Forecasting Cross-Sections of Frailty-Correlated Default

Siem Jan Koopman (), Andre Lucas () and Bernd Schwaab ()
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Bernd Schwaab: VU University Amsterdam

No 08-029/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

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.

Keywords: Non-Gaussian Panel Data; Common Factors; Unobserved Components; Forecasting Conditional Default Probabilities (search for similar items in EconPapers)
JEL-codes: C33 G21 (search for similar items in EconPapers)
Date: Written
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