文章基本信息

标题：Recursive Estimation for Continuous Time Stochastic Volatility Models Using the Milstein Approximation
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作者：Theodoro Koulis ; Alexander Paseka ; Aerambamoorthy Thavaneswaran 等
期刊名称：Journal of Mathematical Finance
印刷版ISSN：2162-2434
电子版ISSN：2162-2442
出版年度：2013
卷号：3
期号：3
页码：357-365
DOI：10.4236/jmf.2013.33036
出版社：Scientific Research Publishing
摘要：Optimal as well as recursive parameter estimation for semimartingales had been studied in [1,2]. Recently, there has been a growing interest in modelling volatility of the observed process by nonlinear stochastic processes [3]. In this paper, we study the recursive estimates for various classes of discretely sampled continuous time stochastic volatility models using the Milstein approximation. We provide closed form expressions for the recursive estimates for recently proposed stochastic volatility models. We also give an example of computation of the term structure of zero rates in an incomplete information environment. In this case, learning about an unobserved state variable is done jointly with the valuation procedure.
关键词：Recursive Estimation; Diffusion Processes; Interest Rate Models; Milstein Approximation