Abstract

For two independent L\'{e}vy processes $\xi$ and $\eta$ and an exponentially distributed random variable $\tau$ with parameter $q>0$ that is independent of $\xi$ and $\eta$, the killed exponential functional is given by $V_{q,\xi,\eta} := \int_0^\tau \mathrm{e}^{-\xi_{s-}} \, \mathrm{d} \eta_s$. With the killed exponential functional arising as the stationary distribution of a Markov process, we calculate the infinitesimal generator of the process and use it to derive different distributional equations describing the law of $V_{q,\xi,\eta}$, as well as functional equations for its Lebesgue density in the absolutely continuous case. Various special cases and examples are considered, yielding more explicit information on the law of the killed exponential functional and illustrating the applications of the equations obtained. Interpreting the case $q=0$ as $\tau=\infty$ leads to the classical exponential functional $\int_0^\infty \mathrm{e}^{-\xi_{s-}} \, \mathrm{d} \eta_s$, allowing to extend many previous results to include killing.

Highlights

  • For two independent real-valued Lévy processes ξ and η, the generalised Ornstein– Uhlenbeck process (Xt)t≥0 driven by ξ and η is defined by

  • The generalised Ornstein–Uhlenbeck process can equivalently be defined as the unique solution of the stochastic differential equation dXt = Xt− dUt + dηt, t ≥ 0

  • In a recent paper [7], we have characterised the support of Vq,ξ,η and established continuity properties of the law of Vq,ξ,η for general Lévy processes ξ and η

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Summary

Introduction

For two independent real-valued Lévy processes ξ and η, the generalised Ornstein– Uhlenbeck process (Xt)t≥0 driven by ξ and η is defined by. In a recent paper [7], we have characterised the support of Vq,ξ,η and established continuity properties of the law of Vq,ξ,η for general Lévy processes ξ and η With this approach, various sufficient conditions for absolute continuity were obtained, yielding new results for the exponential functional without killing. In [3], different distributional equations were derived through methods such as Laplace inversion to study both the law and the density of the exponential functional in the case where q = 0 and η is a subordinator. We collect several more examples to derive explicit results for the law of the killed exponential functional, showing that the previously derived equations can be solved explicitly in special cases

Preliminaries
Killed exponential functionals as invariant distributions of Markov processes
Distributional equations derived by Fourier and Laplace methods
Distributional equations derived by Schwartz theory of distributions
Proofs for Section 5
Applications and examples

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