Ali’s blog

Mostly quant stuff with occasional digressions

Another opinion on the misleading nature of financial engineering

Posted by alifinmath on March 14, 2008

A piece by Edmund Phelps in today’s WSJ:

Our Uncertain Economy

In recent times, most economists have pretended that the economy is essentially predictable and understandable. Economic decision- and policy-making in the private and public sectors, the thinking goes, can be reduced to a science. Today we are seeing consequences of this conceit in the financial industries and central banking. “Financial engineering” and “rule-based” monetary policy, by considering uncertain knowledge to be certain knowledge, are taking us in a hazardous direction.

Predictability was not always the economic fashion. In the 1920s, Frank Knight at the University of Chicago viewed the capitalist economy as shot through with “unmeasurable” risks, which he called “uncertainty.” John Maynard Keynes wrote of the consequences of Knightian uncertainty for rational action.

In the 1970s, though, a new school of neo-neoclassical economists proposed that the market economy, though noisy, was basically predictable. All the risks in the economy, it was claimed, are driven by purely random shocks — like coin throws — subject to known probabilities, and not by innovations whose uncertain effects cannot be predicted.

This model took hold in American economics and soon practitioners sought to apply it. Quantitative finance theory became a tool relied on by most banks and hedge funds. Policy rules based on this model were adopted at the Federal Reserve and other central banks.

The neo-neoclassicals claimed big benefits from these changes. They boasted that their statistical approach to risk made the financial sector much more effective in matching lenders with borrowers, with vast savings in labor and increases in profits. They asserted a decline in “volatility” in the U.S. economy and credited it to the monetary policy rules at the Fed.

Current experience is putting these claims to the test.

Subprime lending and the securitization of debt was an innovation that, it was believed, offered the prospect of increasing homeownership. But “risk management” was out of its depth here: It had no past data from which to estimate needed valuations on the novel assets, it did not allow for possible macroeconomic dynamics, and it took inadequate account of the system effects of unknown numbers of entrants into the new business all at nearly the same.

In passing, I want to mention that in the calculation of risks, the idea of “probability” becomes a complex and difficult one, particularly when 1) data is limited, and 2) we can’t generate data (e.g., by tossing a coin). In foundations and interpretations, the science of probability remains a controversial one. Axiomatisation by Kolmogorov hasn’t changed the nature of the controversies. But I’m tired of typing and I’ll have to discuss this in some subsequent post, in particular mentioning the books, Plight of the Fortune Tellers, by Rebonato, and Creating Modern Probability, by von Plato.




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