FOREX rate prediction: A hybrid approach using chaos theory and multivariate adaptive regression splines

Abstract

In order to predict foreign exchange (FOREX) rates, this paper proposes a new hybrid forecasting approach viz., Chaos+MARS involving chaos theory and multivariate adaptive regression splines (MARS). Chaos theory aims at constructing state space from the given exchange rate data with the help of embedding parameters, whereas MARS aims at yielding accurate predictions using state space constructed. The proposed model is tested for predicting three major FOREX Rates-JPY/USD, GBP/USD, and EUR/USD. The results obtained unveil that the Chaos +MARS yields the accurate predictions than other chaos-based hybrid forecasting models and recommend it as an alternative approach to FOREX rate prediction.