For this project, use monthly historical data from $2000$ to end the most recent calendar year$1.$ Analyze $5$ to $10$ individual stocks; you can pick any stock you want to analyze. Then compose a portfolio based on any combination of the stocks, analyze the portfolio. Specific tasks and questions to be answered through the project include: $$ Explore and describe the dataset $($e$.$g$.,$ descriptive statistics, simple profiling$)$ Compare the cumulative performance of the stocks; use visualization effectively $$ Compare the alphas and betas of the stocks as well as your portfolio $$ Are the alphas different from $0$ at $0\mathrm{.}05$ significance level $($Hypothesis testing for beta is optional; see section $5$ for information if you are interested$)$ How do the parameters change over time $$ Compute the average Sharpe ratio of the recent five years for all the stocks you selected, your portfolio, and S&P $500$ Draw conclusions from your analysis Word of caution: the analysis is based on historical data, and past performance is no guarantee of future results! Additionally, CAPM is a very simple model; there are improved models that can better explain expected returns. $1$ Although the examples in this documents use the period until $2023,$ you should use the period until the end of the most recent calendar year. $54.$ Submission $(1)$ If you use Jupyter Notebook, use markdown to effectively document your code and output. Submit the $.$ipynb file and the corresponding $$print$-$out$$ as a PDF file. If you do not use Jupyter Notebook: submit a report and your source code files