Regression Neural Network for Error Correction in Foreign Exchange Forecasting and Trading

Computers and Operations Research, Vol. 31, pp. 1049-1068

Posted: 8 Aug 2006

See all articles by An-Sing Chen

An-Sing Chen

National Chung Cheng University - Department of Finance

Mark T. Leung

University of Texas at San Antonio - Department of Management Science and Statistics

Abstract

Predicting exchange rates has long been a concern in international finance as most standard econometric methods are unable to produce significantly better forecasts than the random walk model. Recent studies provide some evidence for the ability of using multivariate time series models to generate better forecasts. At the same time, artificial neural networks have been emerging as alternatives to predict exchange rates. In this paper, we propose an adaptive forecasting approach which combines the strengths of neural networks and multivariate econometric models. This hybrid approach contains two forecasting stages. In the first stage, a time series model generates estimates of the exchange rates. In the second stage, General Regression Neural Network is used to correct the errors of the estimates. A number of tests and statistical measures are then applied to compare the performances of the two-stage models (with error-correction by neural network) with those of the single-stage models (without error-correction by neural network). Both empirical and trading simulation experiments suggest that the proposed hybrid approach not only produces better exchange rate forecasts but also results in higher investment returns than the single-stage models. The effect of risk aversion in currency trading is also considered.

Keywords: Neural networks, multivariate time series, exchange rate forecasting, foreign currency, investment strategies

Suggested Citation

Chen, An-Sing and Leung, Mark T., Regression Neural Network for Error Correction in Foreign Exchange Forecasting and Trading. Computers and Operations Research, Vol. 31, pp. 1049-1068. Available at SSRN: https://ssrn.com/abstract=922625

An-Sing Chen (Contact Author)

National Chung Cheng University - Department of Finance ( email )

Chia-Yi, Taiwan 621
China
+011 886 5 272 0411 (Phone)
+011 886 5 272 0818 (Fax)

Mark T. Leung

University of Texas at San Antonio - Department of Management Science and Statistics ( email )

San Antonio, TX
United States

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