The Federal Reserve’s “stress tests” were intended to make the financial system safer. Using risk modeling, the tests subject banks to various stress scenarios in the economy to see how well they would perform and determine the capital “buffer” banks need to remain solvent and safely weather poor economic conditions. But with the Fed relying on risk modeling to determine regulatory capital requirements for banks, what happens if the models are wrong? Risk models can suffer from major weaknesses, ranging from poor assumptions to inadequate data, and can be particularly blind to tail-end risks—for example, the subprime crisis. Rather than making us safer, could the reliance on risk modeling by regulators actually be paving the way for the next systemwide financial crisis?
Math Gone Mad: Systemic Dangers of the Federal Reserve’s Stress Tests
Featuring George Selgin, Director, Center for Monetary and Financial Alternatives, Cato Institute; and Kevin Dowd, Cato Adjunct Scholar, Professor of Finance and Economics at Durham University, UK; moderated by Peter Russo, Director of Congressional Affairs, Cato Institute.