A 'Horse Race' Among Competing Option Pricing Models Using S&P 500 Index Options

Minqiang Li, Neil D. Pearson
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引用次数: 20

Abstract

The last three decades have witnessed a whole array of option pricing models. We compare the predictive performances of a selection of models by carrying out a horse race on S&P 500 index options along the lines of Jackwerth and Rubinstein (2001). The models we consider include: Black-Scholes, trader rules, Heston's stochastic volatility model, Merton's jump diffusion models with and without stochastic volatility, and more recent Levy type models. Trader rules still dominate mathematically more sophisticated models, and the performance of the trader rules is further improved by incorporating the stable index skew pattern documented in Li and Pearson (2005). Furthermore, after incorporating the stable index skew pattern, the Black-Scholes model beats all mathematically more sophisticated models in almost all cases. Mathematically more sophisticated models vary in their overall performance and their relative accuracy in forecasting future volatility levels and future volatility skew shapes.
使用标准普尔500指数期权的竞争性期权定价模型之间的“赛马”
过去三十年出现了一系列期权定价模型。我们沿着Jackwerth和Rubinstein(2001)的思路,通过对标准普尔500指数期权进行赛马来比较选定模型的预测性能。我们考虑的模型包括:Black-Scholes,交易员规则,Heston随机波动模型,Merton有和没有随机波动的跳跃扩散模型,以及最近的Levy型模型。交易者规则仍然主导着数学上更复杂的模型,并且通过纳入Li和Pearson(2005)中记录的稳定指数倾斜模式,交易者规则的性能进一步得到改善。此外,在纳入稳定的指数倾斜模式后,布莱克-斯科尔斯模型在几乎所有情况下都胜过所有数学上更复杂的模型。数学上更复杂的模型在预测未来波动水平和未来波动曲线形状方面的总体表现和相对准确性各不相同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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