Optimal Stopping Games for Markov Processes

2008 ◽  
Vol 47 (2) ◽  
pp. 684-702 ◽  
Author(s):  
Erik Ekström ◽  
Goran Peskir
2013 ◽  
Vol 2013 ◽  
pp. 1-17 ◽  
Author(s):  
Yuri Kifer

We start by briefly surveying a research on optimal stopping games since their introduction by Dynkin more than 40 years ago. Recent renewed interest to Dynkin’s games is due, in particular, to the study of Israeli (game) options introduced in 2000. We discuss the work on these options and related derivative securities for the last decade. Among various results on game options we consider error estimates for their discrete approximations, swing game options, game options in markets with transaction costs, and other questions.


4OR ◽  
2016 ◽  
Vol 15 (3) ◽  
pp. 277-302 ◽  
Author(s):  
Benoîte de Saporta ◽  
François Dufour ◽  
Christophe Nivot

1967 ◽  
Vol 7 (1) ◽  
pp. 37-44
Author(s):  
B. Grigelionis

The abstracts (in two languages) can be found in the pdf file of the article. Original author name(s) and title in Russian and Lithuanian: Б. Григелионис. Об эксцессивных функциях и оптимальных правилах остановки ступенчатых марковских процессов B. Grigelionis. Apie laiptuotų Markovo procesų ekscesyvines funkcijas ir optimalias sustabdymo taisykles


2020 ◽  
Vol 57 (2) ◽  
pp. 497-512
Author(s):  
Bertrand Cloez ◽  
Benoîte de Saporta ◽  
Maud Joubaud

AbstractThis paper investigates the random horizon optimal stopping problem for measure-valued piecewise deterministic Markov processes (PDMPs). This is motivated by population dynamics applications, when one wants to monitor some characteristics of the individuals in a small population. The population and its individual characteristics can be represented by a point measure. We first define a PDMP on a space of locally finite measures. Then we define a sequence of random horizon optimal stopping problems for such processes. We prove that the value function of the problems can be obtained by iterating some dynamic programming operator. Finally we prove via a simple counter-example that controlling the whole population is not equivalent to controlling a random lineage.


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