news_mins_4_pct_dn', 'description': 'Number of minutes that elapsed before price went down 4 percentage points', 'description_cn': '价格下跌4个百分点前elapsed分钟数'} |
||||
{'id': '1946', 'data_set_name': 'news_mins_4_pct_up', 'description': 'Number of minutes that elapsed before price went up 4 percentage points', 'description_cn': '价格上漲4個百分點前 elapsed 分钟数'} |
||||
{'id': '1985', 'data_set_name': 'nws12_afterhsz_01s', 'description': 'Number of minutes that elapsed before price went down 10 percentage points', 'description_cn': '价格下跌至低于初始水平10个百分点前elapsed分钟数'} |
||||
{'id': '1992', 'data_set_name': 'nws12_afterhsz_1l', 'description': 'Number of minutes that elapsed before price went up 1 percentage points', 'description_cn': '涨价至1个百分点前elapsed分钟数'} |
||||
{'id': '1999', 'data_set_name': 'nws12_afterhsz_3l', 'description': 'Number of minutes that elapsed before price went up 3 percentage points', 'description_cn': '价格上涨3个百分点前elapsed的分钟数'} |
||||
{'id': '2001', 'data_set_name': 'nws12_afterhsz_3s', 'description': 'Number of minutes that elapsed before price went down 3 percentage points', 'description_cn': '价格下跌3个百分点前elapsed分钟数'} |
||||
{'id': '2003', 'data_set_name': 'nws12_afterhsz_4l', 'description': 'Number of minutes that elapsed before price went up 4 percentage points', 'description_cn': '价格上升4个百分点前elapsed分钟数'} |
||||
{'id': '2089', 'data_set_name': 'nws12_mainz_4l', 'description': 'Number of minutes that elapsed before price went up 4 percentage points', 'description_cn': '价格上涨4个百分点前elapsed分钟数'} |
||||
{'id': '2154', 'data_set_name': 'nws12_prez_02s', 'description': 'Number of minutes that elapsed before price went down 20 percentage points', 'description_cn': '价格下跌20个百分点前elapsed分钟数'} |
||||
{'id': '2168', 'data_set_name': 'nws12_prez_3s', 'description': 'Number of minutes that elapsed before price went down 3 percentage points', 'description_cn': '价格下跌3个百分点前elapsed分钟数'} |
||||
{'id': '2172', 'data_set_name': 'nws12_prez_4s', 'description': 'Number of minutes that elapsed before price went down 4 percentage points', 'description_cn': '价格下跌4个百分点前elapsed分钟数'} |
||||
{'id': '2173', 'data_set_name': 'nws12_prez_57l', 'description': 'Number of minutes that elapsed before price went up 7.5 percentage points', 'description_cn': '价格上升7.5个百分点前elapsed分钟数'} |
||||
{'id': '2179', 'data_set_name': 'nws12_prez_5s', 'description': 'Number of minutes that elapsed before price went down 5 percentage points', 'description_cn': '价格下跌5个百分点前elapsed分钟数'} |
||||
{'id': '2436', 'data_set_name': 'fn_liab_fair_val_a', 'description': 'Liabilities Fair Value, Recurring, Total', 'description_cn': '看涨期权负债公允价值_ recurring_total'} |
||||
========================= 数据字段结束 ======================================= |
||||
|
||||
@ -0,0 +1,133 @@ |
||||
# -*- coding: utf-8 -*- |
||||
''' |
||||
使用ollama翻译 data-sets description |
||||
''' |
||||
|
||||
import psycopg2 |
||||
import httpx |
||||
import time |
||||
import sys |
||||
|
||||
def translate_with_ollama(text, model="qwen2.5:7b"): |
||||
if not text or not text.strip(): |
||||
return None |
||||
|
||||
url = "http://localhost:11434/api/generate" |
||||
prompt = f"""你是一个金融数据专家，负责翻译期权交易领域的专业字段名。 |
||||
规则： |
||||
1. 在此上下文中，“call” 指“看涨期权”，切勿翻译为“呼叫”。 |
||||
2. "put" 指"看跌期权"。 |
||||
3. “breakeven” 统一翻译为“盈亏平衡点”。 |
||||
4. 整体翻译需简洁，符合数据库字段名的命名习惯。 |
||||
5. 输出仅返回翻译后的中文，不要任何解释。 |
