I've always preferred Conditional Value at Risk (CVaR) to regular VaR. While VaR is the 5% (say) value of loss, CVaR is the average of the loss of the bottom 5

I've always preferred Conditional Value at Risk (CVaR) to regular VaR. While VaR is the 5% (say) value of loss, CVaR is the average of the loss of the bottom 5%. That way it captures the size of the tail risk. The other really big advantage is that you can optimize over CVaR. You can formulate it in a linear program (LP), so you can maximize expected return subject to a limit on CVaR. [1] You can have several CVaR constraints at 1% and 5% say. In contrast, VaR isn't convex, and is difficult to optimize over. [1] http://www.ise.ufl.edu/uryasev/publications/ http://www.ise.ufl.edu/uryasev/publications/ Edit: there is an interesting presentation comparing CVaR and VaR by Stan Uryasev, the main academic that has worked on CVaR formulations here: http://www.ise.ufl.edu/uryasev/files/2011/11/VaR_vs_CVaR_CARISMA_conference_2010.pdf http://www.ise.ufl.edu/uryasev/files/2011/11/VaR_vs_CVaR_CAR...