Economic and financial models have come in for a lot of criticism in the context of the global financial crisis, much of it deserved. One of the primary targets is models that financial institutions widely used to (mis)estimate risk, such as Value-at-Risk (VaR) models for measuring risk exposures (which we’ve discussed elsewhere) or the Gaussian copula function for quantifying the risk of a pool of assets.

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As Richard Bookstaber put it, VaR depends on three assumptions, all of which are generally false : not all assets, particularly illiquid ones, are included in the VaR calculation ; estimates are based on past data that is unrepresentative of the future ; and because financial returns exhibit “fat tails” (extreme outcomes are more likely than you would expect), VaR estimates tell you very little about how bad things can get that last 1% of the time.

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Given that everyone is agreeing sophisticated risk models are worthless in crises, it seems particularly remarkable that regulators allowed some banks to use their in-house models in determining their own capital requirements - since one of the purposes of capital requirements is precisely to provide a cushion that protects banks (and their creditors, and taxpayers) in the event of a crisis. The obvious solution is that regulators should rely on cruder constraints, such as an absolute limit on leverage that banks cannot arbitrage around (one of the recommendations of Treasury’s recent white paper on capital requirements, which we discussed here), or periodic stress tests that estimate how bank asset portfolios will perform in a real crisis.

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Sure, maybe all the financial professionals who design and work with VaR know about its shortcomings, both mathematical and practical. But nevertheless, using VaR brought concrete benefits to specific actors in the banking world. If common sense would lead a risk manager to crack down on a trader taking large, risky bets, then the trader is better off if the risk manager uses VaR instead.

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