On forecasting daily stock volatility: the role of intraday information and market conditions.
Several recent studies advocate the use of nonparametric estimators of daily price vari-ability that exploit intraday information. This paper compares four such estimators, realisedvolatility, realised range, realised power variation and realised bipower variation, by examiningtheir in-sample distributional properties and out-of-sample forecast ranking when the objectof interest is the conventional conditional variance. The analysis is based on a 7-year sample oftransaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH frameworkand relies on several loss functions. The realized range fares relatively well in the in-sample .tanalysis, for instance, regarding the extent to which it brings normality in returns. However,overall the realised power variation provides the most accurate 1-day-ahead forecasts. Fore-cast combination of all four intraday measures produces the smallest forecast errors in abouthalf of the sampled stocks. A market conditions analysis reveals that the additional use ofintraday data on day t .. 1 to forecast volatility on day t is most advantageous when day t isa low volume or an up-market day. The results have implications for value-at-risk analysis.
Year of publication: |
2008
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Authors: | Fuertes, A-M ; Izzeldin, M ; Kalotychou, E |
Publisher: |
The Department of Economics |
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