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Modeling and forecasting return jumps using realized variation measures

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  • Liu, Yi
  • Liu, Huifang
  • Zhang, Lei

Abstract

This paper proposes a simple HAR-RV-based model to predict return jumps through a conditional density of jump size with time-varying moments. We model jump occurrences based on a version of the autoregressive conditional hazard model that relies on past continuous realized volatilities. Applying our methodology to seven equity indices on the U.S. and Chinese stock markets, we reach the following key findings: (i) jump occurrence and size are dependent on past realized volatility, (ii) the proposed model yields superior in- and out-of-sample jump size density forecasts compared to an ARMA(1,1)-GARCH(1,1) model, (iii) and the occurrence and sign of return jumps are predictable to some extent.

Suggested Citation

  • Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
  • Handle: RePEc:eee:ecmode:v:76:y:2019:i:c:p:63-80
    DOI: 10.1016/j.econmod.2018.07.020
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    More about this item

    Keywords

    Realized variation; Jumps; Hazard rates; Probability forecast; Density forecast;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G1 - Financial Economics - - General Financial Markets
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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