Statistics

Heteroscedasticity

Non-constant error variance across observations, violating a standard regression assumption.

Coefficients remain unbiased, but standard errors are wrong - so inference is unreliable even though the fit is not.

Ubiquitous in finance because of volatility clustering: calm periods and turbulent periods have very different error variances. Assuming constant variance across a sample spanning both is not a marginal violation.

Fixes: heteroscedasticity-robust (White) standard errors, weighted least squares, or modelling the variance directly with a GARCH-type model.

Recognising it as a standard-error problem rather than a coefficient problem is the distinction interviewers listen for.

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