英文文献：Multivariate Option Pricing with Time Varying Volatility and Correlations-具有时变波动率和相关性的多元期权定价
英文文献作者：Jeroen V.K. Rombouts,Lars Stentoft
英文文献摘要：
In recent years multivariate models for asset returns have received much attention, in particular this is the case for models with time varying volatility. In this paper we consider models of this class and examine their potential when it comes to option pricing. Specifically, we derive the risk neutral dynamics for a general class of multivariate heteroskedastic models, and we provide a feasible way to price options in this framework. Our framework can be used irrespective of the assumed underlying distribution and dynamics, and it nests several important special cases. We provide an application to options on the minimum of two indices. Our results show that not only is correlation important for these options but so is allowing this correlation to be dynamic. Moreover, we show that for the general model exposure to correlation risk carries an important premium, and when this is neglected option prices are estimated with errors. Finally, we show that when neglecting the non-Gaussian features of the data, option prices are also estimated with large errors.

近年来，多变量资产回报模型受到了广泛的关注，特别是具有时变波动率的模型。在本文中，我们考虑了这类模型，并考察了它们在期权定价方面的潜力。具体地说，我们推导了一般的多变量异方差模型的风险中性动力学，并在此框架下提供了一种可行的期权定价方法。我们的框架可以不用考虑假设的底层分布和动态，它嵌套了几个重要的特殊情况。我们提供了一个应用程序的最小两个索引的选项。我们的结果表明，相关性不仅对这些选项很重要，而且允许这种相关性是动态的也很重要。此外，我们表明，对于一般的模型，暴露于相关风险带有一个重要的溢价，当这被忽略时，期权价格的估计是有误差的。最后，我们证明了当忽略数据的非高斯特性时，期权价格的估计也有很大的误差。