Multiple Testing Quant Interview Guide
Multiple testing quant interview guide for repeated tests, false positives, signal research, correction intuition, and caveats.
Research candidates discussing many tests, signals, or features.
Many tests create false positives
If you test many unrelated ideas, some can look significant by chance. This matters in signal research and feature selection.
Think in families of tests
The risk depends on how many comparisons are being considered together and what decision follows from them after the search is complete.
Concrete example
Testing 100 random signals at a 5 percent threshold can produce several apparent winners even if none have real predictive value.
Mention correction intuition
Corrections, holdouts, and validation can reduce false discoveries. The right approach depends on the research context and the cost of missing real signals.
Common mistakes
Candidates often evaluate the best-looking result as if it were the only test. Selection after many tests changes interpretation.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.