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  3. FIN41910: You are required to construct and evaluate a “decarbonized” equity portfolio using Excel and data: Green Data Science Assignment, UCD, Ireland

FIN41910: You are required to construct and evaluate a “decarbonized” equity portfolio using Excel and data: Green Data Science Assignment, UCD, Ireland

University University College Dublin (UCD)

You are required to construct and evaluate a “decarbonized” equity portfolio using Excel and data provided for S&P 500 index. You are provided with the data on the company, sector, monthly returns, market capitalization, and various carbon-related and ESG data.

  1. Select 100 random stocks from the index. Try to ensure that all sectors are represented. Construct a market capitalization-weighted index.
  2. Choose the carbon metric that you will use for the decarbonized portfolio optimization. E.g. in class, we used carbon intensity as (Scope 1&2 emissions)/Sales. You can choose, for example, Emissions/Number of Employees, Refinitiv’s Emission Score, etc. There is no one right answer here but your choice needs to be motivated (see part 2 – individual report).
  3. Present descriptive statistics for your market cap-based portfolio including mean, standard deviation, min, max, and 80th, 75th, 25th and 20th
  4. Set up the carbon metric target for your decarbonized portfolio. E.g. in class, we aimed to reduce carbon intensity by 50%.
  5. Set up and solve the optimization problems that produce decarbonized portfolios while tracking the performance of the market cap-based index. At the minimum, you can replicate Optimizations 1, 2, and 3 from the class file. However, you can also change and adapt the optimization setup or any constraints as long as you can explain why you do that. For all optimization procedures, include a screenshot of the Solver with the objective function and constraints.
  6. Set up and solve the optimization problem that produces a mean-variance efficient portfolio.
  7. Set up and solve the optimization problem that finds a mean-variance efficient portfolio given the additional carbon constraint. Again, at the minimum, you can replicate the optimization done in class. You can also set up the problem in your own way.
  8. Present the descriptive statistics of ESG performance of the resulting decarbonized portfolios and the MPT-based portfolio.

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