Name
Title | ||
|---|---|---|
An Empirical Study of the Artificial Neural Network for Currency Exchange Rate Time Series Prediction. |
Abstract | ||
|---|---|---|
This paper applies an integrated artificial neural network approach to forecast foreign exchange rates between the US dollar and Chinese Renminbi. In order to obtain a better forecasting performance in foreign exchange rates, this study develops an integrated forecasting model, which applies the SPSS as data preprocess method and an artificial neural network application named Alyuda Neuro Intelligence as forecasting tool. The results of this study provide evidence on the effectiveness and efficiency of the integrated artificial neural network model. The findings of this study should contribute positively to the development of theory, methodology, and practice of using artificial neural network to develop a forecasting model with enhanced forecasting accuracy. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-01216-7_57 | SIXTH INTERNATIONAL SYMPOSIUM ON NEURAL NETWORKS (ISNN 2009) |
Keywords | Field | DocType |
Artificial Intelligence,Neural Network,Forecasting,Exchange Rates | Artificial neural network model,Time series,Renminbi,Computer science,Artificial intelligence,Artificial neural network,Empirical research,Machine learning,Liberian dollar,Currency,Exchange rate | Conference |
Volume | ISSN | Citations |
56 | 1867-5662 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ping-Chang Chen | 1 | 1 | 1.36 |
| Chih-Yao Lo | 2 | 8 | 3.75 |
| Hung-Teng Chang | 3 | 0 | 0.34 |