Economics
FIN371 Carlos Albizu University Miami Campus Investment Analysis Paper

FIN371

### Question Description

I’m stuck on a Economics question and need an explanation.

Pick an asset (stock, ETF, etc.) that has been around for at least 5 years, download the monthly adjusted closing prices and compute monthly returns for the asset and for the market portfolio.

Make sure that you align asset returns with the other variables by date. Conduct the following exercise.

1. Using monthly data, estimate the CAMP equation:

（Attachment)

The dependent variable (Y) is the excess return of the stock, and the independent variable (X) is the excess return of the market portfolio.
Print out:

1. a) data (with variable names clearly marked);
2. b) regression output;
3. c) line fit plot.

1. 1) Report the coefficient estimates, t-statistics, as well as the adjusted R-square;
2. 2) Interpret the beta coefficient and comment on the amount of the market risk this security has;
3. 3) Interpret the alpha coefficient. Evaluate the performance of this asset. Did it outperform/underperform once its market risk exposure is accounted for;
4. 4) If you are the Chief Investment Officer of Vanguard, would you consider incorporating this security into your portfolio? Discuss how you would execute this strategy?

1. What time period should I use? Should I use 20 years, 10 years, or 5 years?

Answer: The decision is yours. Generally speaking, if the returns are from a stable distribution, you want to use as many observations as possible to increase the power of the regression and minimize estimation error. On the other hand, if you think the return distribution has changed and that the more recent data are more appropriate to infer future performance, you want to use only the more recent observations. So the optimal time period is a tradeoff between the two issues mentioned above. If you feel that your stock has been pretty stable over the last 20 years, you want to use all 20 years of data. But if you think last 5 years are more representative, you want to use 5 years.

2. Where do I get data on the returns and on the risk free rate?

You can get SP 500 index (GSPC) closing prices from Yahoo finance. Use the monthly adjusted closing prices to compute returns. Similarly, using a stock’s ticker symbol, you can download its adjusted closing price and compute monthly returns. You can align the data series of the market portfolio and the stock by the dates.

You can use the risk free rate posted on Blackboard “F-F_Research_Data_Factors 2019”.1 Again, you need to make sure that you align the risk free rate, the market and stock returns by the dates. Note that the variable “rf” is the monthly risk free rate in %. You will need to convert it to decimals if your stock and market returns are in decimals.

3. How do I conduct regression analysis?

In Excel, go to “Data”, then “Data Analysis” and select “Regression”. You need to specify that the Y variable is the excess return of the stock and X variable is the excess return of the market portfolio.

If you don’t see “Data Analysis” in your current Excel settings, you can go to “File”, select “Options”, then “Add-ins”, select “Analysis ToolPak”. Then repeat the procedures in the prior paragraph.

