| Summary: | 碩士 === 中原大學 === 企業管理研究所 === 94 === This research discusses constitution process and forecasting issue for Asian currency units (ACU) in terms of ten Asian countries including Japan, Indonesia, Malaysia, Hong Kong, South Korea, Singapore, Thailand, Philippine, Taiwan and China. The first, this article provides the analysis of forecasting performance for ACU against U. S. Dollars by employing variant of methods, e.g. Back-propagation neural network (BPN), recurrent neural network (RNN), time-delay recurrent neural network (TDRNN) and GARCH. The weekly exchange rate data for ACU was covered from March 1992 to June 2005. The results showed that ANNs has better performance than GARCH and BPN model presents prominent forecasting performance in most of division conditions.
The second part is to identify the modified components for central value of Asian currency units (ACU). We utilize back-propagation neural network (BPN) to implement the optimal components analysis and compare the results with radial basis function neural network (RBFNN). We constitute eight models to evaluate the impacts of macroeconomic variables on central value of ACU. The empirical evidence supports that our sample countries need to take foreign direct investment, external debt and bank’s claim on private sector into account for expressing the central value of ACU more effectively.
To verify contagion causes for Asia flu, the data was covered from 1996 to 1998. The experimental model is adaptive network-based fuzzy inference system (ANFIS). The empirical result was indicated that the contagion effect would most likely be influenced by tight financial linkage and similarly macroeconomic condition. This finding could provide solution for authority to diminish the probability of contagion via controlling financial correspondence in inter-bank flows and fundamentally macroeconomic similarity.
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