Pretense of Knowledge in Financial Economics

A colleague called me to task for my criticism of constructivist macroeconomists at the Federal Reserve and macroeconomists in general for their persistent support of discretionary stabilization policy despite evidence indicating such policies are pro-cyclical. What Hayek called a “pretense of knowledge” and a reliance on artificial mathematical precision is also apparent among financial economists. Taleb, author of the Black Swan, argued that the pretense of understanding was even worse among financial economists. Economists are more often content to predict the direction of change while much of the financial economics, including the theory of asset and derivative pricing, presumes to predict magnitudes. Despite a preponderance of evidence indicating stock returns are non-normal much of finance theory assumes normality in returns with constant conditional variance. Accordingly, under the assumptions of a normal distribution stock market declines such as the ones in 1987 and 1997 are only supposed to happen every 500 years.

The over reliance on artificial mathematical precision may also be more apparent in financial economics. Over the last decade many Wall Street investment banking firms relied on PhDs in statistical physics to quantify risk in securitized lending such as the sub-prime secondary market despite their having little institutional understanding of how these markets operate. Clearly, many of the models perpetuated by Wall Street were wrong but you can afford to be wrong if you can rely on the Bernanke put.