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arXiv 0704.0335math.PRq-fin.CPq-fin.PR
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平稳马尔可夫过程分布的逼近及其在期权定价中的应用

Approximation of the distribution of a stationary Markov process with application to option pricing

Gilles Pagès, Fabien Panloup

摘要:

本文在R_+上的R^d值càdlàg函数空间D(R_+,R^d)上建立了一个经验测度序列,以逼近平稳R^d值Markov和Feller过程(X_t)的律.我们得到了该序列收敛性的一些一般结果。然后,我们将它们应用到布朗扩散和解决方案,以Lévy驱动的一些Lyapunov型稳定性假设下的。作为本文工作的数值应用,我们证明了这一过程给出了随机波动率模型中期权定价的一种有效方法。

英文摘要:

We build a sequence of empirical measures on the space D(R_+,R^d) of R^d-valued càdlàg functions on R_+ in order to approximate the law of a stationary R^d-valued Markov and Feller process (X_t). We obtain some general results of convergence of this sequence. Then, we apply them to Brownian diffusions and solutions to Lévy driven SDE's under some Lyapunov-type stability assumptions. As a numerical application of this work, we show that this procedure gives an efficient way of option pricing in stochastic volatility models.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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