Short and long term stock trend prediction using decision tree

This paper presents the results of method designed to predict price trends in the stock market. First objective of this research is to optimize the stock price trend prediction for short term using some oscillators and indicators: Moving Average Convergence Divergence (MACD), the Relative Strength Index (RSI), the Stochastic Oscillator (KDJ) and Bollinger Band (BB). It is observed that using appropriate pre-processing technique and Machine learning model, it is possible to improve accuracy rate of short-term trend prediction. Applying Preprocessing and then using combination of data can yield a better Accuracy rate in Short term Trades, while predicting for Long-term Trend of Stock this Technical indicators are not sufficient. Along with some of this Technical data and Fundamental Data of the company, it is possible to predict Long term stock movement. For Long term Prediction its Debt to Equity, Net profit of pervious 3 year, Promoters holding, Dividend yield and PE ratio is used along with Technical Factors. It is observed that using Fundamental and Technical Data, Long term Stock Prediction is Possible.