In this project, the portfolio returns of the bulge bracket Hedge funds, Private Equity firms, imaginary portfolios- Algo 1 and Algo 2, as well as the returns of a custom portfolio of 3 stocks are analyzed, in comparison with the benchmark S&P 500.

This project is a part of the UC Berkeley Fintech Bootcamp Week-4.

• Python
• Pandas package
• Numpy package
• Datetime library
• Path library
• Matplot library

• Git Bash
• Jupyter Lab
• Operating system: Windows 10, 64-bit
• Microsoft CSV
• Google sheets

• Daily returns (percentage change)
• Cumulative returns
• 21-day rolling standard deviation
• Annual standard deviation
• Risk assessment via Box plot
• Exponentially weighted moving average, with a 21-day half life
• Rolling 21-day Beta between 1 imaginary portfolio and the S&P 500.
• Correlation table
• Sharpe ratios

• Daily returns
• Cumulative returns
• Box plot
• Rolling 21-day standard deviation
• Beta
• Exponentially weighted 21-day moving average
• Sharpe ratios
• Rolling 21-day standard deviation between custom portfolio and other portfolios.
• Sharpe ratios between custom portfolio and other portfolios

• Advanced Micro Devices (AMD)
• Netflix (NFLX)
• Tesla (TSLA)

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.ewm.html

https://www.investopedia.com/ask/answers/010815/what-good-sharpe-ratio.asp

https://www.investopedia.com/investing/beta-know-risk/

• Khaled Kharman- Personal tutor
• Kiel Wheat- Bootcamp classmate
• Joel Gonzales- Bootcamp Teaching Assistant

Satheesh Narasimman