Volatility Forecasting Interview Guide
Volatility forecasting interview guide covering realized volatility, EWMA, GARCH, regimes, implied volatility, evaluation, and examples.
Candidates forecasting risk for trading, options, or portfolio models.
Volatility forecasts estimate future variation
A volatility forecast predicts the scale of future returns over a horizon, not the direction of those returns or trades.
Simple models are useful baselines
Historical volatility, EWMA, and GARCH-style models can be strong starting points before adding more complex predictors.
Concrete example
After a large market shock, an EWMA forecast may rise quickly because recent squared returns receive high weight in the estimate.
Evaluation needs the right target
Compare forecasts against realized volatility or variance over the same horizon, while accounting for noise and overlapping windows.
Common mistakes
Candidates often seek one best model. Volatility forecasting depends on horizon, asset class, regime, and loss function.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.