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Jump Testing and the Speed of Market Adjustment

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  • Torben B. Rasmussen

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    (Aarhus University and CREATES)

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    Abstract

    Asymptotic properties of jump tests rely on the property that any jump occurs within a single time interval no matter what the observation frequency is. Market microstructure effects in relation to news-induced revaluation of the underlying variable is likely to make this an unrealistic assumption for high-frequency transaction data. To capture these microstructure effects, this paper suggests a model in which market prices adjust gradually to jumps in the underlying effcient price. A case study illustrates the empirical relevance of the model, and the performance of different jump tests is investigated here and in a simulation study. Evidence indicates that tests based on the largest of scaled price increments perform better than tests comparing measures of variability. Resolving the matter by testing at lower frequencies turns out to be less straightforward.

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    File URL: ftp://ftp.econ.au.dk/creates/rp/09/rp09_08.pdf
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    Bibliographic Info

    Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2009-08.

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    Length: 49
    Date of creation: 27 Feb 2009
    Date of revision:
    Handle: RePEc:aah:create:2009-08

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    Web page: http://www.econ.au.dk/afn/

    Related research

    Keywords: jumps; hypothesis tests; market microstructure noise; high-frequency data.;

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    16. Mark Podolskij & Daniel Ziggel, 2008. "New tests for jumps: a threshold-based approach," CREATES Research Papers 2008-34, School of Economics and Management, University of Aarhus.
    17. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 1-37.
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    20. Jacod, Jean & Li, Yingying & Mykland, Per A. & Podolskij, Mark & Vetter, Mathias, 2007. "Microstructure noise in the continuous case: the pre-averaging approach," Technical Reports 2007,41, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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