利用线性和非线性神经网络方法确定人民币汇率制度

Xiaobing Feng
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摘要

自2005年以来,中国一直声称将朝着更加市场化的外汇管理体系迈进。然而,中国在某种程度上仍然是一个有管理的经济体制。本文利用传统的线性模型和人工神经网络(ANN)研究了原教旨主义、图表派和货币安排在决定人民币汇率制度中的相对重要性。我们发现,对美元作为参考货币的重视程度有所下降。原教旨主义势力是货币兑换的重要决定因素。RBF神经网络模型在最小化预测误差方面表现最好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determining the RMB Exchange Regime Using Linear and Nonlinear ANN Approaches
Since 2005 China has claimed that it will move towards a more market-oriented system of managing its foreign exchange. China, however, has remained in part a managed economic system. This article examines the relative importance of fundamentalist, chartist and currency arrangements in determining the RMB exchange regime using both traditional linear models and artificial neural networks (ANN). We find that the emphasis on the US Dollar as a reference currency has declined. Fundamentalist forces are strong determinants of the currency exchange. The RBF ANN model is among the best performing in minimizing forecasting error.
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