Heteroskedasticity breaks your standard errors, not your coefficients
Asked at Squarepoint
Your regression errors have non-constant variance, volatility clusters, so changes across observations.
Does this bias your OLS coefficients? If not, what exactly does it break, and how do you fix it?
Show a hint
Which part of the classical OLS results uses the constant-variance assumption, the point estimates, or their standard errors?
Your answer
This one is open-ended. Work it through, then check your reasoning against the full solution.