scholarly journals Partially observed optimal stopping problem for discrete-time Markov processes

4OR ◽  
2016 ◽  
Vol 15 (3) ◽  
pp. 277-302 ◽  
Author(s):  
Benoîte de Saporta ◽  
François Dufour ◽  
Christophe Nivot
Keyword(s):  
Markov Processes ◽  
Discrete Time ◽  
Optimal Stopping ◽  
Optimal Stopping Problem ◽  
Partially Observed

scholarly journals On general optimal stopping problems using penalty method

2012 ◽  
Vol 45 (2) ◽  
Author(s):  
Ł. Stettner
Keyword(s):  
Stochastic Processes ◽  
Markov Processes ◽  
Discrete Time ◽  
Optimal Stopping ◽  
Penalty Method ◽  
Value Function ◽  
Polish Space ◽  
Finite Horizon ◽  
Optimal Stopping Problem ◽  
Optimal Stopping Problems

AbstractIn the paper we use penalty method to approximate a number of general stopping problems over finite horizon. We consider optimal stopping of discrete time or right continuous stochastic processes, and show that suitable version of Snell’s envelope can by approximated by solutions to penalty equations. Then we study optimal stopping problem for Markov processes on a general Polish space, and again show that the optimal stopping value function can be approximated by a solution to a Markov version of the penalty equation.

Approximations of the optimal stopping problem in partial observation

1986 ◽  
Vol 23 (2) ◽  
pp. 341-354 ◽  
Author(s):  
G. Mazziotto
Keyword(s):  
Optimal Stopping ◽  
Measure Space ◽  
Stopping Time ◽  
Optimal Stopping Problem ◽  
Snell Envelope ◽  
Infinite Dimensional ◽  
Markov State ◽  
State Process ◽  
Partially Observed ◽  
True State

The resolution of the optimal stopping problem for a partially observed Markov state process reduces to the computation of a function — the Snell envelope — defined on a measure space which is in general infinite-dimensional. To avoid these computational difficulties, we propose in this paper to approximate the optimal stopping time as the limit of times associated to similar problems for a sequence of processes converging towards the true state. We show on two examples that these approximating states can be chosen such that the Snell envelopes can be explicitly computed.

scholarly journals Value Function and Optimal Rule on the Optimal Stopping Problem for Continuous-Time Markov Processes

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Lu Ye
Keyword(s):  
Explicit Formula ◽  
Markov Processes ◽  
Optimal Stopping ◽  
Continuous Time ◽  
Value Function ◽  
Broad Class ◽  
Stopping Time ◽  
Optimal Stopping Problem ◽  
Optimal Rule ◽  
Reward Functions

This paper considers the optimal stopping problem for continuous-time Markov processes. We describe the methodology and solve the optimal stopping problem for a broad class of reward functions. Moreover, we illustrate the outcomes by some typical Markov processes including diffusion and Lévy processes with jumps. For each of the processes, the explicit formula for value function and optimal stopping time is derived. Furthermore, we relate the derived optimal rules to some other optimal problems.

Optimal Stopping Problem with Controlled Recall

1998 ◽  
Vol 12 (1) ◽  
pp. 91-108 ◽  
Author(s):  
Tsuyoshi Saito
Keyword(s):  
Discrete Time ◽  
Optimal Stopping ◽  
Search Process ◽  
Optimal Stopping Problem ◽  
Search Cost ◽  
Net Profit ◽  
Time Optimal

This paper deals with the following discrete-time optimal stopping problem. For fixed search costs, a random offer, w ~ F(w), will be found for each time. This offer is either accepted, rejected, or “reserved” for recall later. The reserving cost for any offer depends on its value, regardless of how long the offer is reserved. The objective is to maximize the expected discounted net profit, provided that an offer must be accepted. The major finding is that no previously reserved offer should be accepted prior to the deadline of the search process.

Sign in / Sign up

Export Citation Format

Share Document