How a Wrong Date Column Silently Ruins Numerai Signals Backtests

Developers building stock market signals for the Numerai tournament risk inflating backtest performance by joining fundamental data on fiscal period-end dates rather than the date information was actually filed publicly. Most data vendors store fundamentals keyed to a period-end or a generic report date, meaning pipelines can inadvertently feed models revised figures that were not yet available at the time being modeled — a form of lookahead bias. The correct fix is using a first_filed timestamp from SEC EDGAR, which anchors each data row to the moment the figure became publicly knowable, enabling a simple query filter to prevent future data from leaking into past feature windows. Unlike a blanket 90-day lag applied uniformly across all filers, this approach accounts for the wide variation in filing timelines between large and small companies. An analysis of one such dataset found restatements in roughly 18,700 out of 313,000 rows, underscoring that data revisions are frequent enough to meaningfully distort backtests if left unaddressed.