The prediction of an exchange direction may function an early recommendation system for short-term investors and as
an early financial distress warning system for long-term shareholders. Forecasting accuracy is the most important thing
about selecting any forecasting methods. Research efforts in improving the accuracy of forecasting models are increasing since
the last decade. The suitable stock selections those are suitable for investment could be a very difficult task. The key factor for
every investor is to earn maximum profit on their investments. In this paper Support Vector Machine (SVM) is proposed.
SVM could be a specific kind of learning algorithm characterized by the capacity control of the choice function, the
employment of the kernel functions and therefore the scarcity of the answer
