Combining Technical Analysis and Support Vector Machine for Stock Trading

Support vector machine (SVM) is a very powerful machine learning algorithm that can be applied to many kinds of applications, not only computation sciences but investing tasks also. This paper presents a new algorithm combining SVM with technical analysis for investing in stocks. RReliefF feature selection is used to choose the appropriate training and trading features for SVM. The experimental results show that we can make very appreciating investments from the new investing strategy.