Learnt about the Markowitz theory to diversify portfolio to earn a particular interest with the smallest amount of risk and implemented the theory in python by analysing the Nifty 50 stocks over 4 years.

• Analyzed the Nifty 50 stocks from 01/01/2016 to 31/11/2020 with Numpy and Pandas.
• Calculated the Volatility , Compound Annual Growth Rate(CAGR) and Sharpe Ratio for the stock price series.
• Indentified the top 15 stocks with highest Sharpe Ratio.

• Initialized random weights to the 15 stocks (600000 different sets of weights to have a large representative sample) and calculated the expected return, volatility and sharpe ratio corresponding to each of the weights.
• Identified the maximum sharpe ratio of the weight and plotted the portfolios on a Scatter Plot using MatPlotLib.
• Plotted the Efficient Frontier using SLSQP method.
• Distributed a total amount of 1,00,00,000 to get the amount of money for each stock and the number of stocks in our portfolio.

• Tested the Portfolio generated from the observation period(2016-2020). Testing period : 1 Jan'21 - 30 Jun'21.
• Scraped the data of stocks from Yahoo using the yfinance library.
• Compared the portfolio with the benchmark(Nifty 50) over several metrics:
  1. Total Return on Portfolio
  2. Volatility and Sharpe Ratio
  3. Beta
  4. Jenson's Alpha
  5. Sortino/Teynor Ratio

Datafile: nifty50.csv