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Econometrics of co-jumps in high-frequency data with noise

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  • Bibinger, Markus
  • Winkelmann, Lars

Abstract

We establish estimation methods to determine co-jumps in multivariate high-frequency data with non-synchronous observations and market microstructure. A rate-optimal estimator of the entire quadratic covariation of an Itô-semimartingale is constructed by a locally adaptive spectral approach. Thresholding allows to disentangle the co-jump from the continuous part. We derive a feasible limit theorem for a truncated estimator of integrated covolatility which facilitates asymptotically efficient (co-)volatility estimation in the presence of jumps. A test for common jumps is presented. Simulations and an empirical application to intra-day tick-data from EUREX futures demonstrate the practical value of the approach.

Suggested Citation

  • Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    • Handle: RePEc:eee:econom:v:184:y:2015:i:2:p:361-378
    DOI: 10.1016/j.jeconom.2014.10.004
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    Cited by:

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    2. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    3. Li, Chenxing & Maheu, John M, 2020. "A Multivariate GARCH-Jump Mixture Model," MPRA Paper 104770, University Library of Munich, Germany.
    4. Winkelmann, Lars & Yao, Wenying, 2020. "Cojump anchoring," Discussion Papers 2020/17, Free University Berlin, School of Business & Economics.
    5. Lars Winkelmann & Wenying Yao, 2024. "Tests for Jumps in Yield Spreads," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 946-957, July.
    6. Tim Bollerslev & Jia Li & Leonardo Salim Saker Chaves, 2021. "Generalized Jump Regressions for Local Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1015-1025, October.
    7. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    8. Christophe Boucher & Gilles de Truchis & Elena Ivona Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," Working Papers hal-04141651, HAL.
    9. Liao, Yin & Anderson, Heather M., 2019. "Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
    10. Christophe Boucher & Gilles de Truchis & Elena Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," EconomiX Working Papers 2017-20, University of Paris Nanterre, EconomiX.
    11. Arnaud Gloter & Dasha Loukianova & Hilmar Mai, 2016. "Jump filtering and efficient drift estimation for Lévy-Driven SDE’S," Working Papers 2016-04, Center for Research in Economics and Statistics.
    12. Weijia Peng & Chun Yao, 2022. "Co-Jumps, Co-Jump Tests, and Volatility Forecasting: Monte Carlo and Empirical Evidence," JRFM, MDPI, vol. 15(8), pages 1-21, July.
    13. Bibinger, Markus & Neely, Christopher & Winkelmann, Lars, 2019. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 158-184.
    14. Caporin, Massimiliano & Kolokolov, Aleksey & Renò, Roberto, 2017. "Systemic co-jumps," Journal of Financial Economics, Elsevier, vol. 126(3), pages 563-591.
    15. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    16. 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.
    17. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    18. Maria Elvira Mancino & Maria Cristina Recchioni, 2015. "Fourier Spot Volatility Estimator: Asymptotic Normality and Efficiency with Liquid and Illiquid High-Frequency Data," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-33, September.
    19. Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    20. Berger, Theo & Gençay, Ramazan, 2018. "Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 30-46.
    21. Shen, Yiwen & Shi, Meiqi, 2024. "Intraday variation in cross-sectional stock comovement and impact of index-based strategies," Journal of Financial Markets, Elsevier, vol. 68(C).
    22. Ole Martin & Mathias Vetter, 2019. "Laws of large numbers for Hayashi–Yoshida-type functionals," Finance and Stochastics, Springer, vol. 23(3), pages 451-500, July.

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    More about this item

    Keywords

    Co-jumps; Covolatility estimation; Microstructure noise; Non-synchronous observations; Truncation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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