2009-08: Fragility of CVar in portfolio optimization


We evaluate conditional value-at-risk (CVaR) as a risk measure in data-driven portfolio optimization. We show that portfolios obtained by solving mean-CVaR and global minimum CVaR problems are unreliable due to estimation errors of CVaR and/or the mean, which are aggravated by optimization. This problem is exacerbated when the tail of the return distribution is made heavier. We conclude that CVaR, a coherent risk measure, is fragile in portfolio optimization due to estimation errors.

A.E.B. Lim
J.G. Shanthikumar
G.Y. Vahn
Publication date: 
September 21, 2009
Publication type: 
2009 Working Papers