Forecasting Daily Stock Volatility: the Role of Intraday Information and Market Conditions

72 Pages Posted: 29 May 2008 Last revised: 19 Dec 2013

See all articles by Ana-Maria Fuertes

Ana-Maria Fuertes

Cass Business School, City University of London

Elena Kalotychou

Cass Business School, City, University of London

Marwan Izzeldin

Lancaster University Management School

Date Written: May 1, 2008

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. The results have implications for value-at-risk analysis.

Keywords: Conditional variance, Quadratic variation, Nonparametric estimators, Intraday prices, Superior predictive ability

JEL Classification: C53, C32, C14

Suggested Citation

Fuertes, Ana-Maria and Kalotychou, Elena and Izzeldin, Marwan, Forecasting Daily Stock Volatility: the Role of Intraday Information and Market Conditions (May 1, 2008). International Journal of Forecasting (2009) Vol.25, 259-281 , Available at SSRN: https://ssrn.com/abstract=1137997 or http://dx.doi.org/10.2139/ssrn.1137997

Ana-Maria Fuertes (Contact Author)

Cass Business School, City University of London ( email )

Faculty of Finance
106 Bunhill Row
London, EC1Y 8TZ
United Kingdom
+44 207 477 0186 (Phone)
+44 207 477 8881 (Fax)

HOME PAGE: http://www.city.ac.uk/people/academics/ana-maria-fuertes

Elena Kalotychou

Cass Business School, City, University of London ( email )

106 Bunhill Row
London, EC1Y 8TZ
Great Britain

Marwan Izzeldin

Lancaster University Management School ( email )

Lancaster, LA1 4YX
United Kingdom
01524 594674 (Phone)

HOME PAGE: http://www.lums.lancs.ac.uk/profiles/marwan-izzeldin/

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
305
Abstract Views
1,833
rank
110,130
PlumX Metrics