Pricing American Parisian Options under General Time-Inhomogeneous Markov Models

Fuente: arXiv
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Autores principales: Liu, Yuhao, Yang, Nian, Zhang, Gongqiu
Formato: Preprint
Publicado: 2025
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author Liu, Yuhao
Yang, Nian
Zhang, Gongqiu
author_facet Liu, Yuhao
Yang, Nian
Zhang, Gongqiu
contents This paper develops general approaches for pricing various types of American-style Parisian options (down-in/-out, perpetual/finite-maturity) with general payoff functions based on continuous-time Markov chain (CTMC) approximation under general 1D time-inhomogeneous Markov models. For the down-in types, by conditioning on the Parisian stopping time, we reduce the pricing problem to that of a series of vanilla American options with different maturities and their prices integrated with the distribution function of the Parisian stopping time yield the American Parisian down-in option price. This facilitates an efficient application of CTMC approximation to obtain the approximate option price by calculating the required quantities. For the perpetual down-in cases under time-homogeneous models, significant computational cost can be reduced. The down-out cases are more complicated, for which we use the state augmentation approach to record the excursion duration and then the approximate option price is obtained by solving a series of variational inequalities recursively with the Lemke's pivoting method. We show the convergence of CTMC approximation for all the types of American Parisian options under general time-inhomogeneous Markov models, and the accuracy and efficiency of our algorithms are confirmed with extensive numerical experiments.
format Preprint
id arxiv_https___arxiv_org_abs_2503_11053
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Pricing American Parisian Options under General Time-Inhomogeneous Markov Models
Liu, Yuhao
Yang, Nian
Zhang, Gongqiu
Computational Finance
This paper develops general approaches for pricing various types of American-style Parisian options (down-in/-out, perpetual/finite-maturity) with general payoff functions based on continuous-time Markov chain (CTMC) approximation under general 1D time-inhomogeneous Markov models. For the down-in types, by conditioning on the Parisian stopping time, we reduce the pricing problem to that of a series of vanilla American options with different maturities and their prices integrated with the distribution function of the Parisian stopping time yield the American Parisian down-in option price. This facilitates an efficient application of CTMC approximation to obtain the approximate option price by calculating the required quantities. For the perpetual down-in cases under time-homogeneous models, significant computational cost can be reduced. The down-out cases are more complicated, for which we use the state augmentation approach to record the excursion duration and then the approximate option price is obtained by solving a series of variational inequalities recursively with the Lemke's pivoting method. We show the convergence of CTMC approximation for all the types of American Parisian options under general time-inhomogeneous Markov models, and the accuracy and efficiency of our algorithms are confirmed with extensive numerical experiments.
title Pricing American Parisian Options under General Time-Inhomogeneous Markov Models
topic Computational Finance
url https://arxiv.org/abs/2503.11053