  Stock market prediction has been an active area of research for a
considerable period. Arrival of computing, followed by Machine Learning has
upgraded the speed of research as well as opened new avenues. As part of this
research study, we aimed to predict the future stock movement of shares using
the historical prices aided with availability of sentiment data. Two models
were used as part of the exercise, LSTM was the first model with historical
prices as the independent variable. Sentiment Analysis captured using Intensity
Analyzer was used as the major parameter for Random Forest Model used for the
second part, some macro parameters like Gold, Oil prices, USD exchange rate and
Indian Govt. Securities yields were also added to the model for improved
accuracy of the model. As the end product, prices of 4 stocks viz. Reliance,
HDFC Bank, TCS and SBI were predicted using the aforementioned two models. The
results were evaluated using RMSE metric.
