Prediction of Stock Price Direction with Trading Indicators using Machine Learning Techniques

Stock market provides a platform where people can engage in trading. Such tradings contribute to the growth of economy. It is a very intriguing research topic to predict the direction of a stock price i.e. if a stock is neutral or going upwards or downwards. If such prediction can be done efficiently, people can invest more systematically. In this research, we have addressed this issue using different trading indicators as features. Different classification models such as K Nearest Neighbor, Decision Tree, Random Forest, Support Vector Machine, AdaBoost, Multilayer Perceptron have been experimented with and they have yielded excellent results.