Journal of Computational and Applied Mathematics2022,Vol.40414.DOI:10.1016/j.cam.2021.113901

Convergence analysis for continuous-time Markov chain approximation of stochastic local volatility models: Option pricing and Greeks

Ma, Jingtang Yang, Wensheng Cui, Zhenyu
Journal of Computational and Applied Mathematics2022,Vol.40414.DOI:10.1016/j.cam.2021.113901

Convergence analysis for continuous-time Markov chain approximation of stochastic local volatility models: Option pricing and Greeks

Ma, Jingtang 1Yang, Wensheng 1Cui, Zhenyu2
扫码查看

作者信息

  • 1. Southwestern Univ Finance & Econ
  • 2. Stevens Inst Technol
  • 折叠

Abstract

This paper establishes the precise second order convergence rates of the continuous time Markov chain (CTMC) approximation method for pricing options under the general framework of stochastic local volatility (SLV) models. The stochastic local volatility models studied in this paper include Heston model, 4/2 model, alpha-Hypergeometric model, stochastic alpha beta rho (SABR) model, Heston-SABR model and quadratic SLV model. Using the stochastic flow theorem, the closed-form CTMC approximation formula for the Greeks are obtained and the second order convergence rates are proved. Numerical examples confirm the theoretical findings. (C) 2021 Elsevier B.V. All rights reserved.

Key words

Continuous-time Markov chains/Stochastic local volatility models/Option pricing/Greeks/Convergence rates/FRAMEWORK/SABR

引用本文复制引用

出版年

2022
Journal of Computational and Applied Mathematics

Journal of Computational and Applied Mathematics

EISCI
ISSN:0377-0427
被引量3
参考文献量28
段落导航相关论文