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The aim of this study is to forecast credit ratings of E.U. banking institutions, as dictated by Credit Rating Agencies (CRAs). To do so, we developed alternative forecasting models that determine the non-disclosed criteria used in rating. We compiled a sample of 112 E.U. banking institutions,...
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We combine signal processing to machine learning methodologies by introducing a hybrid Ensemble Empirical Mode Decomposition (EEMD), Multivariate Adaptive Regression Splines (MARS) and Support Vector Regression (SVR) model in order to forecast the monthly and daily Euro (EUR)/United States...
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Forecasting the evolution path of macroeconomic variables has always been of keen interest to policy makers and market participants. A common tool used in the relevant forecasting literature is the term spread of Treasury bond yields. In this paper, we decompose the term spread into an...
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