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Markowitz Portfolio Management

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.

Assignment 1

  • 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.

Assignment 2

  • 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.

Assignment 3

  • 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