alexa Comparing RMB Exchange Rate Forecasting Accuracy based on Dynamic BP Neural Network Model and the ARMA Model
ISSN: 2168-9458

Journal of Stock & Forex Trading
Open Access

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Research Article

Comparing RMB Exchange Rate Forecasting Accuracy based on Dynamic BP Neural Network Model and the ARMA Model

Zhiqiang Ye1, Xiang Ren2 and Yaling Shan1*

1Department of Finance, School of Business, East China University of Science and Technology, Shanghai, China

2Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China

*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.

 

Abstract

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.

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