Forecasting exchange rates: An optimal approach

被引:0
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作者
Christina Beneki
Masoud Yarmohammadi
机构
[1] Technological Educational Institute of Ionian Islands,School of Business and Economics, Department of Business Administration
[2] Payame Noor University,Department of Statistics
关键词
China; European union; exchange rates; forecasting; neural networks; recurrent singular spectrum analysis; United Kingdom; vector singular spectrum analysis;
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摘要
This paper looks at forecasting daily exchange rates for the United Kingdom, European Union, and China. Here, the authors evaluate the forecasting performance of neural networks (NN), vector singular spectrum analysis (VSSA), and recurrent singular spectrum analysis (RSSA) for forecasting exchange rates in these countries. The authors find statistically significant evidence based on the RMSE, that both VSSA and RSSA models outperform NN at forecasting the highly unpredictable exchange rates for China. However, the authors find no evidence to suggest any difference between the forecasting accuracy of the three models for UK and EU exchange rates.
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页码:21 / 28
页数:7
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