Finite horizon decision timing with partially observable Poisson processesLudkovski, 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 This is the latest version of this item. Full text not available from this repository. Official URL: http://dx.doi.org/10.1080/15326349.2012.672143 AbstractWe 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.
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