Dimitrios Bisias
Massachusetts Institute of Technology (MIT)

Mark D. Flood
Government of the United States of America - Office of Financial Research

Andrew W. Lo
Massachusetts Institute of Technology (MIT) - Sloan School of Management; Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL); National Bureau of Economic Research (NBER)

Stavros Valavanis
Massachusetts Institute of Technology (MIT)

Abstract

We provide a survey of 31 quantitative measures of systemic risk in the economics and finance literature, chosen to span key themes and issues in systemic risk measurement and management. We motivate these measures from the supervisory, research, and data perspectives in the main text, and present concise definitions of each risk measure - including required inputs, expected outputs, and data requirements - in an extensive appendix. To encourage experimentation and innovation among as broad an audience as possible, we have developed open-source Matlab code for most of the analytics surveyed.