基于随机波动率假设的权证定价理论评述

The Review of Warrant Pricing Theory based on the Stochastic Volatility

随机波动率(SV)模型在衍生品定价和风险管理中的应用开始发挥越来越重要的作用,但是,由于很难得到似然函数的闭型表达式,SV模型的参数估计问题严重限制了它在金融实践领域的普及应用。不过,近年来,学者们提出了许多旨在解决SV模型参数估计问题的有效且可行的新方法,大大推进了SV模型的应用化进程。本文将在权证定价分析的框架内,重点评述SV模型的参数估计方法,并从理论和实证的角度对它们的优点和不足进行简要评介和比较。

Stochastic Volatility （SV） models are increasingly important in practical derivatives pricing applications, yet the empirical application of SV models in financial has been limited due to the difficulties involved in the evaluation of the likelihood function. However, recently there has been fundamental progress in this area due to the proposal of several new estimation methods that try to overcome this problem, being at the same time, empirically feasible. In this paper, we analysis the main estimators of the parameters and the volatility of univariate SV models under the framework of warrant pricing. We describe the main advantages and limitations of each of the methods both from the theoretical and empirical point of view.