++

prepare_prompt/all_data_combined.csv

@@ -1,4 +1,3 @@
-id,name,description,dataset_id,dataset_name,category_id,category_name,region,delay,universe,type,description_cn,tags
 1,call_breakeven_10,"Price at which a stock's call options with expiration 10 days in the future break even based on its recent bid/ask mean.",option9,Options Analytics,option,Option,USA,1,TOP3000,MATRIX,股票在10天后到期的看涨期权基于最近bid/ask均价的盈亏平衡点价格,期权;最近;盈亏;均价;价格;基于;股票;到期;bid;看涨;ask;平衡点;天后
 2,call_breakeven_1080,"Price at which a stock's call options with expiration 1080 days in the future break even based on its recent bid/ask mean.",option9,Options Analytics,option,Option,USA,1,TOP3000,MATRIX,基于最近bid/ask均价，距今1080天后到期的股票看涨期权盈亏平衡点价格,期权;最近;盈亏;均价;1080;价格;基于;ask;距今;bid;到期;股票;看涨;平衡点;天后
 3,call_breakeven_120,"Price at which a stock's call options with expiration 120 days in the future break even based on its recent bid/ask mean.",option9,Options Analytics,option,Option,USA,1,TOP3000,MATRIX,股票距今120天到期的看涨期权盈亏平衡点价格基于最近bid/ask均价,期权;价格;盈亏;最近;均价;基于;距今;到期;股票;看涨;bid;ask;平衡点;120

prepare_prompt/alpha_prompt.txt

@@ -1,12 +1,14 @@
 任务指令
-假设
-市场对企业的流动性风险存在阶段性定价偏差。当企业短期融资依赖度上升但经营性现金流未能同步改善时，市场往往低估其潜在的偿债压力与折价抛售资产风险，导致股价在未来1-3个季度内表现疲软。反之，当企业主动降低短期融资依赖、增强经营性现金流与短期债务的匹配度时，其财务稳健性的提升可能未被市场及时充分定价，从而存在超额收益机会。
+Residual Value Fluctuation Arbitrage Factor
 
-实施方案
-使用“短期有息负债”、“经营性现金流净额”及“货币资金”等基础数据字段，构建核心指标“流动性错配度”（LMD）= （短期有息负债 - 货币资金） / 过去四个季度平均经营性现金流净额。使用时序差分算子（ts_delta）计算LMD在过去两个季度的变化方向与幅度，并结合横截面排名算子（cs_rank）确定其在全市场中的相对位置。对LMD指标显著恶化（排名上升幅度居前）的公司建立空头仓位，对LMD指标持续改善（排名下降幅度居前）的公司建立多头仓位。
+Hypothesis
+In capital-intensive industries utilizing operating leases (e.g., airlines, retail, industrial equipment), fluctuations in the estimated residual value of leased assets reflect market divergence regarding the assets' long-term worth. An upward, out-of-expectations revision in the residual value estimate disclosed in financial reports signals increased optimism from management or appraisers concerning the asset's economic life, technological obsolescence risk, or secondary market liquidity. This optimism may precede an actual improvement in the asset's realizable value or a reduction in discounting costs, serving as a potential positive signal. Conversely, a downward, unexpected revision may foreshadow potential asset impairment and future cash flow erosion.
 
-阿尔法因子优化建议
-该因子信号可能受行业运营资本周期特性干扰。建议采用动态行业分档中性化：首先根据企业历史现金流波动性（使用ts_stddev算子）将其划分为“现金流稳定型”与“现金流周期型”两组，再在各自组内按细分行业进行横截面比较和排名调整。此举可在保留跨行业可比性的同时，更精准地捕捉行业内因流动性管理能力差异而产生的Alpha。
+Implementation
+Construct a "Residual Value Revision Intensity" metric using data from financial statement notes related to "Lease Liabilities," specifically the present value of future minimum lease payments and the estimated residual value of leased assets. The calculation is: (Current Period Disclosed Residual Value Estimate - Prior Period Estimate) / Total Carrying Value of Leased Assets. Employ a time-series breakout detection operator (e.g., ts_breakout or residual analysis) to identify anomalous adjustment points where the estimate deviates from its historical trend. For companies identified with a positive anomalous adjustment, gradually establish a long position after a defined lag period (e.g., 1-3 months) following the disclosure. For those with a negative anomalous adjustment, establish a short position. Use a time-series backfill operator to ensure data continuity.
+
+Alpha Factor Optimization Suggestions
+The efficacy of this factor is likely highly dependent on asset characteristics. It is recommended to introduce asset-segmentation grouping: for instance, group leased assets by type (aircraft, vessels, retail storefronts, IT equipment) and compute the cross-sectional percentile of the Residual Value Revision Intensity within each group. Additionally, overlay industry capacity utilization or secondary asset transaction price momentum as confirming signals. Enhance the factor weight when a residual value upward revision coincides with improving activity in the corresponding asset's secondary market. Conversely, attenuate the signal when these metrics diverge.
 
 *=========================================================================================*
 

prepare_prompt/keys_text.txt

@@ -1 +1,10 @@
-["debt", "cash", "flow", "short", "term", "current", "liabilities", "operating", "interest", "borrowing", "loan", "payable", "obligation", "assets", "currency", "financial", "financing", "capital", "working", "fund", "liquidity", "risk", "maturity", "due", "amount", "outstanding", "balance", "repayment", "facility", "credit", "line", "revolver", "note", "bond", "security", "instrument", "derivative", "hedge", "swap", "rate", "cost", "expense", "charge", "fee", "accrued", "accrual", "provision", "reserve", "allowance", "coverage", "ratio"]
+**Residual Value Fluctuation Arbitrage Factor**
+
+**Hypothesis**
+In capital-intensive industries utilizing operating leases (e.g., airlines, retail, industrial equipment), fluctuations in the estimated residual value of leased assets reflect market divergence regarding the assets' long-term worth. An upward, out-of-expectations revision in the residual value estimate disclosed in financial reports signals increased optimism from management or appraisers concerning the asset's economic life, technological obsolescence risk, or secondary market liquidity. This optimism may precede an actual improvement in the asset's realizable value or a reduction in discounting costs, serving as a potential positive signal. Conversely, a downward, unexpected revision may foreshadow potential asset impairment and future cash flow erosion.
+
+**Implementation**
+Construct a "Residual Value Revision Intensity" metric using data from financial statement notes related to "Lease Liabilities," specifically the present value of future minimum lease payments and the estimated residual value of leased assets. The calculation is: (Current Period Disclosed Residual Value Estimate - Prior Period Estimate) / Total Carrying Value of Leased Assets. Employ a time-series breakout detection operator (e.g., `ts_breakout` or residual analysis) to identify anomalous adjustment points where the estimate deviates from its historical trend. For companies identified with a positive anomalous adjustment, gradually establish a long position after a defined lag period (e.g., 1-3 months) following the disclosure. For those with a negative anomalous adjustment, establish a short position. Use a time-series backfill operator to ensure data continuity.
+
+**Alpha Factor Optimization Suggestions**
+The efficacy of this factor is likely highly dependent on asset characteristics. It is recommended to introduce **asset-segmentation grouping**: for instance, group leased assets by type (aircraft, vessels, retail storefronts, IT equipment) and compute the cross-sectional percentile of the Residual Value Revision Intensity within each group. Additionally, overlay **industry capacity utilization** or **secondary asset transaction price momentum** as confirming signals. Enhance the factor weight when a residual value upward revision coincides with improving activity in the corresponding asset's secondary market. Conversely, attenuate the signal when these metrics diverge.