1
$\begingroup$

My hesitation, as I look at getting into forecasting based on observed variances, is the nagging question - if variances are not constant per-instrument, is it any good to use the last month or year's variance to predict this year's ?

If variances are constant(ish), then my follow-up is - what is the causal model that predicts why this is so? I'm uncomfortable without a mental model of why one stock should have variance distinct from another one, and I want to have some sense of how to know the likeliness of a sudden increase of variance, which would be very bad news indeed!

Thanks in advance.

$\endgroup$
  • $\begingroup$ Variances are definitely not constantt, they fluctuate both for market-wide reasons and (to a lesser extent) for reasons specific to each stock $\endgroup$ – noob2 Jan 29 '16 at 13:17
1
$\begingroup$

I am not sure what you are exactly asking. But usually even a simple Garch(1,1) would be the naive approach of forecasting variance using last period's variance.
A very good survey of volatility modelling on the Arch/garch family is the Hansen and Lunde 2005.

They show that hardly one can beat a garch(1,1), so that is a good first guess.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.