Comparing RMB Exchange Rate Forecasting Accuracy based on Dynamic BP Neural Network Model and the ARMA Model
- *Corresponding Author:
- Yaling Shan
Department of Finance
School of Business
East China University of Science and
Technology, Shanghai, China
Tel: +86 21 6425 2518
E-mail: [email protected]
Received Date: October 19, 2015; Accepted Date: November 04, 2015; Published Date: November 09, 2015
Citation: Ye Z, Ren X, Shan Y (2015) Comparing RMB Exchange Rate Forecasting Accuracy based on Dynamic BP Neural Network Model and the ARMA Model. J Stock Forex Trad 4:161. doi:10.4172/2168-9458.1000161
Copyright: © 2015 Ye Z, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
This paper uses the dynamic back propagation (BP) neural network model and the autoregressive moving average (ARMA) model to forecast the RMB exchange rate based on the data from January 1, 2011 to October 10, 2012. The results show that the dynamic BP neural network model works better than the ARMA model in evaluating both the trend and the deviation of RMB exchange rate.