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Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts (0)
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BibTeX
@MISC{Andersen_answeringthe,
author = {Torben G. Andersen and Tim Bollerslev},
title = {Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts},
year = {}
}
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Abstract
Volatility permeates modern financial theories and decision making processes. As such, accurate measures and good forecasts of future volatility are critical for the implementation and evaluation of asset and derivative pricing theories as well as trading and hedging strategies. In response to this, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility at the daily and lower frequencies using ARCH and stochastic volatility type models. Most of these studies find highly significant in-sample parameter estimates and pronounced intertemporal volatility persistence. Meanwhile, when judged by standard forecast evaluation criteria, based on the squared or absolute returns over daily or longer forecast horizons, standard volatility models provide seemingly poor forecasts. The present paper demonstrates that, contrary to this contention, in empirically realistic situations the models actually produce strikingly accurate interdaily forecasts f...
Keyphrases
absolute return financial market volatility future volatility decision making process accurate measure realistic situation voluminous literature significant in-sample parameter estimate modern financial theory derivative pricing theory pronounced intertemporal volatility persistence strikingly accurate interdaily forecast temporal dependency forecast horizon stochastic volatility type model present paper standard forecast evaluation criterion standard volatility model poor forecast good forecast
