Look-ahead bias
Use only available information.
A current return cannot use a macro signal that was known only after that return.
Statistical analysis
Challenge the result before using it.
Prevent future information from entering the model. Test whether a finding survives different assumptions and uncertain samples.
Visual model
A point estimate is not enough.
Use information available at the time, test several classifications, measure uncertainty, and compare independent implementations.
Look-ahead biasSensitivity testingBootstrap uncertaintyReconciliation
Time t−1Available signal
→
Time tObserved return
→
ChallengeSix thresholds
→
Uncertainty5,000 resamples
→
Control24 / 24 match
Sensitivity testing
Change the assumptions.
Repeat the analysis across plausible thresholds and compare the conclusion.
Uncertainty
Show the range.
Bootstrap intervals show when a strong point estimate is still imprecise.
Reconciliation
Compare independent outputs.
Agreement between Python and PostgreSQL reduces implementation risk.
Where I used it
Regime analysis under challenge
A one-day lag, six threshold combinations, 5,000 resamples, and 24 reconciled outputs define the evidence boundary.
View project evidence →Association before experimentation
Historical behaviour defines test opportunities but does not prove causal uplift.
View project evidence →