Predictions and Trend Analysis for Stock Market Using Machine Learning Algorithms

This paper exploits some of the Industry standard applications for trading and gives new insights on few ML models, namely LSTM, ARIMA, SVR. Techniques like Bollinger Bands and Support and Resistance are implemented to help in understanding the stock data better. The usage of Optimal Portfolio has been demonstrated to aid in making buy/sell decisions. It also talks clearly about the 20 min window used by certain trading application when a new user tries to learn trading, and how the new users are being manipulated. It gives an alternate approach to paper trading with no real money involved and the most appropriate ML models that can be used for short term prediction through commodity hardware.