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A Markov Chain Estimator of Multivariate Volatility from High Frequency Data

In: The Fascination of Probability, Statistics and their Applications

Author

Listed:
  • Peter Reinhard Hansen

    (European University Institute and CREATES)

  • Guillaume Horel

    (Serenitas Capital)

  • Asger Lunde

    (University of Aarhus and CREATES)

  • Ilya Archakov

    (European University Institute)

Abstract

We introduce a multivariate estimator of financial volatility that is based on the theory of Markov chains. The Markov chain framework takes advantage of the discreteness of high-frequency returns. We study the finite sample properties of the estimation in a simulation study and apply it to high-frequency commodity prices.

Suggested Citation

  • Peter Reinhard Hansen & Guillaume Horel & Asger Lunde & Ilya Archakov, 2016. "A Markov Chain Estimator of Multivariate Volatility from High Frequency Data," Springer Books, in: Mark Podolskij & Robert Stelzer & Steen Thorbjørnsen & Almut E. D. Veraart (ed.), The Fascination of Probability, Statistics and their Applications, pages 361-394, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-25826-3_17
    DOI: 10.1007/978-3-319-25826-3_17
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    Cited by:

    1. Siem Jan Koopman & Rutger Lit & André Lucas, 2017. "Intraday Stochastic Volatility in Discrete Price Changes: The Dynamic Skellam Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1490-1503, October.
    2. Bian, Siyu & Serra, Teresa & Garcia, Philip & Irwin, Scott, 2022. "New evidence on market response to public announcements in the presence of microstructure noise," European Journal of Operational Research, Elsevier, vol. 298(2), pages 785-800.
    3. Ilya Archakov, 2026. "A Robust Similarity Estimator," Papers 2601.12198, arXiv.org.

    More about this item

    Keywords

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    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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