Lookback option pricing under the double Heston model using a deep learning algorithm

被引：0

作者：

Mahsa Motameni

Farshid Mehrdoust

Ali Reza Najafi

机构：

[1] Department of Applied Mathematics,

[2] Faculty of Mathematical Sciences University of Guilan,undefined

来源：

Computational and Applied Mathematics | 2022年 / 41卷

关键词：

Double Heston PDE; Lookback option pricing; Deep Galerkin method; Monte Carlo simulation; G13; G22; 91B70;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

To price floating strike lookback options, we obtain a partial differential equation (PDE) according to the double Heston model. To solve the PDE, we employ a deep learning algorithm called the deep Galerkin method (DGM), which is well-suited for high-dimensional PDEs. Finally, we compare the obtained results from mentioned method with the option price under the Monte Carlo simulation method.

引用

共 50 条

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