Signal Decay Quant Interview Guide
Signal decay quant interview guide covering horizon, half-life, turnover, costs, decay curves, examples, and monitoring.
Candidates evaluating how predictive signals weaken over time.
Signal decay measures how edge fades
A signal may predict returns strongly over one horizon and weakly or negatively over another, so horizon choice is part of evaluation.
Half-life connects signal and turnover
Fast-decaying signals may require frequent trading, which raises transaction costs, capacity limits, and execution risk.
Concrete example
A news sentiment signal might matter for hours, while a value signal might be evaluated over weeks or months before decay.
Decay should be monitored
Market adaptation, crowding, data changes, and regime shifts can shorten a signal half-life after deployment in live trading.
Common mistakes
Candidates often report one return horizon. A stronger answer shows performance across horizons and after realistic costs.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.