Early warning systems via machine learning: a study of currency crises
DOI:
https://doi.org/10.11606/1980-5330/ea189768Keywords:
currency crises, forecasting, machine learningAbstract
Early Warning Systems (EWS) for currency crises is an essential topic in macroeconomics, renewed by the introduction of machine learning methods. Most published works have overly optimistic accuracy metrics caused
by disregarding autocorrelation or data publication lags. Our contribution is to build an Early Warning System based on an ensemble of machine learning models appropriate for time series data. Using data from 25 countries between 1995 to 2020, our findings are more modest than recent works but highlight the usefulness and limitations of Early Warning Systems in practice.
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