As mentioned in my last post,
volatility of stock returns vary over time (Heteroscedasticity) and they happen
in a systematic way so as to ensure mean reversion. The concept is appealing
well beyond the regular homoscedastic models which assume constant volatility. And
so the best book I had that provided hands on model calibration experience was
the elementary “Time Series Analysis by Cryer and Chan”.
Wiki says on the subject:
“The
possible existence of heteroscedasticity is a major concern in the application
of regression analysis, including the analysis of variance, because the presence of heteroscedasticity can
invalidate statistical tests of significance that assume that the modeling errors are uncorrelated and normally distributed
and that their variances do not vary with the effects being modeled.”
