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January 05, 2009

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I can't understand why one wouldn't compute an annual or biannual VaR - this would reveal all the problems of a chance event even at 99% that might not matter for fast technical and speculative transactions.

But agreed, a bad worker blames his tool.

I guess it depends on exactly the model used as the basis of the VaR calculation, but wouldn't an longer-term VaR essentially just scale the profit/loss distribution? If you're using VaR to truly represent a dollar value then an annual VaR might make sense (even if presenting VaR as a dollar value to non-quants hides all of the unknown long-tail risks) but if you're tracking VaR over time and looking for extremes (akin to a six-sigma process-control chart) then the time-scale shouldn't matter as much, right?

A longer-term VaR would definitely scale the variance more than linearly in most models I can imagine to be valid. The longer the period, the greater chance of a meteorite hitting NYSE, and the greater chance of any other type of disruption.

Even when you use VaR, you can still look at the expectation of the top 1% of highest risk, and make sure it doesn't cause you a default.

The real problem is in the reductionism of badly overfit models, not in the tails. Heavy tails merely cause fear, they don't really tell you what to do.

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