Abstract
In this study, we focus on analysing the relationship between the foreign exchange rate and the international tourism flow. Three foreign exchange rate forecasting models including GARCH(1,1), EGARCH(1,1), and the IABC forecasting model based on the computational intelligence are employed to produce the forecasting results. The Mean Absolute Percentage Error (MAPE) is selected to be the evaluation criterion for comparing the forecasting results of these models. The experiments contain the USD/NTD foreign exchange rate and the inbound international tourism flows in years of 2009 to 2010. The experimental results reveal that adding the international tourism flow as the new reference in the forecasting process has the positive contribution to the foreign exchange rate forecasting results.
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This work is funded by the Key Project of Fujian Provincial Education Bureau (JA15323).
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Tsai, PW., Chen, ZS., Xue, X., Chang, JF. (2018). Studying the Influence of Tourism Flow on Foreign Exchange Rate by IABC and Time-Series Models. In: Pan, JS., Tsai, PW., Watada, J., Jain, L. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. IIH-MSP 2017. Smart Innovation, Systems and Technologies, vol 81. Springer, Cham. https://doi.org/10.1007/978-3-319-63856-0_28
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DOI: https://doi.org/10.1007/978-3-319-63856-0_28
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