Bounds for joint portfolios of dependent risks

Giovanni Puccetti and Rüschendorf Ludger
Additional contact information
Rüschendorf Ludger: University of Freiburg, Mathematische Stochastik, Freiburg, Deutschland

Statistics & Risk Modeling, 2012, vol. 29, issue 2, 107-132

Abstract: In this paper, we survey, extend and improve several bounds for the distribution function and the tail probabilities of portfolios, where the dependence structure within the portfolio is completely unknown or only partially known. We present various methods for obtaining bounds based on rearrangements, duality theory, conditional moments and reduction techniques. In particular, we consider the case where only the simple marginal distributions are known, the general overlapping marginals case where certain joint distributions are known and the case of additional restrictions on the dependence structure, as, for example, the restriction to positive dependence. Some of the bounds pose a considerable numerical challenge. We discuss the quality of the bounds and numerical aspects in some examples.

Keywords: Fréchet bounds; overlapping marginals; dependent risks; mass transportation theory; joint portfolio (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://doi.org/10.1524/strm.2012.1117 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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:bpj:strimo:v:29:y:2012:i:2:p:107-132:n:4

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/strm/html

DOI: 10.1524/strm.2012.1117

Access Statistics for this article

Statistics & Risk Modeling is currently edited by Robert Stelzer

More articles in Statistics & Risk Modeling from De Gruyter
Bibliographic data for series maintained by Peter Golla ().