A new research paper from Contango Capital Advisors examines the shortcomings of academic thought in developing models that can be used by financial institutions to institute effective enterprisewide risk management systems and policies.
In "Economists' Hubris - The Case of Risk Management," Shahin Shojai, global head of strategic research at Capco, and George Feiger, chief executive of Contango, conclude that most academic models fail when put under the microscope, and that the development of effective models is a long way off. But no matter which models are used, the authors say, the current IT and operational infrastructures of banking institutions do not allow management to obtain a holistic view of risk...
Michael S. Fischer writes at Investment Advisor.
Introduction to Economists' Hubris - The Case of Risk Management
In this, our third article in the economists’ hubris series, we look at the shortcomings of academic thinking on financial risk management, a very topical subject. In the previous two articles, we examined and rejected the notion that contributions from the academic community in the fields of mergers and acquisitions [Shojai (2009)] and asset pricing [Shojai and Feiger (2009)] were of practical use. Economists have drifted into realms of sterile, quasi-mathematical and a priori theorizing instead of coming to grips with the realities of their subject. In this sense, they have stood conventional scientific methodology, which develops theories to explain facts and tests them by their ability to predict, on its head.
Not surprisingly this behavior has carried over to the field of risk management, with an added twist. Like the joke about the man who looks for his dropped keys under the street light because that is where the light is rather than where he dropped the keys, financial economists have focused on things that they can ‘quantify’ rather than on things that actually matter. The latter include the structure of the financial system, the behavior of its participants, and its actual ability to capture and aggregate information.
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