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Forecasting daily volatility with intraday data


Author Info

  • Bart Frijns
  • Dimitris Margaritis


The aim of this paper is to assess to what extent intraday data can explain and predict end-of-the-day volatility. Using a realized volatility measure as proposed by Andersen, T., T. Bollerslev, F. Diebold, and P. Labys. 2001. The distribution of realized exchange rate volatility. Journal of the American Statistical Association 96: 42-55, we hypothesize that volatility generated at the start of the day is an important predictor of daily volatility either on its own accord or in conjunction with information about the seasonal pattern characterizing intraday volatility. We address the question of how much information needs to arrive to the market before a good predictor can be formed. Using data from a specialist market (NYSE), a dealer market (Nasdaq) and a continuous auction market (Paris Bourse), we investigate how different trading structures may affect intraday volatility formation. As a preview to our results, we find that the explanatory power of first-hour volatility for daily volatility is as high as 68%, whereas the average volatility generated during this first hour is <30%. Comparison to a standard GARCH model shows that the forecasts based on the intraday data are generally highly informative both on their own accord and in combination with the GARCH forecasts.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

Volume (Year): 14 (2008)
Issue (Month): 6 ()
Pages: 523-540

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Handle: RePEc:taf:eurjfi:v:14:y:2008:i:6:p:523-540

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Related research

Keywords: intraday return volatility; volatility forecasting; realized volatility; quadratic variation;


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Cited by:
  1. Jan Hanousek & Evžen Kočenda, 2011. "Foreign News and Spillovers in Emerging European Stock Markets," Review of International Economics, Wiley Blackwell, vol. 19(1), pages 170-188, 02.
  2. Daniel Jubinski & Amy F. Lipton, 2012. "Equity volatility, bond yields, and yield spreads," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(5), pages 480-503, 05.


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