Risk-neutral Modeling with Affine and Nonaffine Models
Risk-neutral Modeling with Affine and Nonaffine Models
复制标题
使用仿射和非仿射模型进行风险中性建模
DOI：
10.1093/jjfinec/nbt009
复制
发表时间：
2013
影响因子：
2.5
通讯作者：
G. Durham
中科院分区：
文献类型：
--
作者：
G. Durham
期权价格提供了大量关于市场对未来资产价格动态预期的信息。但是，隐含的动态是在风险中性度量下，而不是在标的资产价格本身演变的物理度量下。本文演示了使用基础资产和期权的数据对物理模型和风险中性模型进行联合分析的新技术。虽然这一领域的大部分先前工作都集中在仿射和仿射跳跃模型上，因为它们的分析易处理性，但本文中使用的技术可以直接应用于广泛的潜在兴趣模型。该技术的基础上评估各种积分的兴趣，使用蒙特卡洛和模拟波动率路径。在一个使用标准普尔500指数数据的应用程序中，我们发现，对数波动率模型的表现显着优于仿射模型，但仍然存在一些错误的证据。作者版权所有，2013年。牛津大学出版社出版。All rights reserved.如需查询，请发送电子邮件至：oup.com，牛津大学出版社。
Option prices provide a great deal of information regarding the market's expectations of future asset price dynamics. But, the implied dynamics are under the risk-neutral measure rather than the physical measure under which the price of the underlying asset itself evolves. This article demonstrates new techniques for joint analysis of the physical and risk-neutral models using data from both the underlying asset and options. While much of the prior work in this area has focused on affine and affine-jump models because of their analytical tractability, the techniques used in this article are straightforward to apply to a broad class of models of potential interest. The techniques are based on evaluating various integrals of interest using Monte Carlo sums over simulated volatility paths. In an application using S&P 500 index data, we find that log volatility models perform dramatically better than affine models, but that some evidence of misspecification remains. Copyright The Author, 2013. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com, Oxford University Press.