Modelling and forecasting by wavelets, and the application to exchange rates

Heung Wong · Wai-Cheung Ip · Zhongjie Xie · Xueli Lui

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Forecasting Techniques and Applications Stock Market Forecasting Methods Time Series Analysis and Forecasting

Abstract

This paper investigates the modelling and forecasting method for non-stationary time series. Using wavelets, the authors propose a modelling procedure that decomposes the series as the sum of three separate components, namely trend, harmonic and irregular components. The estimates suggested in this paper are all consistent. This method has been used for the modelling of US dollar against DM exchange rate data, and ten steps ahead (2 weeks) forecasting are compared with several other methods. Under the Average Percentage of forecasting Error (APE) criterion, the wavelet approach is the best one. The results suggest that forecasting based on wavelets is a viable alternative to existing methods.

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References

1977Time Series Analysis: Forecasting and Control 1982The accuracy of extrapolation (time series) methods: Results of a forecasting competition

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