基于神经网络研究人民币汇率对企债收益的影响  

Study on the Influence of RMB Exchange Rate on Enterprise Bond Yield Based on Neural Network

作　　者：周颖 沐年国[1] ZHOU Ying;MU Nian-guo(School of Management,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学管理学院

出　　处：《重庆工商大学学报（自然科学版）》2020年第1期71-77,共7页Journal of Chongqing Technology and Business University:Natural Science Edition

摘　　要：为了研究企业债券市场,并针对汇率波动对企债市场的影响,提出建立LSTM和GRU两种神经网络模型;首先证明了它们对于企业债券市场收益的研究具有良好的拟合和预测效果,再将人民币兑美元的汇率数据作为神经网络的输入变量之一,验证人民币汇率对企债市场收益的影响,并比较两种模型的预测效果;结果显示:加入汇率指标后,两种模型不仅能捕捉收益趋势,同时都在数值上也更加精准可靠。实证研究表明,目前在研究我国企业债券市场时,人民币汇率是不可忽略的影响因素,并且相较而言GRU模型的结果更为精准。In order to study the corporate bond market and deal with the impact of exchange rate fluctuations on the corporate bond market, we propose to establish two neural network models of LSTM and GRU, first demonstrating that they have a good fit and prediction effect on the research of corporate bond market returns. Using the exchange rate data of RMB against the US dollar as one of the input variables of the neural network,we verify the impact of the RMB exchange rate on the corporate bond market returns and compare the prediction effects of the two models. The results show that after adding the exchange rate indicator,the two models can not only capture the yield trend,but also the value is more accurate and reliable. Empirical studies show that the RMB exchange rate is a non-negligible factor in the study of China’s corporate bond market,and the results of the GRU model are more accurate.

关 键 词：汇率 上证企债指数 对数收益率 LSTM GRU 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]