equation.png

### Unformatted Attachment Preview

This file was created by CMPT_ME_BEME_RETS using the 201909 CRSP database. The 1-monthInc. TBill return is from Ibbotson and Associates 192607 192608 192609 192610 192611 192612 192701 192702 192703 192704 192705 192706 192707 192708 192709 192710 192711 192712 192801 192802 192803 192804 192805 192806 192807 192808 192809 192810 192811 192812 192901 192902 192903 192904 192905 192906 192907 192908 192909 192910 192911 192912 193001 Mkt-RF SMB HML RF 2.96 -2.3 -2.87 2.64 -1.4 4.19 0.36 -1.32 0.01 -3.24 0.04 0.51 2.53 -0.2 -0.35 2.62 -0.04 -0.02 -0.06 -0.56 4.83 4.18 -0.1 3.17 0.13 -1.6 -2.67 0.46 0.43 0.6 5.44 1.41 4.93 -2.34 0.47 -1.53 7.26 -3.23 -1.16 1.97 -0.72 -3.69 4.76 -3.57 -0.71 -4.31 2.13 -4.33 6.58 2.76 -0.31 2.09 0.93 -1.06 -0.68 4.25 -0.72 -1.7 -2.03 -0.69 8.81 -0.26 -1.2 4.23 3.82 3.67 1.52 2.98 -3.46 -4.85 -3.5 -0.06 0.62 -1.35 -0.47 6.68 -2.07 -2.11 2.88 2.18 0.76 1.33 2.27 -2.26 11.81 -1.81 2.8 0.36 -0.85 -0.6 4.66 -3.54 -1.21 -0.34 -0.39 1.68 -0.89 -4.78 1.56 1.43 -0.99 0.61 -6.39 -5.46 -1.57 9.7 -2.17 -2.76 4.46 -3.88 2.66 8.18 -9.52 0.06 -5.47 1.17 -0.63 -20.12 -4.08 7.85 -12.74 -1.91 5.33 1.33 -4.2 -0.59 5.61 3.58 -1.01 0.22 0.25 0.23 0.32 0.31 0.28 0.25 0.26 0.3 0.25 0.3 0.26 0.3 0.28 0.21 0.25 0.21 0.22 0.25 0.33 0.29 0.22 0.32 0.31 0.32 0.32 0.27 0.41 0.38 0.06 0.34 0.36 0.34 0.36 0.44 0.52 0.33 0.4 0.35 0.46 0.37 0.37 0.14 193002 193003 193004 193005 193006 193007 193008 193009 193010 193011 193012 193101 193102 193103 193104 193105 193106 193107 193108 193109 193110 193111 193112 193201 193202 193203 193204 193205 193206 193207 193208 193209 193210 193211 193212 193301 193302 193303 193304 193305 193306 193307 193308 193309 193310 193311 193312 2.5 7.1 -2.06 -1.66 -16.27 4.12 0.3 -12.75 -8.78 -3.04 -7.83 6.24 10.88 -6.43 -9.98 -13.24 13.9 -6.62 0.41 -29.13 8.04 -9.08 -13.53 -1.58 5.46 -11.21 -17.96 -20.51 -0.7 33.84 37.06 -2.94 -13.17 -5.88 4.4 1.25 -15.24 3.29 38.85 21.43 13.11 -9.63 12.05 -10.65 -8.36 9.97 1.83 0.12 3.44 -0.17 -2.04 -3.22 -0.37 -2.22 -2.22 -0.1 2.21 -4.68 3.81 3.39 3.07 -4.61 5.16 -5.38 1.43 -1.97 0.56 -1.87 4.3 -0.56 3.94 -2.77 2.27 1.44 3.72 0.35 -4.44 14.29 -2.43 -2.76 2.08 -8.27 0.69 -2.75 3.9 4.56 36.7 8.67 -1.01 -5.45 -0.32 -0.08 -6.48 0.66 0.39 0.15 -0.84 -0.63 2 -1.56 -0.78 -5.27 -1.35 -3.53 -5.39 7.21 1.6 -3.65 -3.92 -6.57 11.3 -2.1 -1.49 -6.75 1.7 -5.05 -8.86 9.04 -1.45 -2.32 1.42 -3.28 5.32 35.46 33.03 -6.82 -10.04 -13.28 -8.17 6.23 -2.73 7.38 17.43 19.03 -1.88 3.27 2.96 -11.77 -8.46 2.33 -1.53 0.3 0.35 0.21 0.26 0.27 0.2 0.09 