Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/14690
Title: | On forecasting daily stock volatility: The role of intraday information and market conditions | Authors: | Fuertes, Ana Maria Izzeldin, Marwan Kalotychou, Elena |
Major Field of Science: | Social Sciences | Field Category: | Economics and Business | Keywords: | Conditional variance;Superior predictive ability;Realised volatility;Nonparametric estimators;Intraday price | Issue Date: | Apr-2009 | Source: | International Journal of Forecasting, 2009, vol. 25, no. 2, pp. 259-281 | Volume: | 25 | Issue: | 2 | Start page: | 259 | End page: | 281 | Journal: | International Journal of Forecasting | Abstract: | Several recent studies advocate the use of nonparametric estimators of daily price variability that exploit intraday information. This paper compares four such estimators, realised volatility, realised range, realised power variation and realised bipower variation, by examining their in-sample distributional properties and out-of-sample forecast ranking when the object of interest is the conventional conditional variance. The analysis is based on a 7-year sample of transaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH framework and relies on several loss functions. The realized range fares relatively well in the in-sample fit analysis, 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. Forecast combination of all four intraday measures produces the smallest forecast errors in about half of the sampled stocks. A market conditions analysis reveals that the additional use of intraday data on day t - 1 to forecast volatility on day t is most advantageous when day t is a low volume or an up-market day. These results have implications for option pricing, asset allocation and value-at-risk. | URI: | https://hdl.handle.net/20.500.14279/14690 | ISSN: | 01692070 | DOI: | 10.1016/j.ijforecast.2009.01.006 | Rights: | © Elsevier | Type: | Article | Affiliation : | City University London Lancaster University |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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