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Testing for non-correlation between price and volatility jumps

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  • Jacod, Jean
  • Klüppelberg, Claudia
  • Müller, Gernot

Abstract

We consider a log-price process Xt, which is observed at discrete times 0,Δn, 2Δn,…, and the process has a stochastic squared volatility σt2. Assuming that the price process as well as the volatility process have common jumps, we suggest tests for non-correlation between log-price and squared volatility jumps, or functions of such jumps. Our tests have a prescribed asymptotic level, as the mesh Δn tends to 0 and the observation time Tn tends to ∞. The finite sample performance of our test is studied using simulations. We finally apply our tests to real data, and the test rejects the non-correlation hypothesis for the combination of squared log-price jumps and the moduli of the jumps of the squared volatility. This sheds new light on economically motivated statements on causality between price and volatility jumps and on econometric modeling.

Suggested Citation

  • Jacod, Jean & Klüppelberg, Claudia & Müller, Gernot, 2017. "Testing for non-correlation between price and volatility jumps," Journal of Econometrics, Elsevier, vol. 197(2), pages 284-297.
  • Handle: RePEc:eee:econom:v:197:y:2017:i:2:p:284-297
    DOI: 10.1016/j.jeconom.2016.11.007
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    Cited by:

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    2. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2023. "Shot-noise cojumps: exact simulation and option pricing," LSE Research Online Documents on Economics 111537, London School of Economics and Political Science, LSE Library.
    3. Deniz Erdemlioglu & Christopher J. Neely & Xiye Yang, 2023. "Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications," Working Papers 2023-016, Federal Reserve Bank of St. Louis.
    4. Ewald, Christian & Zou, Yihan, 2021. "Stochastic volatility: A tale of co-jumps, non-normality, GMM and high frequency data," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 37-52.
    5. Volk-Makarewicz, Warren & Borovkova, Svetlana & Heidergott, Bernd, 2022. "Assessing the impact of jumps in an option pricing model: A gradient estimation approach," European Journal of Operational Research, Elsevier, vol. 298(2), pages 740-751.

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