Efficient computation of first passage times in Kou's jump-diffusion model

TL;DR

This paper introduces a simplified expression for the Laplace transform of first passage times in Kou's jump-diffusion model, enabling faster and more accurate numerical inversion using Fourier-series methods.

Contribution

It provides a more straightforward Laplace transform expression and demonstrates the extension to complex plane, improving computational efficiency and accuracy.

Findings

Significantly faster computation times.

Enhanced accuracy in inverting Laplace transforms.

Effective application of Fourier-series methods.

Abstract

S. G. Kou and H. Wang [First Passage times of a Jump Diffusion Process \textit{Ann. Appl. Probab.} {\bf 35} (2003) 504--531] give expressions of both the (real) Laplace transform of the distribution of first passage time and the (real) Laplace transform of the joint distribution of the first passage time and the running maxima of a jump-diffusion model called Kou model. %However, to invert the last Laplace transform it is needed Kuo and Wang invert the first Laplace transform by using Gaver-Stehfest algorithm, and the inversion of second one involves a large computing time with an algebra computer system. In the present paper, we give a much simpler expression of the Laplace transform of the joint distribution, and we also show, using Complex Analysis techniques, that both Laplace transform can be extended to the complex plane. Hence, we can use variants of the Fourier-series methods to invert that Laplace transfoms, which are very efficent. The improvement in the computing times and accuracy is remarkable.