A study on Strategies of Trading the News Using Massive Data Mining

Abstract

Predicting the correlation between the events and price movement is quiet challenge in the dynamic environment. The refreshing rate of stock price results huge volume of data and therefore forecasting the financial series is chaotic and stochastic. The volume participation of share is determined by other facts including sectorial or individual share news and it leads to volume increased and price increased shares in the nonlinear market. Most of the times the price relies on mathematical model rather than news or information shared in the media. New investors find it is difficult to consider either news or mathematical models for prediction. Our proposed model recommends decision to novice traders to avoid such loses in their portfolio using massive data. Using this approach, an investor can see the impact of an event and its outcome instead of betting on the shares randomly and reduce the false effect on trading the news.