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Forecasting Cross-Sections of Frailty-Correlated Default

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Author Info
Siem Jan Koopman () (VU University Amsterdam)
André Lucas () (VU University Amsterdam)
Bernd Schwaab () (VU University Amsterdam)

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Abstract

We propose a novel econometric model for estimating and forecasting cross-sections of time-varying conditional default probabilities. The model captures the systematic variation in corporate default counts across e.g. rating and industry groups by using dynamic factors from a large panel of selected macroeconomic and financial data as well as common unobserved risk factors. All factors are statistically and economically significant and together capture a large part of the time-variation in observed default rates. In this framework we improve the out-of-sample forecasting accuracy associated with conditional default probabilities by about 10-35% in terms of Mean Absolute Error, particularly in years of default stress.

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Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 08-029/4.

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Date of creation: 20 Mar 2008
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Handle: RePEc:dgr:uvatin:20080029

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Web page: http://www.tinbergen.nl/

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Related research
Keywords: Non-Gaussian Panel Data; Common Factors; Unobserved Components; Forecasting Conditional Default Probabilities;

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Find related papers by JEL classification:
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data
G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Mortgages

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    Other versions:
  2. Thomas C. Wilson, 1998. "Portfolio credit risk," Economic Policy Review, Federal Reserve Bank of New York, issue Oct, pages 71-82. [Downloadable!]
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    Other versions:
  4. 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. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute. [Downloadable!]
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