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.<p>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.<p>In contrast, VaR isn't convex, and is difficult to optimize over.<p>[1] <a href="http://www.ise.ufl.edu/uryasev/publications/" rel="nofollow">http://www.ise.ufl.edu/uryasev/publications/</a><p>Edit: there is an interesting presentation comparing CVaR and VaR by Stan Uryasev, the main academic that has worked on CVaR formulations here:<p><a href="http://www.ise.ufl.edu/uryasev/files/2011/11/VaR_vs_CVaR_CARISMA_conference_2010.pdf" rel="nofollow">http://www.ise.ufl.edu/uryasev/files/2011/11/VaR_vs_CVaR_CAR...</a>
The article does mention the downsides but doesn't really cover how devastating they can be. VaR was the common calculation persuading the banks that everything was nice and safe in 2007 and 2008.<p>From the article<p><i>VaR does not discuss the magnitude of the expected loss beyond the value of VaR, i.e. it will tell us that we are likely to see a loss exceeding a value, but not how much it exceeds it.<p>It does not take into account extreme events, but only typical market conditions.<p>Since it uses historical data (it is rearward-looking) it will not take into account future market regime shifts that can change volatilities and correlations of assets.</i>