文章基本信息

标题：Computing optimal recovery policies for financial markets
本地全文：下载
作者：Fred E. Benth ; Geir Dahl ; Carlo Mannino 等
期刊名称：Department of Computer and System Sciences Antonio Ruberti Technical Reports
印刷版ISSN：2035-5750
出版年度：2010
卷号：2
期号：20
语种：English
出版社：Department of Computer and System Sciences Antonio Ruberti. Sapienza, Università di Roma
摘要：The current financial crisis motivates the study of correlated defaults in financial systems. In this paper we focus on such a model which is based on Markov random fields. This is a probabilistic model where uncertainty in default probabilities incorporates expert's opinions on the default risk (based on various credit ratings). We consider a bilevel optimization model for finding an optimal recovery policy: which companies should be supported given a fixed budget. This is closely linked to the problem of finding a maximum likelihood estimator of the defaulting set of agents, and we show how to compute this solution efficiently using combinatorial methods. We also prove properties of such optimal solutions. A practical procedure for estimation of model parameters is also given. Computational examples are presented and experiments indicate that our methods can find optimal recovery policies for up to about 100 companies. The overall approach is evaluated on a real-world problem concerning the major banks in Scandinavia and public loans. To our knowledge this is a first attempt to apply combinatorial optimization techniques to this important, and expanding, area of default risk analysis.
关键词：Financial models;discrete optimization;bilevel programming;Markov random field