0.22 0.09 0.13 0.14 0.15 0.04 0.13 0.08 0.09 0.08 0.06 0.03 0.03 0.1 0.17 0.12 0.23 0.23 0.16 0.11 0.06 0.02 0.03 0.03 0.03 0.02 0.02 0.01 0.01 -0.03 0.04 0.1 0.04 0.02 0.02 0.03 0.02 0.01 0.02 0.02 193401 193402 193403 193404 193405 193406 193407 193408 193409 193410 193411 193412 193501 193502 193503 193504 193505 193506 193507 193508 193509 193510 193511 193512 193601 193602 193603 193604 193605 193606 193607 193608 193609 193610 193611 193612 193701 193702 193703 193704 193705 193706 193707 193708 193709 193710 193711 12.6 -2.5 0.09 -1.79 -7.25 2.64 -10.96 5.58 -0.23 -1.66 8.33 0.36 -3.45 -1.94 -3.68 9.06 3.47 5.93 7.51 2.65 2.63 7.03 4.88 4.56 6.89 2.49 0.99 -8.14 5.19 2.4 6.67 0.99 0.98 7.12 3.27 0.21 3.35 1.09 -0.27 -7.36 -0.83 -4.21 8.91 -4.86 -13.61 -9.61 -8.31 12.53 5.19 2.51 2.8 -0.26 -2.14 -6.94 5.42 -1.52 1.24 6.49 3.08 1.07 0.42 -3.54 -1.56 -3.34 -2.51 1.47 6.28 1.57 2.65 4.3 0.22 5.1 1.14 0.66 -6.03 0.81 -3.25 1.14 0.72 3.07 -2.39 9.01 3.61 4.31 1.23 -1.78 -3.77 -0.66 -3.65 0.85 0.42 -6.89 0.45 -3.65 15.54 2.12 -2.73 -3.75 -5.91 -2.92 -10.66 0.5 -1.24 -5.11 -2.24 -3.17 -1.89 -7.24 -5.06 4.27 2.61 -1.65 6.86 5.7 -4.05 -2.33 11.91 1.07 10.51 5.04 -1.66 -2.08 2.63 -1.2 2.56 3.99 0.88 2.52 -0.92 3.96 2.61 5.05 6.39 -3.61 -3.49 -3.21 0.82 -2.25 -4.57 -1.62 0.2 0.05 0.02 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.01 0.01 0.01 0.02 0.02 0.02 0.03 0.01 0.02 0.01 0.02 0.01 0 0.01 0.02 0.01 0.03 0.06 0.03 0.03 0.02 0.04 0.02 0.02 193712 193801 193802 193803 193804 193805 193806 193807 193808 193809 193810 193811 193812 193901 193902 193903 193904 193905 193906 193907 193908 193909 193910 193911 193912 194001 194002 194003 194004 194005 194006 194007 194008 194009 194010 194011 194012 194101 194102 194103 194104 194105 194106 194107 194108 194109 194110 -4.24 0.49 5.84 -23.82 14.51 -3.83 23.87 7.34 -2.67 0.81 7.8 -1.72 4.19 -5.96 3.51 -11.99 -0.18 6.8 -5.31 10.24 -6.68 16.88 -0.53 -3.62 3.03 -2.41 1.44 2.05 0.22 -21.95 6.67 3.16 2.19 2.39 3.02 -1.61 0.69 -4.17 -1.43 0.84 -5.46 1.39 5.83 5.87 -0.17 -0.87 -5.25 -7.76 4.97 0.35 -4.24 6.37 -2.47 4.05 6.66 -2.44 -2.72 5.83 -2.56 -1.8 -1.56 0.63 -4.76 1.66 2.81 -1.02 4.32 -4.61 20.23 -0.01 -5.07 0.79 0.24 2.51 1.25 3.92 -6.66 -2.13 1.01 -0.11 3.22 0.28 1.94 -2.15 1 -1.57 0.1 -1.69 -0.66 1.32 5.7 -0.41 -0.99 -2.02 -0.39 -1.6 -2.02 -3.52 0.18 -0.28 0.3 2.18 -4.72 -1.62 5.01 -1.23 0.5 -3.92 2.95 -8.29 -0.3 0.47 -5.41 -0.03 -2.42 22.22 -4.89 -6.46 -4.06 -0.77 -0.32 -1.27 -0.13 -3.69 4.63 -0.74 0.56 -1.13 4.64 0.12 -0.89 3.83 0.89 3.04 3.41 0.6 0.59 7.25 -1.1 -0.28 1.63 0 0 0 -0.01 