Systemic Risk: What Defaults Are Telling Us

Published Online:https://doi.org/10.1287/mnsc.1110.1375

References

  • Acharya V., Yorulmazer T. Information contagion and bank herding. J. Money, Credit, Banking (2008) 40(1):215–231CrossrefGoogle Scholar
  • Acharya V., Pedersen L., Philippon T., Richardson M. Measuring systemic risk. (2010) . Working paper, New York University, New YorkCrossrefGoogle Scholar
  • Adrian T., Brunnermeier M. CoVaR. (2010) . Working paper, Princeton University, Princeton, NJGoogle Scholar
  • Aharony J., Swary I. Contagion effects of bank failures: Evidence from capital markets. J. Bus. (1983) 56(3):305–317CrossrefGoogle Scholar
  • Aharony J., Swary I. Additional evidence on the information-based contagion effects of bank failures. J. Banking Finance (1996) 20(1):57–69CrossrefGoogle Scholar
  • Avesani R., Pascual A. G., Li J. A new risk indicator and stress testing tool: A multifactor nth-to-default CDS basket. (2006) . IMF Working Paper 06/105, International Monetary Fund, Washington, DCGoogle Scholar
  • Azizpour S., Giesecke K., Schwenkler G. Exploring the sources of default clustering. (2010) . Working paper, Stanford University, Palo Alto, CAGoogle Scholar
  • Berkowitz J., Christoffersen P., Pelletier D. Evaluating value-at-risk models with desk-level data. Management Sci. (2009) . ePub ahead of print January 28, http://mansci.journal.informs.org/cgi/content/abstract/mnsc.1080.0964v1Google Scholar
  • Brown C., Dinc S. The politics of bank failures: Evidence from emerging markets. Quart. J. Econom. (2005) 120(4):1413–1444CrossrefGoogle Scholar
  • Brown C., Dinc S. Too many to fail? Evidence of regulatory reluctance in bank failures when the banking sector is weak. Rev. Financial Stud. (2011) 24(4):1378–1405CrossrefGoogle Scholar
  • Brownlees C., Engle R. Volatility, correlation and tails for systemic risk measurement. (2010) . Working paper, New York University, New YorkGoogle Scholar
  • Chan-Lau J., Gravelle T. The END: A new indicator of financial and nonfinancial corporate sector vulnerability. (2005) . IMF Working Paper 05/231, International Monetary Fund, Washington, DCGoogle Scholar
  • Chen L., Collin-Dufresne P., Goldstein R. S. On the relation between credit spread puzzles and the equity premium puzzle. Rev. Financial Stud. (2009) 22(9):3367–3409CrossrefGoogle Scholar
  • Christoffersen P. Evaluating interval forecasts. Internat. Econom. Rev. (1998) 39(4):842–862CrossrefGoogle Scholar
  • Cole R., Wu Q. Is hazard or probit more accurate in predicting bank failures? Evidence from U.S. bank failures. (2010) . Working paper, DePaul University, ChicagoGoogle Scholar
  • Collin-Dufresne P., Goldstein R., Helwege J. How large can jump-to-default risk premia be? Modeling contagion via the updating of beliefs. (2009) . Working paper, Columbia University, New YorkGoogle Scholar
  • Cooperman E., Lee W., Wolfe G. The 1985 Ohio thrift crisis, the FSLIC's solvency and rate contagion for retail CDs. J. Finance (1992) 47(3):919–941CrossrefGoogle Scholar
  • Das S., Duffie D., Kapadia N., Saita L. Common failings: How corporate defaults are correlated. J. Finance (2007) 62(1):93–117CrossrefGoogle Scholar
  • Duffie D., Eckner A., Horel G., Saita L. Frailty correlated default. J. Finance (2009) 64(5):2089–2123CrossrefGoogle Scholar
  • Duffie D., Saita L., Wang K. Multi-period corporate default prediction with stochastic covariates. J. Financial Econom. (2007) 83(3):635–665CrossrefGoogle Scholar
  • Engle R., Manganelli S. CAViaR: Conditional autoregressive value at risk by regression quantiles. J. Bus. Econom. Statist. (2004) 22(4):367–381CrossrefGoogle Scholar
  • Eraker B., Johannes M., Polson N. The impact of jumps in volatility and return. J. Finance (2003) 58(3):1269–1300CrossrefGoogle Scholar
  • Estrella A., Trubin M. R. The yield curve as a leading indicator: Some practical issues. Current Issues Econom. Finance (2006) 12(5):1–7Google Scholar
  • Giesecke K. Correlated default with incomplete information. J. Banking Finance (2004) 28(7):1521–1545CrossrefGoogle Scholar
  • Giesecke K., Goldberg L. R., Ding X. A top-down approach to multiname credit. Oper. Res. (2011) 59(2):283–300LinkGoogle Scholar
  • Hamilton D. Moody's senior ratings algorithm and estimated senior ratings. (2005) . Report, Moody's Investors Service. Last accessed June 24, 2011, http://www.moodys.com/researchandratings/Google Scholar
  • Huang X., Zhou H., Zhu H. A framework for assessing the systemic risk of major financial institutions. J. Banking Finance (2009) 33(11):2036–2049CrossrefGoogle Scholar
  • Kass R., Raftery A. Bayes factors. J. Amer. Statist. Assoc. (1995) 90(430):773–795CrossrefGoogle Scholar
  • Koopman S. J., Lucas A., Monteiro A. The multistage latent factor intensity model for credit rating transitions. J. Econometrics (2008) 142(1):399–424CrossrefGoogle Scholar
  • Kupiec P. H. Techniques for verifying the accuracy of risk measurement models. J. Derivatives (1995) 3(2):73–84CrossrefGoogle Scholar
  • Lando D., Nielsen M. S. Correlation in corporate defaults: Contagion or conditional independence? J. Financial Intermediation (2010) 19(3):355–372CrossrefGoogle Scholar
  • Lane W., Looney S., Wansley J. An application of the Cox proportional hazards model to bank failure. J. Banking Finance (1986) 10(4):511–531CrossrefGoogle Scholar
  • Lehar A. Measuring systemic risk: A risk management approach. J. Banking Finance (2005) 29(10):2577–2603CrossrefGoogle Scholar
  • McCullagh P., Nelder J.Generalized Linear Models (1989) (Chapman and Hall, London) CrossrefGoogle Scholar
  • McDonald C., Van de Gucht L. High-yield bond default and call risks. Rev. Econom. Statist. (1999) 81(3):409–419CrossrefGoogle Scholar
  • Meyer P.-A. Démonstration simplifée d'un théorème de Knight. Séminaire de Probabilités V (1971) 191(Springer-Verlag, Berlin) 191–195Lecture Note in MathematicsCrossrefGoogle Scholar
  • Ogata Y. The asymptotic behaviour of maximum likelihood estimators of stationary point processes. Ann. Inst. Statist. Math. (1978) 30(part A):243–261CrossrefGoogle Scholar
  • Schwarcz S. L. Systemic risk. Georgetown Law J. (2008) 97(1):193–249Google Scholar
  • Shumway T. Forecasting bankruptcy more accurately: A simple hazard model. J. Bus. (2001) 74(1):101–124CrossrefGoogle Scholar
  • Whalen G. A proportional hazards model of bank failure: An examination of its usefulness as an early warning model tool. Federal Reserve Bank of Cleveland Econom. Rev. (1991) 1991(QI):21–31Google Scholar
  • Wheelock D., Wilson P. Why do banks disappear? The determinants of U.S. bank failures and acquisitions. Rev. Econom. Statist. (2000) 82(1):127–138CrossrefGoogle Scholar
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