Firm Bankruptcy Prediction: A Bayesian Model Averaging Approach
نویسنده
چکیده
I develop a new predictive approach using Bayesian model averaging to account for incomplete knowledge of the true model behind corporate bankruptcy. I find that uncertainty over the correct model is empirically large, with far fewer variables significant predictors of bankruptcy compared to conventional approaches. Only the ratio of total liabilities to total assets and the volatility of market returns are robust bankruptcy predictors in the overall sample and in all industry groups. Model averaged bankruptcy forecasts that aggregate information across models or allow for industry specific effects substantially outperform individual models.
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