Estimation of Continuous-Time Models with an Application to Equity Volatility Dynamics
Cheung Kong Graduate School of Business
University of Maryland - Robert H. Smith School of Business
Journal of Financial Economics, Forthcoming
Robert H. Smith School Research Paper No. RHS 06-017
The treatment of this article renders closed-form density approximation feasible for univariate continuous-time models. Implementation methodology depends directly on the parametric-form of the drift and the diffusion of the primitive process and not on its transformation to a unit-variance process. Offering methodological convenience, the approximation method relies on numerically evaluating one-dimensional integrals and circumvents existing dependence on intractable multidimensional integrals. Density-based inferences can now be drawn for a broader set of models of equity volatility. Our empirical results provide insights on crucial outstanding issues related to the rank-ordering of continuous-time stochastic volatility models, the absence/presence of nonlinearities in the drift function of equity volatility, and the desirability of pursuing more flexible diffusion function specifications.
Number of Pages in PDF File: 29
Keywords: Continuous-time models, Maximum-likelihood estimation, Density approximation, Market volatility dynamics
JEL Classification: G10, G11, G12, G13, C15, C32, C52Accepted Paper Series
Date posted: January 27, 2006
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