Parametric pricing of higher order moments in S&P500 options
Parametric pricing of higher order moments in S&P500 options
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DOI：
10.1002/jae.762
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发表时间：
2005-03-01
影响因子：
2.1
通讯作者：
Martin, VL
中科院分区：
文献类型：
--
作者：
Lim, GC;Martin, GM;Martin, VL
基于广义Student t-分布，建立了一个通用的参数框架，用于标准普尔500指数期权的定价。股票收益的高阶矩以及随时间变化的波动性被定价。一个重要的计算优势，建议的框架，基于蒙特卡洛的定价方法是，期权可以使用一维正交积分定价。实证应用是基于标准普尔500期权交易的选择日在1995年4月，总样本超过100，000观察。一系列的性能标准被用来评估所提出的模型，以及一些替代模型。实证结果表明，定价高阶矩和随时间变化的波动率产生的期权定价的改善，以及纠正与Black-Scboles模型的波动率偏斜。版权所有（c）2004年约翰威利父子有限公司。
A general parametric framework based on the generalized Student t-distribution is developed for pricing S&P500 options. Higher order moments in stock returns as well as time-varying volatility are priced. An important computational advantage of the proposed framework over Monte Carlo-based pricing methods is that options can be priced using one-dimensional quadrature integration. The empirical application is based on S&P500 options traded on select days in April 1995, a total sample of over 100,000 observations. A range of performance criteria are used to evaluate the proposed model, as well as a number of alternative models. The empirical results show that pricing higher order moments and time-varying volatility yields improvements in the pricing of options, as well as correcting the volatility skew associated with the Black-Scboles model. Copyright (c) 2004 John Wiley & Sons, Ltd.