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Study on Exchange Rate Volatility under Cross-border RMB Settlement Based on Multi-layer Neural Network Algorithm

机译：基于多层神经网络算法的跨境人民币结算下的汇率波动性研究

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摘要

In order to increase profits, foreign trade enterprises need to reduce costs. But cross-border RMB settlement can reduce costs of foreign trade enterprises, which avoids exchange rate risks to some extent and reduces losses. However, cross-border RMB settlement will still be affected by exchange rate changes. In order to explore the law of exchange rate changes and make predictions to reduce the impact of exchange rate changes, the multi-layer neural network algorithm was used to train and test the exchange rates of the USD, EUR, JPY and HKD between November 2017 and July 2018 on the Matlab. The result indicated that the change of currency exchange rate was regular, and different currencies have different characteristics of change. The multi-layer neural network algorithm could accurately predict the exchange rate changes of most currencies and had the best performance in predicting the exchange rates of the USD and EUR, especially the EUR and the second best performance in predicting the exchange rate of the HKD; it could predict the general trend though it had the poorest performance in predicting the exchange rate of the JPY.
机译：为了增加利润，外贸企业需要降低成本。但是跨境人民币结算可以降低外贸企业的成本，在一定程度上避免了汇率风险，减少了损失。但是，跨境人民币结算仍将受到汇率变化的影响。为了探索汇率变化规律并做出预测以减少汇率变化的影响，2017年11月使用多层神经网络算法训练和测试了美元，欧元，日元和港元的汇率和2018年7月在Matlab上。结果表明，货币汇率的变化是规律性的，不同货币具有不同的变化特征。多层神经网络算法可以准确预测大多数货币的汇率变化，在预测美元和欧元（尤其是欧元）汇率方面表现最佳，在预测港元汇率方面表现第二佳；尽管它在预测日元汇率方面表现最差，但可以预测总体趋势。

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