The Exploratory Study on the Prediction of the RMB Exchange Rate by Using Gray Relational Analysis and Neural Network
| Autor: | Tsung-Wei Cheng, 鄭漴瑋 |
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| Rok vydání: | 2014 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 102 RMB becomes popular than thirty years ago in currency exchange, nowadays more and more ATM and reserve currency of the central bank in many countries start to make use of RMB. RMB goes through an unusual process in the internationalization, and it also directly reveals that the economy of People’s Public of China (PRC) rapidly spring up during the thirty years. More and more scholars and researchers have studied the field of RMB exchange rate. Yang（2013）took advantage of back propagation neural network to predict RMB exchange. In addition, Feng and Qin（2012）also made use of regression analysis to assay the relations between the fluctuation in RMB exchange rate and total imports-exports and reserve currency. Therefore, to explore and analyze the fluctuation trend in RMB is meaningful and valuable. In this study, the first step is to screen out 11 important factors of the RMB exchange rate, including “balance of trade,” “international balance of payments,” “inflation,” “credit,” ”market expectation,” “reserve currency,” “interest margin,” “GDP,” “investment rates,” “price level” and “money supply.” Then it builds a back propagation neural network database, from 2004 to 2012, and tries to figure out the best model to predict the RMB exchange rate in the future. Secondly, it puts 11 factors from grey relational analysis into the model and uses stepwise regression procedure to build a simple and efficient multiple regression model. At last, according to the data of RMB exchange in 2013, the study tries to compare these two models in accuracy of prediction for the trend of exchange rate in RMB. And then, it hopes that the study can define and provide a better model to the investors as references. This study result shoes that back propagation neural network is better than multiple regression model on the prediction of RMB exchange rate.However, multiple regression model is relatively more stable and fewer errors than back propagation neural network. In accuracy of the prediction, back propagation neural network is about 75% and thus it is a worthy reference for RMB investing. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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