Exponential Lévy Models with Stochastic Volatility and Stochastic Jump-Intensity

Matthew J. Lorig
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引用次数: 4

Abstract

We consider the problem of valuing a European option written on an asset whose dynamics are described by an exponential L\'evy-type model. In our framework, both the volatility and jump-intensity are allowed to vary stochastically in time through common driving factors -- one fast-varying and one slow-varying. Using Fourier analysis we derive an explicit formula for the approximate price of any European-style derivative whose payoff has a generalized Fourier transform; in particular, this includes European calls and puts. From a theoretical perspective, our results extend the class of multiscale stochastic volatility models of \citet*{fpss} to models of the exponential L\'evy type. From a financial perspective, the inclusion of jumps and stochastic volatility allow us to capture the term-structure of implied volatility. To illustrate the flexibility of our modeling framework we extend five exponential L\'evy processes to include stochastic volatility and jump-intensity. For each of the extended models, using a single fast-varying factor of volatility and jump-intensity, we perform a calibration to the S&P500 implied volatility surface. Our results show decisively that the extended framework provides a significantly better fit to implied volatility than both the traditional exponential L\'evy models and the fast mean-reverting stochastic volatility models of \citet{fpss}.
具有随机波动率和随机跳跃强度的指数lsamvy模型
我们考虑对一种资产的欧式期权进行估值的问题,该资产的动态由指数型l型模型描述。在我们的框架中,波动性和跳跃强度都允许通过共同的驱动因素随时间随机变化——一个是快速变化的,一个是缓慢变化的。利用傅里叶分析,我们导出了任何欧式导数的近似价格的显式公式,其收益具有广义傅里叶变换;这尤其包括欧洲的看涨期权和看跌期权。从理论的角度来看,我们的研究结果将\citet*{fpss}的多尺度随机波动模型扩展到指数型lsamvy模型。从金融角度来看,包含跳跃和随机波动使我们能够捕捉隐含波动率的期限结构。为了说明我们的建模框架的灵活性,我们扩展了五个指数lsamvy过程,以包括随机波动和跳跃强度。对于每个扩展模型,使用单个快速变化的波动率和跳跃强度因子,我们对标准普尔500隐含波动率曲面进行校准。我们的研究结果明确地表明,扩展框架提供了一个显着更好的拟合隐含波动率比传统的指数lsamvy模型和快速均值回归随机波动率模型\citet{fpss}。
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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