An Iterative Method for Pricing American Options Under Jump-Diffusion Models
An Iterative Method for Pricing American Options Under Jump-Diffusion Models
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DOI：
10.2139/ssrn.1748943
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发表时间：
2011-01
期刊：
影响因子：
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通讯作者：
Santtu Salmi;J. Toivanen
中科院分区：
文献类型：
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作者：
Santtu Salmi;J. Toivanen
本文提出了一种跳扩散模型下美式期权定价的迭代方法。对偏积分微分方程进行有限差分离散，将美式期权定价问题转化为线性互补问题。跳跃-扩散模型包括一个积分项，这使得所得到的系统是稠密的。我们提出了一种迭代法来有效地求解LCP，并证明了其收敛性。用Kou@？s和Merton@？的跳跃扩散模型表明，由此产生的迭代收敛迅速。
We propose an iterative method for pricing American options under jump-diffusion models. A finite difference discretization is performed on the partial integro-differential equation, and the American option pricing problem is formulated as a linear complementarity problem (LCP). Jump-diffusion models include an integral term, which causes the resulting system to be dense. We propose an iteration to solve the LCPs efficiently and prove its convergence. Numerical examples with Kou@?s and Merton@?s jump-diffusion models show that the resulting iteration converges rapidly.