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An iterative method for pricing American options under jump-diffusion models

机译:跳扩散模型下美式期权定价的迭代方法

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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.
机译:我们提出一种在跳扩散模型下为美式期权定价的迭代方法。对部分积分-微分方程进行有限差分离散化,并将美国期权定价问题表述为线性互补问题(LCP)。跳跃扩散模型包含一个积分项,该积分项会导致生成的系统密集。我们提出了一个迭代来有效地解决LCP并证明其收敛性。使用Kou和Merton的跳跃扩散模型的数值示例表明,所产生的迭代快速收敛。

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