Discrete time stochastic multi-player competitive games with affine payoffs

Ivan Guo , Marek Rutkowski

Abstract

A novel class of multi-player competitive stochastic games in discrete-time with an affine specification of the redistribution of payoffs at exercise is examined. The affine games cover as a very special case the classic two-person stochastic stopping games introduced by Dynkin (1969). We first extend to the case of a single-period deterministic affine game the results from Guo and Rutkowski (2012, 2014) where the socalled redistribution games were studied. We identify conditions under which optimal equilibria and value for a multi-player affine game exist. We also examine stochastic multi-period affine games and we show that, under mild assumptions, they can be solved by the method of backward induction.
Author Ivan Guo - [The University of Sydney]
Ivan Guo,,
-
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, Marek Rutkowski (FMIS / DSPFM) - [ School of Mathematics and Statistics, University of Sydney, Sydney, NSW 2006, Australia]
Marek Rutkowski,,
- Department of Stochastic Processes and Financial Mathematics
- School of Mathematics and Statistics, University of Sydney, Sydney, Australia
Journal seriesStochastic Processes and Their Applications, ISSN 0304-4149
Issue year2016
Vol126
No1
Pages1-32
Publication size in sheets1.55
Keywords in EnglishMulti-player game; Redistribution game; Affine game; Dynkin stopping game; Stochastic game; Nash equilibrium; Optimal equilibrium
ASJC Classification2604 Applied Mathematics; 2611 Modelling and Simulation; 2613 Statistics and Probability
Abstract in PolishZbadano nową klasę gier stochastycznych z dyskretnym czasem.
DOIDOI:10.1016/j.spa.2015.07.013
URL http://www.sciencedirect.com/science/article/pii/S030441491500191X
Languageen angielski
Score (nominal)30
Score sourcejournalList
ScoreMinisterial score = 25.0, 02-02-2020, ArticleFromJournal
Ministerial score (2013-2016) = 30.0, 02-02-2020, ArticleFromJournal
Publication indicators Scopus Citations = 1; WoS Citations = 1; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 1.178; WoS Impact Factor: 2016 = 1.024 (2) - 2016=1.271 (5)
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