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B8306 Fall Professor Xuelin Li Due: Friday, Nov 17 1 Problem Set 4 HOMEWORK INSTRUCTIONS Hand in your homework in a single Excel spreadsheet. Answer each question in a separate worksheet. Write the names of all group members and your group number on the first worksheet of your homework. Turn in homework ON CANVAS BY MIDNIGHT on the due date. Question 1. In this question, we will use the portfolio optimization tools we’ve discussed in class to evaluate the effects of “green” investing. Green investing involves choosing stocks for your portfolio based not only on their risk-return characteristics, but also on the social, environmental and governance standards of the company issuing the stock. 1 Say you have been hired by a university endowment to construct a socially responsible portfolio. This portfolio should overweight socially responsible companies, and underweight socially irresponsible companies. However, the university endowment still would like you to optimize the risk-reward of the portfolio subject to your social responsibility mandate. You decide to construct this portfolio using three indexes: the S&P500 index, a global Energy sector index (which is deemed to represent socially “irresponsible” companies), and the MSCI KLD 400 Social Index (which invests in socially “good” companies, like Microsoft, Facebook, Alphabet, Cisco, and so on; we refer to this as SRI for socially responsible investments). Data for the three indexes is contained in the 1- asset-class-levels.csv spreadsheet on Canvas. The data show the total return from investing in the indexes, assuming dividends are reinvested back into the index. a) Calculate the monthly returns for the three indexes, i.e. 𝑃 𝑡+1 /𝑃 𝑡 . b) Calculate the annualized returns and volatilities for the three indexes. Also calculate the Sharpe ratios for the three indexes assuming an annual risk-free rate of 𝑟 𝑓 = 2.5% . c) Calculate the correlation matrix for index returns. 1 A good reference for this is the recent paper Baker, Bergstresser, Serafeim and Wurgler, 2018, Financing the response to climate change: The pricing and ownership of U.S. Green Bonds ,” NBER working paper.
B8306 Fall Professor Xuelin Li Due: Friday, Nov 17 2 d) Find the optimal Sharpe ratio portfolio consisting of these three assets. (Use the average returns, variances and correlations of the three securities, in the same way that we did in class . Make sure that the “Make Unconstrained Variables Non- Negative” checkbox is not chosen – we want to allow negative weights). Does this portfolio seem to satisfy your client’s desire for a “green” investment? (Assume the endowment will invest fully in this portfolio and hold no cash, i.e. there is no need to calculate 𝑤 in this problem.) e) Now trace out the efficient frontier achievable using these three assets. This is a plot of the minimum volatility for a portfolio that has a given expected return. The volatilities are plotted on the x-axis and the expected returns are plotted on the y-axis. The spreadsheet contains a column of expected returns. For each of these you should go to Solver, and find the minimum volatility portfolio (by choosing 2 weights and setting the third equal to 1 − 𝑤 1 − 𝑤 2 ) that has the given expected return (again, make sure to allow negative weights). In Solver you can add a constraint that sets the cell with the portfolio expected return (which we proxy using the portfolio’s historical average return) equal to the desired expected return, e.g., 4%, 5%, …, 8%, 9%, etc. f) You now choose to modify the original problem to generate a greener answer. To do so, instead of using the securities’ historical average returns, you decide to use modified returns, that express your social preferences. For the SRI portfolio its modified return is set equal to its actual historical annualized return plus 0.25%. For the Energy portfolio, its modified return is set equal to its historical annualized return minus 0.25%. Using these modified returns and the actual portfolio volatility , optimize this portfolio’s modified Sharpe ratio (i.e., its modified annual return minus 𝑟 𝑓 divided by the actual volatility). Is the resultant portfolio more socially responsible than the original one from part (d)? What is this green portfolio’s actual (i.e. , using the historical not modified average returns) Sharpe ratio? Where does the portfolio lie relative to the efficient frontier? g) Would you recommend this portfolio to your client? Discuss why or why not. Question 2 . In this question, you will use the monthly return data on the stock market, risk-free T-Bills, and four US industries in the 2-industry-rets.csv file on Canvas. The goal is to test the CAPM’s empirical ability to explain the value-weighted average
B8306 Fall Professor Xuelin Li Due: Friday, Nov 17 3 stock returns for four US industries (food, smoking, toy, and steel) from 1926 through the present day. To do this, you will estimate industries betas and their average excess returns during this period. NOTE: This dataset is available from Ken French’s website at Dartmouth. The industry returns come from his monthly 49 industry portfolio files; and the market return and risk-free rate come from the Fama/French 3 Factors monthly file. a) Compute the monthly excess stock returns for the market and for each of the four industries by subtracting the risk-free returns from each asset ’s raw returns . b) Using Excel’s slope() function, compute the beta of each of the four industries using the entire data sample, based on the monthly excess returns of the stocks and the market computed in (a). Check that the beta estimates align with economic intuition. c) Compute the annualized average excess stock returns for each of the four industries and for the market for the entire period. d) If the market’s average excess return over the entire data sample is a good estimate of its expected excess return and the CAPM is correct, what should the slope of the security market line (SML) be? e) U sing Excel’s slope function, compute the slope of a line of best fit that summarizes the relationship between the four industries average excess returns (the y-axis) and their betas (the x-axis) in this period. Do the industries with higher betas experience higher average returns? How does the slope of this relationship compare to your answer to (d)? f) Compute each of the four industries’ alphas using the entire data sample. [Again, assume that the market’s average excess return in the period is a good estimate of its expected excess return.] What does the CAPM predict that these four alphas should be? Which industries perform better or worse than the CAPM predicts? g) Plot the CAPM’s predicted SML for the period . [The SML when done with excess returns starts at the origin and increases as a function of securities betas with a
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B8306 Fall Professor Xuelin Li Due: Friday, Nov 17 4 slope given by the market’s excess return. ] Assets’ expected ( which we’ll estimate as the average for the period) excess returns should be on the y -axis and assets’ betas should be on the x -axis. Add four points for the four industries to your plot. How should we interpret the vertical distance between each of the four points and the SML? h) Compute the annualized Sharpe ratios for each of the four industries and the market during the period. [You will need to use annualized returns and annualized volatility.] Which of these five assets has the highest Sharpe ratio? Is this consistent with the CAPM’s prediction? i) Would it have been possible during this period to use any of the industries in this analysis to construct an overall portfolio that had a higher Sharpe ratio than the market? Be sure to reconcile this answer with your answer to part (h).