EconPapers    
Economics at your fingertips  
 

Forecasting Bankruptcy with Incomplete Information

Xin Xu

MPRA Paper from University Library of Munich, Germany

Abstract: 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 [2001]). 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.

Keywords: Credit Risk Modeling; Incomplete Information; Hazard Models; Bankruptcy Forecast; Probability of Default (PD); Forecasting Accuracy; Intensity-based Models; Reduced-form Models; Duration Analysis; Survival Analysis (search for similar items in EconPapers)
JEL-codes: C41 G17 G33 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cta, nep-for and nep-rmg
Date: 2013-05-28, Revised 2014-03-31
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/55024/1/MPRA_paper_55024.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:55024

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Series data maintained by Joachim Winter ().

 
Page updated 2017-09-29
Handle: RePEc:pra:mprapa:55024