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The Stochastic Component Of Realized Volatility

Author

Listed:
  • WAI MUN FONG

    (Department of Finance and Accounting, National University of Singapore, Singapore;
    Department of Economics, National University of Singapore, Singapore)

  • WING-KEUNG WONG

    (Department of Economics, National University of Singapore, Singapore)

Abstract

Volatility–volume regressions provide a convenient framework to study sources of volatility predictability. We apply this approach to the daily realized volatility of common stocks. We find that unexpected volume plays a more significant role in explaining realized volatility than expected volume, and accounts for about one-third of the non-persistent component in the volatility process. Contrary to the findings of Lamoureux and Lastrapes (1990), the ARCH effect is robust even in the presence of volume. However, this component explains only about half of the variations in realized volatility. Thus, large portion of realized volatility is clearly stochastic. This presents a significant challenge to the goal of achieving precise realized volatility forecasts.

Suggested Citation

  • Wai Mun Fong & Wing-Keung Wong, 2006. "The Stochastic Component Of Realized Volatility," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(01), pages 1-34.
    • Handle: RePEc:wsi:afexxx:v:02:y:2006:i:01:n:s2010495206500047
    DOI: 10.1142/S2010495206500047
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    More about this item

    Keywords

    Realized volatility; trading volume; autoregressive models; ARCH; C22; G10;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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