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Bootstrapping high-frequency jump tests

Author

Listed:
  • Prosper Dovonon
  • Silvia Gonçalves
  • Ulrich Hounyo
  • Nour Meddahi

Abstract

The main contribution of this article is to propose a bootstrap test for jumps based on functions of realized volatility and bipower variation. Bootstrap intraday returns are randomly generated from a mean zero Gaussian distribution with a variance given by a local measure of integrated volatility (which we denote by {v^in}$\lbrace \hat{v}_{i}^{n}\rbrace $). We first discuss a set of high-level conditions on {v^in}$\lbrace \hat{v}_{i}^{n}\rbrace $ such that any bootstrap test of this form has the correct asymptotic size and is alternative-consistent. We then provide a set of primitive conditions that justify the choice of a thresholding-based estimator for {v^in}$\lbrace \hat{v}_{i}^{n}\rbrace $. Our cumulant expansions show that the bootstrap is unable to mimic the higher-order bias of the test statistic. We propose a modification of the original bootstrap test which contains an appropriate bias correction term and for which second-order asymptotic refinements are obtained.
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Suggested Citation

  • Prosper Dovonon & Silvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2016. "Bootstrapping high-frequency jump tests," CIRANO Working Papers 2016s-24, CIRANO.
    • Handle: RePEc:cir:cirwor:2016s-24
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    File URL: https://cirano.qc.ca/files/publications/2016s-24.pdf
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Hounyo, Ulrich & Varneskov, Rasmus T., 2020. "Inference for local distributions at high sampling frequencies: A bootstrap approach," Journal of Econometrics, Elsevier, vol. 215(1), pages 1-34.
    2. Jiao, Xiyu & Pretis, Felix & Schwarz, Moritz, 2024. "Testing for coefficient distortion due to outliers with an application to the economic impacts of climate change," Journal of Econometrics, Elsevier, vol. 239(1).
    3. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    4. Yuma Uehara, 2023. "Bootstrap method for misspecified ergodic Lévy driven stochastic differential equation models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(4), pages 533-565, August.
    5. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    6. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    7. Baruník Jozef & Fišer Pavel, 2024. "Co-Jumping of Treasury Yield Curve Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(3), pages 481-506.
    8. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    9. Ulrich Hounyo & Rasmus T. Varneskov, 2018. "Inference for Local Distributions at High Sampling Frequencies: A Bootstrap Approach," CREATES Research Papers 2018-16, Department of Economics and Business Economics, Aarhus University.
    10. Zhang, Chuanhai & Liu, Zhi & Liu, Qiang, 2021. "Jumps at ultra-high frequency: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    11. Markus Bibinger & Nikolaus Hautsch & Alexander Ristig, 2024. "Jump detection in high-frequency order prices," Papers 2403.00819, arXiv.org.
    12. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
    13. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.

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    Keywords

    jumps; bootstrap; block multipower variation;
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