Friday, July 31, 2009

The Truth About Value at Risk...

It's another phony mathematical number based on an equations that do not necessarily reflect reality. (Though the government is using it as a regulatory tool to measure risk.)

Pablo Triana explains:

Is Goldman Sachs (GS) the biggest risk-taker on Wall Street? Besides
headlining the record profits the bank just posted (months after getting taxpayer support), the media have reported extensively on the firm's all-time-high risk exposure—measured, of course, by that widely embraced financial metric: VaR, or Value at Risk.

VaR, used for decades on the Street, supposedly reveals the maximum amount an investment house could lose (to a statistical degree of confidence) on its trading portfolios in a specified period. And the peak in Goldman's average daily VaR—$245 million in the second quarter, almost double that of a year earlier—prompted accusations that the well-connected firm had dangerously ratcheted up risk-taking in the midst of a crisis.

There's no reason to think this is true. Whatever your opinion of Goldman's fortunes and market forays in this recession, the fact is that a VaR-based analysis of any firm's riskiness is useless. VaR lies. Big time. As a predictor of risk, it's an impostor. It should be consigned to the dustbin. Firms should stop reporting it. Analysts and regulators should stop using it.

Some, including regulators who base capital reserve requirements on this metric, may call VaR a "measure of market risk" and "predictor of future losses." But it is neither of those things. Its forecast of how much an investor can lose from a trading position is entirely calculated from historical data. It's a mathematical tool that simply reflects what happened to a portfolio of assets during a certain past period. (The person supplying the data to the model can essentially select any dates.)

The VaR metric has little to do with how a portfolio will fare in the future—and that includes tomorrow. When it comes to the market, the past is definitely not prologue. A current calm may not yield future placidity. Turbulence is not inevitably followed by further chaos.

VaR models also tend to plug in weird assumptions that typically deliver unrealistically low risk numbers: the assumption, for instance, that markets follow a normal probability distribution, thus ruling out extreme events. Or that diversification in the portfolio will offset risk exposure (because a group of assets happened to move in different directions previously).

Read Triana's full article here.

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