Using the Self-Organizing Maps to Forecast the Trend of Exchange-Rate in the Taiwan Monetary Market
| Autor: | YU KUO-CHENG, 游國誠 |
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| Rok vydání: | 2006 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 94 Fluctuation of foreign exchange rate had tremendous influences towards Taiwan’s market since Taiwan’s economy had highly business dependence on international trade. The loss due to the fluctuation of foreign exchange was so big that could reach the annual profit of a mid-sized, listed company in TSEC Market. Therefore, the ability to forecast exchange rate precisely had become the key to compete with other transnational companies. Due to the advanced information technology, Artificial Intelligence, especially Artificial Neural Network, applied more in financial forecast. Based on the experiment, Artificial Neural Network could improve the accuracy of financial forecast. The Self-Organizing Maps (SOM), one of the Artificial Neural Network algorithm, is a method to reduce the dimension of data and display the data in low dimension space, and capable with pattern recognition. In order to forecast the reliable trading signal of the next trend period for the investors, this research had adopted the Self-Organizing Maps algorithm for the K-Chart pattern learning of Taiwan foreign exchange rate. The conclusion of this research had demonstrated that SOM network is capable of grouping K-Chart pattern effectively. Based on the forecasted K-Chart pattern, the reliable trading signal could be determined and the suggestion of investment could be provided as well. However, since the trading signal determination provided by SOM was not dynamic enough, BPN could be the aid to improve the case. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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