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An Optimal Early Warning System for Currency Crises Under Model Uncertainty

This paper assesses a number of early warning (EWS) models of financial crises with the aim of proposing an optimal model that can predict the incidence of a currency crisis in developing countries. For this purpose, we employ the dynamic model averaging (DMA) and equal weighting (EW) approaches to combine forecasts from individual models allowing for time varying weights. Taking Egypt as a case study and focusing only on currency crises, our findings show that combining forecasts (DMA- and EW-based EWS) models which account for model uncertainty perform better than other competing models in both in-sample and out-of-sample forecasts.