Document Type
Article
Abstract
Investment strategy is the key point of investors who can make profits or otherwise. Investors always focus on their viewpoints subjectively, which may make them fall into the logic puzzle. The purpose of this paper is to integrate the technical analysis of financial markets with an emerging neural network model, Support Vector Machine (SVM), to solve the problem of investment strategy in Taiwan Futures Market (TAIFEX). The evaluation of investment strategy is the most essential task of investment analysis. However, the evaluation is usually time-consuming and laborious for investment experts. An effective and efficient decision support tool could significantly alleviate his/her burden and improve decision quality. The experimental results from a real-case study demonstrate its salient features of generalization and usability compared with original technical analysis.
Recommended Citation
Li, Sheng-Tun; Shiue, Weissor; Huang, Meng-Huah; and Tseng, Shih-Yu, "Investment Strategy Analysis using Support Vector Machines" (2003). ICEB 2003 Proceedings (Singapore). 8.
https://aisel.aisnet.org/iceb2003/8