Statistical models based on machine learning offer a better approach to predicting financial crises than longer-established methods, a working paper published this month by the European Central Bank argues.

In Toward robust early-warning models: a horse race, ensembles and model uncertainty, Markus Holopainen and Peter Sarlin examine how well different types of model predict financial crises. The authors conduct a competition, or "horse race", between conventional statistical methods and machine