Real time decision making forecasting using data mining and decision tree

The stock market is gaining relevance with each day. Much research has been done in the area of finding a means to forecasting the fluctuations. Yet decision-making remains a challenging task in the current age of forecasting. Our proposed algorithm uses autoregressive methods to assist with the decision to buy as well as the selling point for any stock price. The proposed algorithm is more useful for the shareholder than the trader. This decision making tool can be essential to the formation of the business plan and its viability is proved by the significant amount of profit that has already been yielded.