A Reality Check for Data Snooping¶
White, H. (2000). A Reality Check for Data Snooping. Econometrica, 68(5), 1097-1126.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Mechanisms¶
- Forecast Backtesting
- Its failure modes cluster around fooling yourself: backtest overfitting and data-snooping (tuning knobs until the historical curve looks good, then mistaking that fit for predictive skill), look-ahead leakage, survivorship, and regimes simply missing from history.
This sourceDefines data snooping as repeated use of the same data for model selection and warns that apparently good predictive results may be due to chance.
- Its failure modes cluster around fooling yourself: backtest overfitting and data-snooping (tuning knobs until the historical curve looks good, then mistaking that fit for predictive skill), look-ahead leakage, survivorship, and regimes simply missing from history.
- Proximity Signal Backtest
- Its failure mode is overfitting the past — with enough dimensions and enough tuning, a metric can be made to "predict" historical outcomes perfectly by memorizing noise, a form of data-snooping bias that collapses the moment it meets new cases.
This sourceShows how repeated model search on one historical data set can produce apparently successful forecasts by chance rather than genuine predictive ability.
- Its failure mode is overfitting the past — with enough dimensions and enough tuning, a metric can be made to "predict" historical outcomes perfectly by memorizing noise, a form of data-snooping bias that collapses the moment it meets new cases.
Verification¶
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Registry ID ref:1663ff879538 · see in the full table