Least-squares Monte-Carlo methods for optimal stopping investment under CEV models

Jingtang Ma, Zhengyang Lu, Wenyuan Li and Jie Xing

Quantitative Finance, 2020, vol. 20, issue 7, 1199-1211

Abstract: The optimal stopping investment is a kind of mixed expected utility maximization problems with optimal stopping time. The aim of this paper is to develop the least-squares Monte-Carlo methods to solve the optimal stopping investment under the constant elasticity of variance (CEV) model. Such a problem has no closed-form solutions for the value functions, optimal strategies and optimal exercise boundaries due to the early exercised feature. The dual optimal stopping problem is first derived and then the strong duality between the dual and prime problems is established. The least-squares Monte-Carlo methods based on the dual control theory are developed and numerical simulations are provided. Both the power and non-HARA utilities are studied.

Date: 2020
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DOI: 10.1080/14697688.2020.1736325

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