Uncertainty in financial crisis prediction: a Bayesian approach

Jack Page

Systemic financial crises occur infrequently, giving relatively few crisis observations to feed into the models that try to warn when a crisis is on the horizon. So how certain are these models? And can policymakers trust them when making vital decisions related to financial stability? In this blog, I build a Bayesian neural network to predict financial crises. I show that such a framework can effectively quantify the uncertainty inherent in prediction.

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