Finite horizon decision timing with partially observable Poisson processes

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Ludkovski, Michael and Sezer, Semih Onur (2012) Finite horizon decision timing with partially observable Poisson processes. Stochastic Models, 28 (2). pp. 207-247. ISSN 1532-6349

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Official URL: http://dx.doi.org/10.1080/15326349.2012.672143


We study decision timing problems on finite horizon with Poissonian information arrivals. In our model, a decision maker wishes to optimally time her action in order to maximize her expected reward. The reward depends on an unobservable Markovian environment, and information about the environment is collected through a (compound) Poisson observation process. Examples of such systems arise in investment timing, reliability theory, Bayesian regime detection and technology adoption models. We solve the problem by studying an optimal stopping problem for a piecewise-deterministic process, which gives the posterior likelihoods of the unobservable environment. Our method lends itself to simple numerical implementation and we present several illustrative numerical examples.

Item Type:Article
Uncontrolled Keywords:Bayesian sequential analysis; Decision making; Markov modulated Poisson processes; Optimal stopping
Subjects:Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
ID Code:19067
Deposited By:Semih Onur Sezer
Deposited On:28 May 2012 14:52
Last Modified:31 Jul 2019 10:59

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