News Mining Agent for Automated Stock Trading: System to Apply data mining techniques in real time to predict movement of stocks
Stock market dynamics have drawn the attention of analysts from varied academic disciplines and commercial circles. The advent of online trading and real time facilities in the stock markets has fired a new field of interest in developing automatic trading agents that conduct trades in a relatively autonomous fashion under fixed strategies. This book examines a trading strategy based on analysis of external input in the form of online news. A machine-learning model is built using the reaction of stock markets to news items spread over a period of time. The news-based agent uses this model in real time to predict the price movement of stocks, and place orders accordingly. The performance the agent is evaluated by conducting controlled experiments with proven opponent strategies based on statistical models.