Conventional models beat machine learning in predicting crises, paper finds
Bundesbank paper contrasts performance of logit approach to machine learning
A conventional logit approach works significantly better than machine learning models in predicting financial crises, a working paper published by the Deutsche Bundesbank finds.
In An evaluation of early-warning models for systemic banking crises: does machine learning improve predictions?, Johannes Beutel, Sophia List and Gregor von Schweinitz construct an early-warning system based on a logit approach. They use this as a benchmark to contrast with machine learning models.
They then apply
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