Abstract

This paper evaluates the forecasting performance of alternative models for the one-day ahead forecasts of BIST-30 index (Istanbul Stock Exchange- Borsa Istanbul major index that contains 30 blue-chip stocks) volatility. Realized volatility is used as the relevant benchmark for the evaluation of forecasts. We document evidence, which shows that realized volatility is a less noisy estimator than the daily square benchmark explaining more of the variation in the volatility. In addition; the benefit of using extreme value estimators as volatility proxies are discussed. It is empirically demonstrated that the extreme value estimators are 5 to 8 times more efficient than historical volatility measures. The use of extreme value estimators with simple forecasting models provide better short-term forecasts than the GARCH based volatility forecasts due to higher efficiency of extreme value estimators.

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