PANDAS (FinTech Unit 4 HW)
Harold's company has been investing in algorithmic trading strategies. Some of the investment managers love them, some hate them, but they all think their way is best.
You just learned these quantitative analysis techniques with Python and Pandas, so Harold has come to you with a challenge—to help him determine which portfolio is performing the best across multiple areas: volatility, returns, risk, and Sharpe ratios.
I created a tool (an analysis notebook) that analyzes and visualizes the major metrics of the portfolios across all of the areas mentioned above, and determined which portfolio outperformed the others. I used given historical daily returns of several portfolios: some from the firm's algorithmic portfolios, some that represent the portfolios of famous "whale" investors like Warren Buffett, and some from the big hedge and mutual funds. I then used that analysis to create a custom portfolio of stocks and compared its performance to that of the other portfolios, as well as the larger market (S&P 500 Index).
In the Jupyter Notebook, I have completed the following:
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Read in and Wrangled "Returns" Data
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Determined Success of Each Portfolio: Conducted Quantitative Analysis
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Chose and Evaluated a Custom Portfolio: Created a Custom Portfolio
Final analysis notebook is located in 'whale_analysis.ipynb'.