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Computational Forecasting of Two Exchange Rates

. The 4th International Workshop on Computational Intelligence in Economics and Finance (CIEF'2005), page (CIEF-10). Marriott City Center, Salt Lake City, Utah, USA, (July 2005)

Abstract

genetic programming and artificial neural networks are employed to forecast two different exchange rates, US dollar/Japanese Yen and US dollar/Taiwan dollar. Extended forecasts (that go beyond one-step-ahead) obtained using the computational techniques were compared with naive random walk predictions of the two exchange rates. Sixteen-step-ahead forecasts obtained using genetic programming outperformed the one- and sixteen-step-ahead random walk US dollar/Taiwan dollar exchange rate predictions. Further, sixteen-step-ahead forecasts of the wavelet-transformed US dollar/Japanese Yen exchange rate also using genetic programming outperformed the sixteen-step-ahead random walk predictions of the exchange rate.

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