Heteroscedastic return residuals
Question
Residual variance increases in volatile markets. What changes about OLS coefficients and standard errors?
Short answer
Under a correctly specified conditional mean and exogenous regressors, heteroscedasticity alone does not create coefficient bias. It invalidates the usual homoscedastic variance estimator and sacrifices classical efficiency. Use a suitable heteroscedasticity-robust covariance estimator, or HAC when serial dependence is also relevant. Weighted least squares can improve efficiency if its variance model is defensible; it is not a cure for an incorrect conditional mean.
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Open the worked solutionLessons behind this question
- Ridge, Lasso, and Elastic Net
- The Normal Equations: Closed-Form Least Squares
- Covariance and Correlation
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