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Statistical Surveillance of Volatility Forecasting Models

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  • Vasyl Golosnoy
  • Iryna Okhrin
  • Wolfgang Schmid

Abstract

This paper elaborates sequential procedures for monitoring the validity of a volatility model. A state-space representation describes dynamics of daily integrated volatility. The observation equation relates the integrated volatility to its measures such as the realized volatility or bipower variation. On-line control procedures, based on volatility forecasting errors, allow us to decide whether the chosen representation remains correctly specified. A signal indicates that the assumed volatility model may no longer be valid. The performance of our approach is analyzed within a Monte Carlo simulation study and illustrated in an empirical application for selected U.S. stocks. Copyright The Author 2011. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.

Suggested Citation

  • Vasyl Golosnoy & Iryna Okhrin & Wolfgang Schmid, 2012. "Statistical Surveillance of Volatility Forecasting Models," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 513-543, June.
    • Handle: RePEc:oup:jfinec:v:10:y:2012:i:3:p:513-543
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbr017
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    Cited by:

    1. Miriam Isabel Seifert, 2023. "Characterization of valid auxiliary functions for representations of extreme value distributions and their max-domains of attraction," Papers 2311.15355, arXiv.org.
    2. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    3. Vasyl Golosnoy, 2018. "Sequential monitoring of portfolio betas," Statistical Papers, Springer, vol. 59(2), pages 663-684, June.
    4. Holger Dette & Vasyl Golosnoy & Janosch Kellermann, 2023. "The effect of intraday periodicity on realized volatility measures," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(3), pages 315-342, April.

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