Basic analysis of stocks and some financial ratios resulting in a CAPM comparison
This project uses Anaconda, NumPy, Pandas DataReader to show: Portfolios and returns Volitilty and Risk Average True Range Risk and Return Risk as standard deviation Sharpe Ratio Monte Carlo Simulation Portfolio Optimisation Correlation of assets Risk and coherence Linear regression vs correlation True Random distribution vs correlated Visulaisation of linear regression Market Beta of the S&P500 Capital Wealth pricing model (CAPM) Beta and CAPM calculations Expected return on investment
The full workflow is to start with bash for windows, git, replit, github autopilot, jupyter notebook, tableau, output to excel or machine readable pdfs
The first 3 phases extract data from a csv file. The 4th phase onwards uses APIs.
The data is taken from Yahoo finance. Future data sources will be from SEBI, RBI, NSDL, CSDL, etc.