On the Wiener disorder problem

TL;DR

This paper addresses a Bayesian change detection problem where the change is triggered by external shocks observed as a Poisson process, and proposes optimal detection rules minimizing detection delay and false alarms.

Contribution

It introduces a novel formulation of the Wiener disorder problem incorporating observable shocks and derives optimal detection rules under this new framework.

Findings

Derived an optimal detection rule minimizing a linear Bayes risk.

Provided a solution for the variational formulation with false alarm constraints.

Extended the classical Wiener disorder problem to include external shock observations.

Abstract

In the Wiener disorder problem, the drift of a Wiener process changes suddenly at some unknown and unobservable disorder time. The objective is to detect this change as quickly as possible after it happens. Earlier work on the Bayesian formulation of this problem brings optimal (or asymptotically optimal) detection rules assuming that the prior distribution of the change time is given at time zero, and additional information is received by observing the Wiener process only. Here, we consider a different information structure where possible causes of this disorder are observed. More precisely, we assume that we also observe an arrival/counting process representing external shocks. The disorder happens because of these shocks, and the change time coincides with one of the arrival times. Such a formulation arises, for example, from detecting a change in financial data caused by major financial events, or detecting damages in structures caused by earthquakes. In this paper, we formulate the problem in a Bayesian framework assuming that those observable shocks form a Poisson process. We present an optimal detection rule that minimizes a linear Bayes risk, which includes the expected detection delay and the probability of early false alarms. We also give the solution of the ``variational formulation'' where the objective is to minimize the detection delay over all stopping rules for which the false alarm probability does not exceed a given constant.