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The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index

Author

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  • Adam Clements

    () (QUT)

  • Yin Liao

    () (QUT)

Abstract

Modeling and forecasting realized volatility is of paramount importance. Previous studies have examined the role of both the continuous and jump components of volatility in forecasting. This paper considers how to use index level jumps and cojumps across index constituents for forecasting index level volatility. In combination with the magnitude of past index jumps, the intensity of both index jumps and cojumps are examined. Estimated jump intensity from a point process model is used within a forecasting regression framework. Even in the presence of the diffusive part of total volatility, and past jump size, intensity of both index and cojumps are found to significantly improve forecast accuracy. An important contribution is that information relating to the behaviour of underlying constituent stocks is useful for forecasting index level behaviour. Improvements in forecast performance are particularly apparent on the days when jumps or cojumps occur, or when markets are turbulent.

Suggested Citation

  • Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
  • Handle: RePEc:qut:auncer:2014_02
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    File URL: http://www.ncer.edu.au/papers/documents/WP101.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Realized volatility; diffusion; jumps; point process; Hawkes process; forecasting;
    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
    • G00 - Financial Economics - - General - - - General

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