Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. Successful estimation of future stock prices can yield signi cant profi ts. Several fi nancial investment decisions are based on such forecasts and analysis. The aim of this project is to estimate the closing price of stocks using bayesian analysis to aid in investment decisions with regards to purchase/sale of stocks. Closing price of stocks is the final value of stock price before the market closes for the day. Since stock market prediction is prone to fluctuations with a lot of money at stake, bayesian analysis could be very helpful as it can capture uncertainty in parameter estimation and hence in predictions.
Detailed analysis and conclusions has been provided in the report
The code has been written in python programming language(version 3.7) in jupyter notebook environment. Please make sure version of your python is >=3.7 and jupyter notebook is installed.
Packages that needs to be installed
- tensorflow_probability
- tensorflow
- statsmodels
- math
- matplotlib
- numpy
- pandas
- pandas_datareader
- datetime
- plotly