Bibliographic Details
| Title: |
IntelliTrade-Powered Stock Forecasting AI System with Candlestick Patterns. |
| Authors: |
LEE, CHIUNG-HONG1 cholee@o365.fcu.edu.tw, GAN, YEE-SIANG2 ysgan@o365.fcu.edu.tw, WU, PO-YI1 allen91220@gmail.com, CHUANG, CHENG-WEI1 asabisa52@gmail.com, DENG, YUN-FEI1 xdxd15915@gmail.com |
| Source: |
Journal of Information Science & Engineering. May2026, Vol. 42 Issue 3, p629-643. 15p. |
| Subjects: |
Stock price forecasting, Trend analysis, Electronic trading of securities, Stock charts, Optimization algorithms, Economic decision making |
| Abstract: |
This study proposed a web-based system that utilizes an AI model trained on candlestick patterns to display buy and sell signals, and it uses Direct Preference Optimization (DPO) to dynamically adjust parameters, ensuring that the model can adapt to market changes. Traditional models focus on individual stocks or indices, which are often time-consuming and complex. In contrast, this approach effectively identifies trend initiation points using candlestick patterns. Experimental results show strong performance in recent markets, highlighting the potential of advanced AI techniques for robust stock market analysis and decision-making in financial applications. [ABSTRACT FROM AUTHOR] |
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Copyright of Journal of Information Science & Engineering is the property of Institute of Information Science, Academia Sinica and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |
