The Quantification of Systemic Risk and Stability: New Methods and Measures

Romney B. Duffey

Chapter in NBER book Quantifying Systemic Risk (2013), Joseph G. Haubrich and Andrew W. Lo, editors (p. 223 - 262)
Conference held November 6, 2009
Published in January 2013 by University of Chicago Press
© 2013 by the National Bureau of Economic Research

This chapter analyzes world economic data in order to predict the next crisis probability based on the presence and influence of human risk taking and decision making in financial markets. It summarizes recent ideas on risk prediction for multiple technological systems using existing data, and explicitly includes the key impact of human involvement using the learning hypothesis. It is argued that risk is caused by uncertainty, and the measure of uncertainty is probability. The risk of an outcome (accident, event, error, or failure) is never zero, and the possibility of an outcome always exists, with a chance given by the future (posterior) probability. The key is to include the human involvement, and to create and use the correct and relevant measures for experience, learning, complexity, and risk exposure.

Acknowledgments

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Document Object Identifier (DOI): 10.7208/chicago/9780226921969.003.0008

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