The Risks of Financial Modeling: VaR and the Economic Meltdown

Opening Statement By Chairman Brad Miller

Economics has not been known in the past for mathematical precision. Harry Truman said he wanted a one-handed economist because he was frustrated with economists who equivocated by saying “on the one hand…on the other hand.” George Bernard Shaw said that if all the world’s economists were laid end to end, they still wouldn’t reach a conclusion. And apparently no one knows who first observed that economics was the only field in which two people can share a Nobel Prize for reaching exactly the opposite conclusion.

But in the last 15 or 20 years, math and physics PhDs from academia and the laboratory have entered the financial sector.  Quantitative analysts, or "quants," directed their mathematical and statistical skills to financial forecasts at a time when global financial markets were becoming more interdependent than ever before. 

The quants conceived such financial instruments as collaterized debt obligations, or “CDOs,” and credit default swaps, or “CDSs,” that would never have existed without them and their computers.  They developed strategies for trading those instruments even in the absence of any underlying security or any real market.  They constructed risk models that convinced their less scientifically and technologically adept bosses that their instruments and strategies were infallibly safe.  And their bosses spread faith in the quants’ models to regulators, who agreed to apply them to establish capital reserve requirements that were supposed to guarantee the soundness of financial institutions against adverse events.  It almost seemed like economic models had brought the precision of the laws of physics to financial risk management.  Engineering schools even offered courses in “financial engineering.”

The supposedly immutable “laws” underlying the quants’ models didn’t work, and the complex models turn out to have hidden risks rather than protected against them, all at a terrible cost.  Those risks—concealed and maybe even encouraged by the models—have led to hundreds of billions of dollars in losses to investors and the taxpayers, to a global recession imposing trillions of dollars in losses to the world economy and immeasurable monetary and human costs.  People around the world are losing their jobs, their homes, their dignity and their hope.

Taxpayers here and around the world are shouldering the burden arising from financial firms' miscalculation of risk, poor judgment, excessive bonuses and profligate behavior.  It is for this reason that the Subcommittee has chosen to direct its attention today to that intersection of quantitative analysis, economics, and regulation.  The “Value at Risk” model, or “VaR” stands squarely at the center of this intersection as the most prominent risk model used by major financial institutions.  The VaR is designed to provide an answer to the question, “What is the potential loss that could be faced within a limited, specified time to the value of an asset?”

The highest probability is that tomorrow’s value will be the same as today’s; the next highest probability is of a very small movement in value up or down, and so on.  The more radical the movement in value, the lower the probability of its occurrence. In other words, the danger to the financial firm or the community comes at the extreme margins of the VaR distribution curve, in the “tails” of the distribution. As a map to day-to-day behavior, the VaR is probably pretty accurate for normal times, just as teams favored by odds makers usually win. But just as long shots sometimes come home, asset bubbles or other “non-normal” market conditions also occur, and the VaR is unlikely to capture the risks and dangers.  The VaR also cannot tell you when you have moved into “non-normal” market conditions.

While the VaR was originally designed for financial institutions' to use in-house to evaluate short-term risk in their trading books, it was given a key role in determining capital requirements for large banks under a major multilateral agreement, the Basel II Accord, published in 2004.  That same year, the U.S. Securities and Exchange Commission, at the instigation of the five largest investment banks, adopted a capital reserve regime applying Basel II standards to the Nation’s largest investment banks, a decision that opened the door to their over-leveraging and liquidity problems.  Three of the institutions that asked the SEC for this change in rules—Bear Stearns, Merrill Lynch, Lehman Brothers—no longer exist.  At the time, those financial institutions assured regulators that the VaR would reflect the level of risk they were taking on, and that a low VaR justified lower reserve requirements.  The result was exactly what the investment banks asked for; lower capital reserve requirements that allowed them to invest in even more risky financial instruments all justified with risk models that assured regulators that there was nothing to worry about. 

In light of the VaR’s prominent role in the financial crisis, this Subcommittee is examining that role and the role of related risk-measurement methods.  From a policy perspective, the most important immediate question is how regulators use VaR numbers and other such models devised by regulated institutions and whether they are an appropriate guide to setting capital reserve requirements.   But, beyond that, we must also ask whether the scientific and technical capabilities that helped lead us into the current crisis should be applied to prevent future catastrophic events.  Can mathematics, statistics, and economics produce longer-range models – models that could give us early warning of when our complex financial system is heading for trouble?  Or are such models inevitably going to be abused to hide risk-taking and encourage excessive gambling by firms whose failures can throw the whole world into a recession?  If models cannot be a useful guide for regulation, should we just abandon this approach and simply increase reserves, reducing profits and perhaps some useful economic conduct in the short run, but protecting taxpayers and the world economy in the long run?

These are big questions, but the stakes for taxpayers and investors and the world economy justify the effort to get at some answers. 

I now recognize Mr. Broun for his opening statement.

Witnesses

Panel 1

1 - Dr. Richard Bookstaber
Financial Author
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2 - Dr. Nassim Nicholas Taleb
Distinguished Professor of Risk Engineering Polytechnic Institute of New York University Polytechnic Institute of New York University
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Panel 2

1 - Dr. Gregg Berman
Head of Risk Business RiskMetrics Group RiskMetrics Group
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2 - Dr. David Colander
Christian A. Johnson Distinguished Professor of Economics Middlebury College Middlebury College
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3 - Mr. James G. Rickards
Senior Managing Director Omnis, Inc. Omnis, Inc.
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4 - Mr. Christopher Whalen
Managing Director Institutional Risk Analytics Institutional Risk Analytics
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