 Multiperiod corporate default prediction—A forward intensity approachJin-Chuan Duan, Jie Sun and Tao Wang Journal of Econometrics, 2012, vol. 170, issue 1, 191-209 Abstract: A forward intensity model for the prediction of corporate defaults over different future periods is proposed. Maximum pseudo-likelihood analysis is then conducted on a large sample of the US industrial and financial firms spanning the period 1991–2011 on a monthly basis. Several commonly used factors and firm-specific attributes are shown to be useful for prediction at both short and long horizons. Our implementation also factors in momentum in some variables and documents their importance in default prediction. The model’s prediction is very accurate for shorter horizons. Its accuracy deteriorates somewhat when the horizon is increased to two or three years, but the performance still remains reasonable. The forward intensity model is also amenable to aggregation, which allows for an analysis of default behavior at the portfolio and/or economy level. Keywords: Default; Bankruptcy; Forward intensity; Maximum pseudo-likelihood; Forward default probability; Cumulative default probability; Accuracy ratio (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:170:y:2012:i:1:p:191-209 DOI: 10.1016/j.jeconom.2012.05.002 Access Statistics for this article Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson More articles in Journal of Econometrics from Elsevier |
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