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statistical-testing skill: optional signal-column support (enables time-shift decay test)

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技术栈
python

调研方向

Read the statistical-testing skill's input model and data discovery step, then review related issue #17 for the factor suite design. Define how an optional numeric signal column is identified and confirmed, and how multi-horizon IC, shifted IC decay, and single-asset half-life diagnostics are reported. Done when signal diagnostics run for confirmed candidates while inputs without a signal retain the existing behavior.

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描述

enhancement

Context

The QuantGPT time-shift decay test (shift factor values by 5/10/20 days; a real signal should weaken, not persist — persistence implies the backtest fit a lagged/regime artifact) did not port into the statistical-testing skill because the skill's data model is date + returns only, with no raw signal column.

Proposal

Extend the skill's accepted input to an optional signal column alongside returns (e.g. signal, score, forecast). When present, enable:

  1. Signal→forward-return IC at multiple horizons (1/5/10/20d): rank correlation between signal at t and strategy/asset forward return. Establishes the signal actually predicts what it claims.
  2. Time-shift decay: recompute IC with signal shifted 5/10/20d forward. Pass: shifted |IC| < real |IC| at every shift. Failure means the "edge" is a lagged exposure (e.g., just holding yesterday's beta).
  3. Half-life of predictive power — fold into #17 (factor suite) once panel data is supported; single-asset decay curve can live here.

Design notes

  • Absent: no engine look-ahead concerns here — this is research-side validation, all shifts applied explicitly.
  • Data discovery (Step 1) should flag a numeric signal column as signal_candidate and ask the user whether to run signal diagnostics.
  • Related: #17 (full cross-sectional factor suite — this issue is the single-series subset).
主要语言
Python
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  3. Fork 仓库,在一个分支上完成修改。
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