Center for Interdisziplinary Research

ZiF Research Group

Robust Finance: Strategic Power, Knightian Uncertainty, and the Foundations of Economic Policy Advice

Convenors: Frank Riedel (Bielefeld, GER), Chris Shannon (Berkeley, USA)

March–July, 2015

The theory of financial markets is one of the most successful theories social scientists, applied mathematicians and physicists have ever developed. Its success, however, has also contributed to its immense misuse and failure in practice. The ongoing crisis has been accompanied by huge losses incurred by investment banks that had to be covered by societies as a whole.

Economic policy advisors failed to predict, let alone understand, the causes and consequences for the real side of the economy. The usual macroeconomic models used to estimate the course of the economy and to advise policy makers did not include financial markets and thus were unable to anticipate the effects of the fallout from the storm that was building up in financial markets.

On the scientific side, some consensus has emerged regarding certain unfortunate developments that contributed to the crisis. One primary factor was the increasing splintering of finance, financial mathematics and economics into disjoint subjects. In recent years, financial mathematics has developed into more and more secluded regions of financial engineering without universal sound economic foundations. Microeconomic theory, although essential for understanding the social and welfare effects of financial decisions, has not been integrated into financial mathematics.

Our research group aims to overcome this unfortunate separation into what one might call "financial engineering without judgment" and "economic policy without mathematical sophistication" by creating a theory of finance that achieves the heroic aim of using the mathematical tools of stochastic calculus in combination with the sound economic judgement provided by game theory, mechanism design, and decision theory. .

We also take the failure of macroeconomic policy models as an incentive and a new chance to study the potential of economics as a social science: can we predict the course of complex economic systems, or are there natural boundaries for a social science that prevent any serious prediction? If this is so, what are the consequences for the scientific consultancy of economic policy? .

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