Estimation of continuous-time models with an application to equity volatility dynamics
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 di usion of the primitive process and not its transformation to a unit-variance process. Offering methodological convenience, the approximation method re- lies 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 out- standing issues related to the ranking-orderings of continuous-time stochastic volatility models, the absence/presence of non-linearities in the drift function, and the desirability of pursuing more flexible diffusion function specifications.
Continuous-time models Maximum-likelihood estimation Density approximation Equity volatility Volatility dynamics
Gurdip Bakshi Nengjiu Ju Hui Ou-Yang
Department of Finance, Smith School of Business, University of Maryland, College Park, MD 20742 Fuqua School of Business, Duke University, Durham, NC 27708
国际会议
西安
英文
1-28
2006-07-17（万方平台首次上网日期，不代表论文的发表时间）