Investigating Suspected Look-Ahead Bias in StockRank Gradient Factors

Summary

A user reports unusually strong factor-analysis returns after combining StockRank with a gradient factor built from a two-day moving average. They suspect look-ahead bias because the strategy produces no trade data in a simulated account, while an XGBoost version appears to work and produces simulated output. The post asks whether the gradient calculation interacts with StockRank in a way that introduces future data.

The document gives no factor formula, code, diagnostic results, or engineer response; it only describes the discrepancy and links to experiments. It therefore raises a useful research question about checking data timing and behavior across analysis, ranking, and simulation workflows, but does not establish that future information is present or explain how to detect it. The reported performance and simulation mismatch are clues to investigate, not evidence of a confirmed cause.

Key ideas

• Unusually strong factor-analysis results prompted a concern about look-ahead bias.
• The reported factor uses a gradient derived from a two-day moving average.
• The user observed different behavior between StockRank and an XGBoost workflow.
• The post offers no technical diagnosis or evidence that future data entered the calculation.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.