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Browsing by Subject "Optimal stopping (Mathematical statistics)"

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    Poisson disorder problem with control on costly observations
    (2012) Kadiyala, Bharadwaj
    A Poisson process Xt changes its rate at an unknown and unobservable time θ from λ0 to λ1. Detecting the change time as quickly as possible in an optimal way is described in literature as the Poisson disorder problem. We provide a more realistic generalization of the disorder problem for Poisson process by introducing fixed and continuous costs for being able to observe the arrival process. As a result, in addition to finding the optimal alarm time, we also characterize an optimal way of observing the arrival process. We illustrate the structure of the solution spaces with the help of some numerical examples.
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    Pricing perpetual American-type strangle option for merton's jump diffusion process
    (2014) Onat, Ayşegül
    A stock price Xt evolves according to jump diffusion process with certain parameters. An asset manager who holds a strangle option on that stock, wants to maximize his/her expected payoff over the infinite time horizon. We derive an optimal exercise rule for asset manager when the underlying stock is dividend paying and non-dividend paying. We conclude that optimal stopping strategy changes according to stock’s dividend rate. We also illustrate the solution on numerical examples.
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    Wiener disorder problem with observation control
    (2012) Altınok, Duygu
    Suppose that a Wiener process gains a known drift rate at some unobservable disorder time with some zero-modified exponential distribution. The process is observed only at some intervals that we control. Beginning and end points and the lengths of the observation intervals are controlled optimally. We pay cost for observing the process and for switching on the observation. We show that Bayes optimal alarm times minimizing the expected total cost of false alarms, detection delay cost and observation costs exist. Optimal alarms may occur during the observations or between the observation times when the odds-ratio process hits a set. We derive the sufficient conditions for the existence of the optimal stopping and switching rules and describe the numerical methods to calculate optimal value function.

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