Inference methods for discretely observed continuous-time stochastic volatility models: A commented overview

被引：7
|
作者：
Jimenez J.C. [1 ]
Biscay R.J. [1 ]
Ozaki T. [2 ]
机构：
[1] Instituto de Cibernética, Matemética y Física, Departamento de Matemática Interdisiplinaria, Vedado, La Habana 4, Calle 15, e/ C y D
[2] Department of Prediction and Control, Institute of Statistical Mathematics, Minato-ku, Tokyo 106-8569
来源：
Asia-Pacific Financial Markets | 2005年 / 12卷 / 2期
关键词：
Diffusion processes; Inference methods; Stochastic volatility models;
D O I：
10.1007/s10690-006-9015-8
中图分类号：
学科分类号：
摘要：
In this paper an overview of inference methods for continuous-time stochastic volatility models observed at discrete times is presented. It includes estimation methods for both parametric and nonparametric models that are completely or partially observed in a variety of situations where the data might be nonlinear functions of the components of the model and/or contaminated with observation noise. In each case, the main reported methods are presented, making emphasis on underlying ideas, theoretical properties of the estimators (bias, consistency, efficient, etc.), and the viability of their implementation to solve actual problems in finance. © Springer 2006.
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页码：109 / 141
页数：32
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