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A Consistent and Robust Test for Autocorrelated Jump Occurrences

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  • Simon Kwok

Abstract

We develop a nonparametric test for the temporal dependence of jump occurrences in the population. The test is consistent against all pairwise serial dependence, and is robust to the jump activity level and the choice of sampling scheme. We establish asymptotic normality and local power property for a rich set of local alternatives, including both self-exciting and/or self-inhibitory jumps. Simulation study confirms the robustness of the test and reveals its competitive size and power performance over existing tests. In an empirical study on high-frequency stock returns, our procedure uncovers a wide array of autocorrelation profiles of jump occurrences for different stocks in different time periods.

Suggested Citation

  • Simon Kwok, 2024. "A Consistent and Robust Test for Autocorrelated Jump Occurrences," Journal of Financial Econometrics, Oxford University Press, vol. 22(1), pages 157-186.
    • Handle: RePEc:oup:jfinec:v:22:y:2024:i:1:p:157-186.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbac031
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    More about this item

    Keywords

    autocorrelation; financial contagion; nonparametric test; self-excited jumps; self-inhibitory jumps;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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