We have to change our risk models, and not just defer to the big banks’ inaccurate models which got us into this mess.
I have been fighting risk models both as a Wall Street trader and as a professor and my worst nightmares were the results of regulators. It was they who promoted the reliance on ratings by credit agencies. The “value-at-risk” models regulators promoted made us take more risks…
We replaced the heuristics of the elders with arrogant (and incompetent) beliefs, breaking, in the name of science, the chain of knowledge. Old, conservative bankers and traders have been replaced by keen young mathematical analysts, yet anyone who listened to a grandmother who survived the Depression would have been warned against debt and been better prepared than Ben Bernanke and Alan Greenspan, respectively chairman and former chairman of America’s Federal Reserve.
[And see this]
- Economist Robert Kuttner
- And many others
Today, Simon Johnson summarized the whole modeling issue very well:
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 …), or periodic stress tests that estimate how bank asset portfolios will perform in a real crisis.
But there is a more interesting question to ask as well: why did VaR become so popular? It’s important to remember that competition among models is shaped by the human beings who create and use them, and those human beings have their own incentives.
David Colander made this point about economic models: the sociology of the economics profession gave preference to elegant mathematical models that could describe the world using the smallest number of parameters. “Common sense does not advance one very far within the economics profession,” he says.
A similar point can be made about VaR models. 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.
Not only that, but imagine the situation of the chief risk manager of a bank in, say, 2004. As Andrew Lo has argued, if he attempted to reduce his bank’s exposure to structured securities such as CDOs, he would be out of a job; VaR gave him a handy tool to rationalize a situation that defied common sense but that made his bosses only too happy. And at the top levels, CEOs and directors who probably did not understand the shortcomings of VaR were biased in its favor because it told them a story they wanted to hear.
In other words, models succeed because they meet the needs of real human beings, and VaR was just what they needed during the boom. And we should assume that a profit-seeking financial sector will continue to invent models that further the objectives of the individuals and institutions that use them. The implication is that regulators need to resist the group think of large financial institutions. If everyone involved is using the same roadmap of risks, we will all drive off the cliff again together.
We ignore Johnson’s warnings at our own peril.