Value at Risk (VaR) is often criticised. This is especially the case from those who don't use it, no surprise there and I label such propaganda as statistical xenophobia by the masses.
In this post we look at the problems with VaR and what can be done to improve this measure of potential downside.
In the world of operational risk, there are a lot of analysts who believe that they can dimension the impacts from uncertainty by counting the number of events they experience over a period of time and then multiply that count by the average loss amount for the total event horizon they observe.
This approach for quantifying the impacts from uncertainty is full of error and it should be avoided. In fact, let's be clear, it is so fundamentally wrong as a measure of exposure that it isn't even a goo
For many risk managers, the recent financial meltdown has left them questioning the veryessence of risk modeling, used by many since the 1990s to measure their firm’sfinancial risk. Investment firms have traditionally relied on fantasticallycomplex mathematical models for measuring the associated risk in their variousportfolios, primarily to reassure investors that all is well. However, theworldwide events of the past 18 months have, arguably, left the reputation of riskmodeling in tatters. Here
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