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- Title
Firm Default Prediction: A Bayesian Model-Averaging Approach.
- Authors
Traczynski, Jeffrey
- Abstract
I develop a new predictive approach using Bayesian model averaging to account for incomplete knowledge of the true model behind corporate default and bankruptcy filing. I find that uncertainty over the correct model is empirically large, with far fewer variables being significant predictors of default compared with conventional approaches. Only the ratio of total liabilities to total assets and the volatility of market returns are robust default predictors in the overall sample and individual industry groups. Model-averaged forecasts that aggregate information across models or allow for industry-specific effects substantially outperform individual models.
- Subjects
DEFAULT (Finance); BANKRUPTCY; BAYESIAN analysis; MATHEMATICAL models of forecasting; CORPORATE bankruptcy statistics; UNCERTAINTY; ASSET-liability management; COUNTERPARTY risk; FORECASTING
- Publication
Journal of Financial & Quantitative Analysis, 2017, Vol 52, p1211
- ISSN
0022-1090
- Publication type
Article
- DOI
10.1017/S002210901700031X