EconPapers    
Economics at your fingertips  
 

Asset allocation when guarding against catastrophic losses: a comparison between the structure variable and joint probability methods

Brendan Bradley and Murad Taqqu

Quantitative Finance, 2004, vol. 4, issue 6, 619-636

Abstract: We apply a bivariate approach to the asset allocation problem for investors seeking to minimize the probability of large losses. It involves modelling the tails of joint distributions using techniques motivated by extreme value theory. We compare results with a corresponding univariate approach using simulated and financial data. Through an examination of a simulated and real financial data set we show that the estimated risks using the bivariate and univariate approaches are in close agreement for a wide range of losses and allocations. This is important since the bivariate approach is significantly more computationally expensive. We therefore suggest that the univariate approach be used for the typical level of loss that an investor may want to guard against. This univariate approach is effective even if there are more than two assets. The software written in support of this work is available on demand and we describe its use in the appendix.

Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/14697680400008635 (text/html)
Access to full text is restricted to subscribers.

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:taf:quantf:v:4:y:2004:i:6:p:619-636

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20

DOI: 10.1080/14697680400008635

Access Statistics for this article

Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral

More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:quantf:v:4:y:2004:i:6:p:619-636