« Happy New Year! | Main | Create beautiful statistical graphics with ggplot2 »

January 05, 2009


Feed You can follow this conversation by subscribing to the comment feed for this post.

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.

The comments to this entry are closed.

Search Revolutions Blog

Got comments or suggestions for the blog editor?
Email David Smith.
Follow revodavid on Twitter Follow David on Twitter: @revodavid