05 November 2008
The Real Purpose of Risk Models
As Warren Buffett said, “Beware of geeks bearing formulas.” There is a discipline in the physical sciences that limits the credulity given to theories about how the world is organized. Those hypotheses are always subject to challenge by investigating peers, even when a consensus accepts them as workable models. It’s that humility of science that seems to have escaped the financial engineers who created the risk reduction technology on which the markets have learned to rely.
Quasi-scientific models developed by “quants” are really only tools of persuasion, the use of which is motivated by the rewards that come to successful salesmen. They don’t exist primarily for the purpose of better understanding reality. Credit-default swaps were not really “created to insure blue-chip bond investors against the risk of default,” as Steve Lohr wrote in the November 5, 2008 New York Times. Rather, they were put together in order to convince investors to buy those securities and thereby earn greater fees for the brokers who sold them. Counterparty risk and the housing bubble could be ignored because they did not fit into the model. The risk model’s mathematical elegance and persuasiveness would be compromised by their inclusion.
One difference between an engineer and a scientist is the distance to their time horizons. Long after the financial engineer has collected his reward for the sale of a fancy credit instrument using his model, the economist/social scientist will still be trying to anticipate the long-term consequences of human behavior according to its formulas.
As Warren Buffett said, “Beware of geeks bearing formulas.” There is a discipline in the physical sciences that limits the credulity given to theories about how the world is organized. Those hypotheses are always subject to challenge by investigating peers, even when a consensus accepts them as workable models. It’s that humility of science that seems to have escaped the financial engineers who created the risk reduction technology on which the markets have learned to rely.
Quasi-scientific models developed by “quants” are really only tools of persuasion, the use of which is motivated by the rewards that come to successful salesmen. They don’t exist primarily for the purpose of better understanding reality. Credit-default swaps were not really “created to insure blue-chip bond investors against the risk of default,” as Steve Lohr wrote in the November 5, 2008 New York Times. Rather, they were put together in order to convince investors to buy those securities and thereby earn greater fees for the brokers who sold them. Counterparty risk and the housing bubble could be ignored because they did not fit into the model. The risk model’s mathematical elegance and persuasiveness would be compromised by their inclusion.
One difference between an engineer and a scientist is the distance to their time horizons. Long after the financial engineer has collected his reward for the sale of a fancy credit instrument using his model, the economist/social scientist will still be trying to anticipate the long-term consequences of human behavior according to its formulas.
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