Robust portfolio choice with CVaR and VaR under distribution and mean return ambiguity

A. Paç and Mustafa Pınar ()

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2014, vol. 22, issue 3, 875-891

Abstract: We consider the problem of optimal portfolio choice using the Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR) measures for a market consisting of n risky assets and a riskless asset and where short positions are allowed. When the distribution of returns of risky assets is unknown but the mean return vector and variance/covariance matrix of the risky assets are fixed, we derive the distributionally robust portfolio rules. Then, we address uncertainty (ambiguity) in the mean return vector in addition to distribution ambiguity, and derive the optimal portfolio rules when the uncertainty in the return vector is modeled via an ellipsoidal uncertainty set. In the presence of a riskless asset, the robust CVaR and VaR measures, coupled with a minimum mean return constraint, yield simple, mean-variance efficient optimal portfolio rules. In a market without the riskless asset, we obtain a closed-form portfolio rule that generalizes earlier results, without a minimum mean return restriction. Copyright Sociedad de Estadística e Investigación Operativa 2014

Keywords: Robust portfolio choice; Ellipsoidal uncertainty; Conditional Value-at-Risk; Value-at-Risk; Distributional robustness; 91G10; 91B30; 90C90 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11750-013-0303-y (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:spr:topjnl:v:22:y:2014:i:3:p:875-891

Ordering information: This journal article can be ordered from
http://link.springer.de/orders.htm

DOI: 10.1007/s11750-013-0303-y

Access Statistics for this article

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research is currently edited by Juan José Salazar González and Gustavo Bergantiños

More articles in TOP: An Official Journal of the Spanish Society of Statistics and Operations Research from Springer, Sociedad de Estadística e Investigación Operativa
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().