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IMPROVING STOCK INVESTMENT DECISION WITH ARTIFICIAL NEURAL NETWORK |
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| รหัสดีโอไอ | |
| Creator | Aekkachai Nittayagasetwat |
| Title | IMPROVING STOCK INVESTMENT DECISION WITH ARTIFICIAL NEURAL NETWORK |
| Contributor | Jiroj Buranasiri |
| Publisher | คณะนิเทศศาสตร์ มหาวิทยาลัยราชภัฏรำไพพรรณี |
| Publication Year | 2567 |
| Journal Title | วารสารนวัตกรรมสังคมและเทคโนโลยีสื่อสารมวลชน |
| Journal Vol. | 7 |
| Journal No. | 2 |
| Page no. | 1-12 |
| Keyword | Artificial Neural Network (ANN), the Stock Exchange of Thailand, market efficiency |
| URL Website | https://so04.tci-thaijo.org/index.php/JRBGS |
| Website title | https://so04.tci-thaijo.org/index.php/JRBGS |
| ISSN | 2822-0463 |
| Abstract | Artificial neural network (ANN) is used for providing investment decisions to investors but are not yet widespread in the Thai stock market because of doubts about the effectiveness of such techniques and the market efficiency level, which makes trading data unable to be used to predict the future direction of stock prices. Thus, this study aims to explore the effectiveness of using artificial neural networks to improve investment decisions and to prove the efficiency of the Stock Exchange of Thailand by testing the accuracy of investment decision recommendations from such techniques. The independent variables of this research are from data from the previous day, which are typically used in technical analysis, including price, trading value, returns, the existence of holiday after trading, and returns of the Dow Jones Index, which represents foreign investment. The reason for using these data is that they reflect the information on demand and supply in stock trading, and the domestic stock exchange and foreign stock exchanges publicly disclose them. The results of the study support the feasibility of using ANN to provide decision advice to investors. The recommendations were correct up to 70% and showed that the Stock Exchange of Thailand was not able to meet the assumption of low pricing efficiency. |
