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The evaluation of American options in a stochastic volatility model with jumps: An efficient finite element approach

机译:带有跳跃的随机波动率模型中的美式期权评估:一种有效的有限元方法

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We consider the problem of pricing American options in the framework of a well-known stochastic volatility model with jumps, the Bates model. According to this model the asset price is described by a jump-diffusion stochastic differential equation in which the jump term consists of a Levy process of compound Poisson type, while the volatility is modeled as a CIR-type process correlated with the asset price. Pricing American options under the Bates model requires us to solve a partial integro-differential equation with the final condition and boundary conditions prescribed on a free boundary. In this paper a numerical method for solving such a problem is proposed. In particular, first of all, using a Richardson extrapolation technique, the problem is reduced to a problem with fixed boundary. Then the problem obtained is solved using an ad hoc finite element method which efficiently combines an implicit/explicit time stepping, an operator splitting technique, and a non-uniform mesh of right-angled triangles. Numerical experiments are presented showing that the option pricing algorithm developed in this paper is extremely accurate and fast. In particular it is significantly more efficient than other numerical methods that have recently been proposed for pricing American options under the Bates model.
机译:我们在著名的带跳跃的随机波动率模型(贝茨模型)的框架内考虑对美式期权定价的问题。根据该模型,资产价格由跳跃扩散随机微分方程描述,其中跳跃项由复合泊松类型的征费过程组成,而波动率被建模为与资产价格相关的CIR类型过程。在贝茨模型下对美式期权定价需要我们求解一个偏微分方程,其最终条件和边界条件在自由边界上规定。本文提出了一种数值方法来解决这一问题。特别地,首先,使用Richardson外推技术,将问题简化为具有固定边界的问题。然后,使用特设有限元方法解决了所获得的问题,该方法有效地结合了隐式/显式时间步长,算子拆分技术和直角三角形的非均匀网格。数值实验表明,本文开发的期权定价算法非常准确,快速。特别是,它比最近提出的在贝茨模型下为美式期权定价的其他数值方法要有效得多。

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