Predicting the Last Zero before an exponential time of a Spectrally Negative L\'evy Process

TL;DR

This paper addresses the problem of optimally predicting the last zero of a spectrally negative Lévy process before an independent exponential time, extending previous infinite horizon results to a finite horizon setting with new characterizations.

Contribution

It introduces a finite horizon optimal prediction framework for spectrally negative Lévy processes, characterizing the optimal stopping rule via a non-linear integral equation system.

Findings

Optimal stopping time is based on crossing a time-dependent curve.

The curve is killed when the mean of the exponential time is reached.

Numerical examples include Brownian motion and compound Poisson processes.

Abstract

Given a spectrally negative L\'evy process, we predict, in a $L_1$ sense, the last passage time of the process below zero before an independent exponential time. This optimal prediction problem generalises Baurdoux and Pedraza (2020) where the infinite horizon problem is solved. Using a similar argument as that in Urusov (2005), we show that this optimal prediction problem is equivalent to solving an optimal prediction problem in a finite horizon setting. Surprisingly (unlike the infinite horizon problem) an optimal stopping time is based on a curve that is killed at the moment the mean of the exponential time is reached. That is, an optimal stopping time is the first time the process crosses above a non-negative, continuous and non-increasing curve depending on time. This curve and the value function are characterised as a solution of a system of non-linear integral equations which can be understood as a generalisation of the free boundary equations (see e.g. Peskir and Shiryaev (2006) Chapter IV.14.1) in the presence of jumps. As an example, we calculate numerically such curve in the Brownian motion case and a compound Poisson process with exponential sized jumps perturbed by a Brownian motion.