Department of Economics and Business Economics

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

Research output: Working paperResearch

  • School of Economics and Management
We provide an empirical framework for assessing the distributional properties of daily specu-
lative returns within the context of the continuous-time modeling paradigm 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 intra-
day data. A sequence of relatively simple-to-implement moment-based tests involving various
transforms of the daily returns speak directly to the import of different features of the under-
lying continuous-time processes that might have generated the data. As such, the tests may
serve as a useful diagnostic tool in the specification of empirically more realistic asset pricing
models. Our results are also directly related to the popular mixture-of-distributions hypoth-
esis and the role of the corresponding latent information arrival process. On applying our
sequential test procedure to the thirty individual stocks in the Dow Jones Industrial Average
index, the data suggest that it is important to allow for both time-varying diffusive volatility,
jumps, and leverage effects in order to satisfactorily describe the daily stock price dynamics.
At a broader level, the empirical results also illustrate how the realized variation measures and
high-frequency sampling schemes may be used in eliciting important distributional features and
asset pricing implications more generally.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages72
Publication statusPublished - 2007

    Research areas

  • 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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ID: 10570086