Paper Title
An Integrated Approach for Investment Recommendations for Sensex Stocks in Indian Stock Market using Machine Learning Approach

This research is to build an integrated model which outputs accurate suggestions for both short and long-term investors. 3 modules are implemented through machine learning approach for providing the investment suggestions to investors which are revising and refining fundamental machine learning module, sentiment analysis module, classification module respectively for providing the investment suggestions to investors. Most of the researchers trying to predict the prices in stock market focusses on either fundamental analysis or sentimental analysis alone. A model that uses fundamental information to combine with sentiment analysis used in this study will help the investor make accurate decision in Indian stock market. Classification is carried out with the help of random forest classifier which is used to train and develop the model for providing accurate investment suggestions in the stock market. This Integrated approach has been used to know the investment decisions on long term basis and short-term basis. Keywords - Sentimental analysis, Fundamental Analysis, Sensex returns, Random Forest Classifier Model