Abstract This research aims to analyze and to compare the ability of different mathematical models, such as artificial neural networks (ANN) and ARCH and GARCH models, to forecast the daily exchange rates Euro/U.S. dollar (USD), identifying which, among all the models applied, produces more accurate forecasts. By empirically comparing the different mathematical models developed in this research, the traditional indicators for assessing the relevance of the models show that the ARCH and GARCH models, especially in their static formulations, are better than the ANN for analyzing and forecasting the dynamics of the exchange rates.
Forecasting Exchange Rates: a Comparative Analysis
PACELLI, VINCENZO
2012-01-01
Abstract
Abstract This research aims to analyze and to compare the ability of different mathematical models, such as artificial neural networks (ANN) and ARCH and GARCH models, to forecast the daily exchange rates Euro/U.S. dollar (USD), identifying which, among all the models applied, produces more accurate forecasts. By empirically comparing the different mathematical models developed in this research, the traditional indicators for assessing the relevance of the models show that the ARCH and GARCH models, especially in their static formulations, are better than the ANN for analyzing and forecasting the dynamics of the exchange rates.File in questo prodotto:
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