Speed and duration of drawdown under general Markov models

Lingfei Li, Pingping Zeng and Gongqiu Zhang

Quantitative Finance, 2024, vol. 24, issue 3-4, 367-386

Abstract: We propose an efficient computational method based on continuous-time Markov chain (CTMC) approximation to compute the distributions of the speed and duration of drawdown for general one-dimensional (1D) time-homogeneous Markov processes. We derive linear systems for the Laplace transforms of drawdown quantities and show how to solve them efficiently by recursion. In addition, we prove the convergence of our method and obtain a sharp estimate of the convergence rate under some assumptions. As applications, we consider pricing two financial options that provide protection against drawdown risk. Finally, we demonstrate the accuracy and efficiency of our method through extensive numerical experiments.

Date: 2024
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DOI: 10.1080/14697688.2024.2336154

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