代写Instruction for Homework 2 Evaluating the Portfolio of Telfer Capital Fund代写留学生Python程序
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Evaluating the Portfolio of Telfer Capital Fund
Deadline: Oct 24, 2024
Background: Telfer Capital fund is the leading student investment fund at the University of Ottawa. Please refer to the following website for more information regarding this fund.
https://telfer.uottawa.ca/en/microprogram-capital-markets/
Your tasks:
Task 1: Drew the efficient frontier of all stocks in the Telfer Capital Fund and check if their current holding is on the frontier or not (All the information in the excel file uploaded under Admin/HW2). You can finish this task by modifying the portfolio management code I have uploaded under Admin/HW2 or asking ChatGPT to write code for you.
Note: You need an WRDS account to get access to financial data when using my code. Please reach out to our Financial lab to set up your account: https://uottawa.libguides.com/financelab/resource_descriptions#s-lg-box-wrapper-19494618
Task 2: My code used the mean of stocks’ historical returns as their expected return, which is a very unrealistic estimation of the expected return. In Taks 2, we want to recalculate these expected returns using the Fama-French Four-factor model.
What I am looking for: Changes in the expected returns of each stock in your final picture (from the mean of historical returns to Fama-French-four-factor-based expected returns).
Tools at your disposal:
1) Fama-French Four factor model:
2) French’s website for you to download historical data of all four factors
https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html
3) A excel file that shows how to calculate the expected return of stocks based on Capital Asset Pricing Model.
4) A modified python code that has finished 90% of the homework:
a. Download Fama-French four factors using getFamaFrenchFactor package
b. Calculate the expected return of R_mt (Risk premium of market return to risk free asset), SMB (risk premium of factor SMB), HML(risk premium of factor HML), MOM(risk premium of factor MOM), and R_f (risk free asset)
c. Merge Fama-French four factor with stock historical data
d. The puzzle left:
i. How to calculate the beta for each stock with the all the four factors: R_mt, SMB, HML, and MOM?
ii. How to calculate the expected return of each stock?
iii. How to put the expected return of each stock into an array: monthly_returns, so that you can use the rest of the code to draw the efficient frontier?
Hint: https://pandas.pydata.org/docs/reference/api/pandas.array.html