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Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns

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Author Info

  • Torben G. Andersen

    ()
    (Northwestern University, NBER, and CREATES)

  • Tim Bollerslev

    ()
    (Duke University, NBER, and CREATES)

  • Per Frederiksen

    ()
    (Nordea Markets)

  • Morten Ørregaard Nielsen

    ()
    (Queen's University and CREATES)

Abstract

We provide an empirical framework for assessing the distributional properties of daily speculative returns within the context of the continuous-time jump diffusion models traditionally used in asset pricing finance. Our approach builds directly on recently developed realized variation measures and non-parametric jump detection statistics constructed from high-frequency intraday data. A sequence of simple-to-implement moment-based tests involving various transformations of the daily returns speak directly to the importance of different distributional features, and may serve as useful diagnostic tools in the specification of empirically more realistic continuous-time asset pricing models. On applying the tests to the thirty individual stocks in the Dow Jones Industrial Average index, we find that it is important to allow for both time-varying diffusive volatility, jumps, and leverage effects to satisfactorily describe the daily stock price dynamics.

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File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1173.pdf
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Bibliographic Info

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 1173.

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Length: 69 pages
Date of creation: Jul 2008
Date of revision:
Handle: RePEc:qed:wpaper:1173

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Keywords: return distributions; continuous-time models; mixture-of-distributions hypothesis; financial-time sampling; high-frequency data; volatility signature plots; realized volatilities; jumps; leverage and volatility feedback effects;

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