KUBS 생활
Academic Activities
Management Science
Vol. 57, No. 8, August 2011, pp. 1387–1405
Kay Giesecke
Department of Management Science and Engineering, Stanford University, Stanford, California 94305, giesecke@stanford.edu
Baeho Kim
Korea University Business School, Anam-dong, Sungbuk-gu, Seoul 136-701, Korea, baehokim@korea.ac.kr
http://pubsonline.informs.org/doi/pdf/10.1287/mnsc.1110.1375
Abstract
This paper develops dynamic measures of the systemic risk of the financial sector as a whole. It defines
systemic risk as the conditional probability of failure of a sufficiently large fraction of the total population
of financial institutions. This definition recognizes that the cause of systemic distress is the correlated failure of
institutions to meet obligations to creditors, customers, and trading partners. The likelihood estimators of the
failure probability are based on a dynamic hazard model of correlated failure timing that captures the influence
on failure timing of time-varying macroeconomic and sector-specific risk factors, and of spillover effects. Tests
indicate that our measures provide accurate out-of-sample forecasts of the term structure of systemic risk in the
United States for the period from 1998 to 2009.
Keywords
banks; financial system; correlated failure; systemic risk
Vol. 57, No. 8, August 2011, pp. 1387–1405
Kay Giesecke
Department of Management Science and Engineering, Stanford University, Stanford, California 94305, giesecke@stanford.edu
Baeho Kim
Korea University Business School, Anam-dong, Sungbuk-gu, Seoul 136-701, Korea, baehokim@korea.ac.kr
http://pubsonline.informs.org/doi/pdf/10.1287/mnsc.1110.1375
Abstract
This paper develops dynamic measures of the systemic risk of the financial sector as a whole. It defines
systemic risk as the conditional probability of failure of a sufficiently large fraction of the total population
of financial institutions. This definition recognizes that the cause of systemic distress is the correlated failure of
institutions to meet obligations to creditors, customers, and trading partners. The likelihood estimators of the
failure probability are based on a dynamic hazard model of correlated failure timing that captures the influence
on failure timing of time-varying macroeconomic and sector-specific risk factors, and of spillover effects. Tests
indicate that our measures provide accurate out-of-sample forecasts of the term structure of systemic risk in the
United States for the period from 1998 to 2009.
Keywords
banks; financial system; correlated failure; systemic risk