Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/67837 
Year of Publication: 
2008
Series/Report no.: 
Queen's Economics Department Working Paper No. 1173
Publisher: 
Queen's University, Department of Economics, Kingston (Ontario)
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.
Subjects: 
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
JEL: 
C1
G1
Document Type: 
Working Paper

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