Prediction of USD/RMB Price Change Based on BP Neural Network

Authors

  • Xiaorui Li

DOI:

https://doi.org/10.62051/3hfshr07

Keywords:

BP neural network; MATLAB; prediction of USD/RMB price change.

Abstract

The market position of the RMB has gradually increased, and the price change of the US dollar against the RMB has become increasingly important. Therefore, it is vital to use scientific means to forecast the exchange rate forecasting model. In this thesis, the BP neural network model is established by MATLAB, and the price change of the USD/RMB exchange rate is analyzed and processed according to the characteristics of the exchange rate prediction model. Part of the data is elected for the network training, the other part is used to verify the accuracy of neural network prediction. The results indicate that the fitting accuracy is 94.6%. Continuing to modify some arguments of the model including changing the number of training rounds to 100000, and changing the training target to 1e-15 with the learning rate remaining unchanged, The equal accuracy could be further increased to 96%. In the results, the model can precisely, mirror the trend of fluctuations, verify the effectiveness of this forecasting method, provide an important reference for financial institutions and personnel engaged in the financial industry, and have great significance for foreign exchange management to effectively avoid market risks and cope with the impact of exchange rate fluctuations.

Downloads

Download data is not yet available.

References

LuYuanYuan. Based on the GARCH - ELMAN model of RMB exchange rate prediction. Journal of Modern Business, 2022, (13): 56-60.

Deng Jingwei. Research on Foreign exchange rate prediction based on neural network. Jinan University, 2017.

Yan Haifeng, Xie Lili. RMB exchange rate prediction based on GARCH-M model. Journal of Chongqing Technology and Business University (Social Science Edition), 2009, 26 (04): 41-44.

Xu Shaoqiang, Li Yamin. RMB Exchange rate forecast with reference to "Basket" currencies: An empirical method based on ARMA model. International Economic Review, 2007, (03): 30-40.

Carriero A, Kapetanios G, Marcellino M. Forecasting exchange rates with a large Bayesian VARIJ. International Journal of Forecasting, 2009, 25(2): 400-417.

Refens A N, Barac M A, Chen L, et al. Constructive learning and its application to currency exchange rate forecasting. Neural Computing & Application, 1993, 1 (1): 465-493.

Dai Xiaofeng, Xiao Qingxian. Research on Time Series Analysis Method and Application of RMB Exchange rate Forecast. Journal of University of Shanghai for Science and Technology, 2005, 27 (4): 341-344.

Xu Panpan. RMB Exchange rate forecast based on ARMIA-LSTM combination model. Northeast university of finance and economics, 2022.

Wang Li, Yuan Peidong. The RMB exchange rate based on signal analysis and neural network forecasting model research. Journal of Gilu Industrial University, 2020, 34 (5): 61-67.

Feng Wenfang. Analysis of RMB/USD exchange rate trend based on BP neural network. Hebei Enterprise, 2014(1): 46-47.

Yu Dan. Research on Exchange rate prediction based on a synthetic artificial neural network model. Lanzhou Jiaotong University, 2019.

Downloads

Published

12-08-2024

How to Cite

Li, X. (2024) “Prediction of USD/RMB Price Change Based on BP Neural Network”, Transactions on Computer Science and Intelligent Systems Research, 5, pp. 862–867. doi:10.62051/3hfshr07.