Forecasting Bankruptcy with Incomplete Information
We propose new specifications that explicitly account for information noise in the input data of bankruptcy hazard models. The specifications are motivated by a theory of modeling credit risk with incomplete information (Duffie and Lando ). Based on over 2 million firm-months of data during 1979-2012, we demonstrate that our proposed specifications significantly improve both in-sample model fit and out-of-sample forecasting accuracy. The improvements in forecasting accuracy are persistent throughout the 10-year holdout periods. The improvements are also robust to empirical setup, and are more substantial in cases where information quality is a more serious problem. Our findings provide strong empirical support for using our proposed hazard specifications in credit risk research and industry applications. They also reconcile conflicting empirical results in the literature.
|Date of creation:||28 May 2013|
|Date of revision:||31 Mar 2014|
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- Darrell Duffie & Leandro Siata & Ke Wang, 2006.
"Multi-Period Corporate Default Prediction With Stochastic Covariates,"
NBER Working Papers
11962, National Bureau of Economic Research, Inc.
- Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CARF F-Series CARF-F-047, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CIRJE F-Series CIRJE-F-373, CIRJE, Faculty of Economics, University of Tokyo.
- Giesecke, Kay & Longstaff, Francis A. & Schaefer, Stephen & Strebulaev, Ilya, 2011. "Corporate bond default risk: A 150-year perspective," Journal of Financial Economics, Elsevier, vol. 102(2), pages 233-250.
- John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2006.
"In Search of Distress Risk,"
NBER Working Papers
12362, National Bureau of Economic Research, Inc.
- John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2005. "In Searach of Distress Risk," Harvard Institute of Economic Research Working Papers 2081, Harvard - Institute of Economic Research.
- Szilagyi, Jan & Hilscher, Jens & Campbell, John, 2008. "In Search of Distress Risk," Scholarly Articles 3199070, Harvard University Department of Economics.
- Campbell, John Y. & Hilscher, Jens & Szilagyi, Jan, 2005. "In search of distress risk," Discussion Paper Series 1: Economic Studies 2005,27, Deutsche Bundesbank, Research Centre.
- Giesecke, Kay, 2006. "Default and information," Journal of Economic Dynamics and Control, Elsevier, vol. 30(11), pages 2281-2303, November.
- Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
- Leland, Hayne E & Toft, Klaus Bjerre, 1996.
" Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads,"
Journal of Finance,
American Finance Association, vol. 51(3), pages 987-1019, July.
- Hayne E. Leland and Klaus Bjerre Toft., 1995. "Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads," Research Program in Finance Working Papers RPF-259, University of California at Berkeley.
- Hilscher, Jens Dietrich & Campbell, John Y. & Szilagyi, Jan, 2011. "Predicting Financial Distress and the Performance of Distressed Stocks," Scholarly Articles 9887619, Harvard University Department of Economics.
- Giesecke, Kay, 2004. "Correlated default with incomplete information," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1521-1545, July.
- Duan, Jin-Chuan & Sun, Jie & Wang, Tao, 2012. "Multiperiod corporate default prediction—A forward intensity approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 191-209.
- Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, 09.
- Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-24, January.
- X. Frank Zhang, 2006. "Information Uncertainty and Stock Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 105-137, 02.
- Lin, Chen & Ma, Yue & Xuan, Yuhai, 2011. "Ownership structure and financial constraints: Evidence from a structural estimation," Journal of Financial Economics, Elsevier, vol. 102(2), pages 416-431.
- Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
- Duffie, Darrell & Lando, David, 2001. "Term Structures of Credit Spreads with Incomplete Accounting Information," Econometrica, Econometric Society, vol. 69(3), pages 633-64, May.
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