Computing optimal recovery policies for financial markets

Fred E. Benth (), Geir Dahl () and Carlo Mannino ()
Additional contact information
Fred E. Benth: Department of Mathematics, CMA, University of Oslo, Norway.
Geir Dahl: Department of Mathematics and Department of Informatics, CMA, University of Oslo, Norway.
Carlo Mannino: Dipartimento di Informatica e Sistemistica "Antonio Ruberti" Sapienza, Universita' di Roma

No 2010-20, DIS Technical Reports from Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza"

Abstract: 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.

Keywords: Financial models; discrete optimization; bilevel programming; Markov random field (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.dis.uniroma1.it/~bibdis/RePEc/aeg/wpaper/2010-20.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aeg:wpaper:2010-20

Access Statistics for this paper

More papers in DIS Technical Reports from Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza" Contact information at EDIRC.
Bibliographic data for series maintained by Antonietta Angelica Zucconi ( this e-mail address is bad, please contact ).