||||
|
||||
请翻译：{text}""" |
||||
|
||||
payload = {"model": model, "prompt": prompt, "stream": False} |
||||
|
||||
try: |
||||
response = httpx.post(url, json=payload, timeout=180.0) |
||||
response.raise_for_status() |
||||
result = response.json() |
||||
return result['response'].strip() |
||||
except httpx.TimeoutException: |
||||
print(f"\n[超时] {text[:60]}...") |
||||
return None |
||||
except Exception as e: |
||||
print(f"\n[请求失败] {text[:30]}... - {e}") |
||||
return None |
||||
|
||||
db_config = { |
||||
'host': '192.168.31.201', |
||||
'port': 5432, |
||||
'database': 'alpha', |
||||
'user': 'jack', |
||||
'password': 'aaaAAA111' |
||||
} |
||||
|
||||
start_from_id = 0 |
||||
|
||||
try: |
||||
conn = psycopg2.connect(**db_config) |
||||
cur = conn.cursor() |
||||
|
||||
cur.execute(""" |
||||
SELECT id, description |
||||
FROM operator |
||||
WHERE description IS NOT NULL |
||||
AND description_cn IS NULL |
||||
AND id >= %s |
||||
ORDER BY id ASC |
||||
""", (start_from_id,)) |
||||
|
||||
rows = cur.fetchall() |
||||
total = len(rows) |
||||
|
||||
if total == 0: |
||||
print("没有需要翻译的记录！") |
||||
sys.exit(0) |
||||
|
||||
print(f"找到 {total} 条待翻译记录 (从ID {start_from_id} 开始)") |
||||
print("=" * 60) |
||||
|
||||
success_count = 0 |
||||
fail_count = 0 |
||||
last_success_id = start_from_id |
||||
|
||||
for idx, (row_id, description) in enumerate(rows, 1): |
||||
percent = (idx / total) * 100 |
||||
sys.stdout.write(f"\r处理进度: {idx}/{total} ({percent:.1f}%) | 成功: {success_count} | 失败: {fail_count}") |
||||
sys.stdout.flush() |
||||
|
||||
max_retries = 2 |
||||
translate_text = None |
||||
|
||||
for attempt in range(max_retries): |
||||
translate_text = translate_with_ollama(description) |
||||
if translate_text: |
||||
break |
||||
elif attempt < max_retries - 1: |
||||
time.sleep(3) |
||||
|
||||
if translate_text: |
||||
print(translate_text) |
||||
try: |
||||
cur.execute( |
||||
"UPDATE operator SET description_cn = %s WHERE id = %s", |
||||
(translate_text, row_id) |
||||
) |
||||
success_count += 1 |
||||
last_success_id = row_id |
||||
except Exception as e: |
||||
print(f"\n[更新失败] ID:{row_id} - {e}") |
||||
fail_count += 1 |
||||
else: |
||||
fail_count += 1 |
||||
|
||||
if idx % 10 == 0: |
||||
conn.commit() |
||||
|
||||
time.sleep(1) |
||||
|
||||
conn.commit() |
||||
|
||||
print(f"\n" + "=" * 60) |
||||
print("翻译任务完成！") |
||||
print(f"✓ 成功翻译: {success_count} 条") |
||||
print(f"✗ 翻译失败: {fail_count} 条") |
||||
print(f"最后成功处理的ID: {last_success_id}") |
||||
|
||||
cur.close() |
||||
conn.close() |
||||
|
||||
except psycopg2.Error as e: |
||||
print(f"\n[数据库错误] {e}") |
||||
except KeyboardInterrupt: |
||||
print(f"\n\n用户中断程序") |
||||
print(f"已处理到ID: {last_success_id}") |
||||
conn.commit() |
||||
except Exception as e: |
||||
print(f"\n[程序错误] {e}") |
||||
finally: |
||||
if 'conn' in locals() and conn: |
||||
conn.close() |
||||
File diff suppressed because it is too large
Load Diff
@ -0,0 +1 @@ |
||||
['operating_income', 'revenue', 'sales', 'market_cap', 'market_value', 'valuation', 'book_value', 'total_assets', 'total_liabilities', 'shareholder_equity', 'capitalization', 'pe_ratio', 'pb_ratio', 'ps_ratio', 'net_income', 'gross_profit', 'operating_profit', 'cash_flow', 'operating_cash_flow', 'free_cash_flow'] |
||||
Loading…
Reference in new issue