The Quantification of Systemic Risk and Stability: New Methods and Measures
Chapter in NBER book Quantifying Systemic Risk (2013), Joseph G. Haubrich and Andrew W. Lo, editors (p. 223 - 262)
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.
This paper was revised on August 29, 2014
Document Object Identifier (DOI): 10.7208/chicago/9780226921969.003.0008This chapter first appeared as NBER working paper w17022, The Quantification of Systemic Risk and Stability: New Methods and Measures, Romney B. Duffey
Commentary on this chapter: Comment, Joseph G. Haubrich
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