Solvency games

N. Berger, N. Kapur, L. J. Schulman, V. V. Vazirani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

We study the decision theory of a maximally risk-averse investor - one whose objective, in the face of stochastic uncertainties, is to minimize the probability of ever going broke. With a view to developing the mathematical basics of such a theory, we start with a very simple model and obtain the following results: a characterization of best play by investors; an explanation of why poor and rich players may have different best strategies; an explanation of why expectation-maximization is not necessarily the best strategy even for rich players. For computation of optimal play, we show how to apply the Value Iteration method, and prove a bound on its convergence rate.

Original languageEnglish
Title of host publicationFSTTCS 2008 - IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science
Pages61-72
Number of pages12
StatePublished - 2008
Externally publishedYes
Event28th International Conference on the Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2008 - Bangalore, India
Duration: 9 Dec 200811 Dec 2008

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume2
ISSN (Print)1868-8969

Conference

Conference28th International Conference on the Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2008
Country/TerritoryIndia
CityBangalore
Period9/12/0811/12/08

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