0.01 0 0 -0.01 0 0.02 0.01 -0.06 0 -0.01 0.01 -0.01 0 0.01 0.01 0 -0.01 0.01 0 0 0 0 0 0 0 -0.02 0 0.01 -0.01 0 0 0 0 -0.01 -0.01 0.01 -0.01 0 0 0.03 0.01 0.01 0 194111 194112 194201 194202 194203 194204 194205 194206 194207 194208 194209 194210 194211 194212 194301 194302 194303 194304 194305 194306 194307 194308 194309 194310 194311 194312 194401 194402 194403 194404 194405 194406 194407 194408 194409 194410 194411 194412 194501 194502 194503 194504 194505 194506 194507 194508 194509 -1.92 -4.87 0.79 -2.46 -6.58 -4.37 5.94 2.69 3.51 1.8 2.61 6.82 0.15 5.12 7.13 6.15 6.01 0.81 5.74 1.82 -4.77 1.3 2.4 -1.15 -5.91 6.36 1.74 0.37 2.46 -1.69 5.07 5.49 -1.49 1.57 0.01 0.16 1.71 4.03 2.01 6.23 -3.89 7.8 1.73 0.39 -2.17 6.2 4.77 -1.21 -2.98 7.52 1.72 1.78 -0.6 -3.05 -1.22 -0.16 -0.09 0.66 1.82 -1.54 -2.49 8.78 4.84 5.03 2.06 4.41 -1.06 -2.41 -0.62 1.28 0.58 -1.64 3.34 2.56 -0.1 1.71 -1.35 1.67 4.04 0.55 2.41 0.47 -0.14 0.37 2.24 2.44 1.56 -1.61 0.32 1.51 3.1 -1.46 1.61 1.71 -0.64 -5.94 10.1 -1.13 -0.62 2.09 -2.65 0.54 2.4 1.33 2.39 6.47 -4.24 0.56 8.23 6.51 5.48 5.86 3.28 -0.74 -2.27 -0.47 1.43 1.65 -4.04 3.22 2.17 0.83 3.43 -1.13 1.02 1.82 -0.43 -1.63 -1.21 -0.34 2.31 5.91 0.71 4.4 -1.78 3.21 0.35 4.32 -2.71 -4.4 0.48 0 0.01 0.02 0.01 0.01 0.01 0.03 0.02 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.02 0.03 0.03 0.03 0.03 0.03 0.02 0.03 0.03 0.02 0.03 0.02 0.02 0.03 0.03 0.02 0.03 0.03 0.03 194510 194511 194512 194601 194602 194603 194604 194605 194606 194607 194608 194609 194610 194611 194612 194701 194702 194703 194704 194705 194706 194707 194708 194709 194710 194711 194712 194801 194802 194803 194804 194805 194806 194807 194808 194809 194810 194811 194812 194901 194902 194903 194904 194905 194906 194907 194908 3.89 5.39 1.2 6.24 -5.83 5.87 4.23 3.93 -3.89 -2.69 -6.44 -10.17 -1.44 -0.01 4.96 1.25 -1.08 -1.67 -4.8 -0.97 5.29 4.14 -1.74 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195105 195106 195107 195108 195109 195110 195111 195112 195201 195202 195203 195204 195205 195206 195207 195208 195209 195210 195211 195212 195301 195302 195303 195304 195305 195306 195307 3.09 3.14 1.82 5.13 1.7 1.48 1.26 3.94 4.31 -5.94 1.36 4.85 4.81 -0.18 2.76 5.54 5.7 1.41 -2.15 4.86 -2.34 -2.62 6.94 4.27 0.7 -2.53 0.57 3.33 1.45 -2.62 4.44 -4.97 3.2 3.83 0.91 -0.76 -2.03 -0.66 5.94 2.93 -0.34 -0.27 -1.43 -2.83 0.52 -1.89 2.4 1.05 1.03 -0.93 2.07 3.36 0.04 -1.41 1.99 -2.12 -2.38 0.51 0.73 0.57 -0.58 -0.84 1.49 1.73 0.09 -0.64 -1.49 -0.01 -1.95 -1.99 0.99 1.9 -0.22 -0.29 -2.25 -0.61 0.79 -2.99 0.48 -1.01 -1.61 -0.4 1.18 1.15 -1.06 -0.71 -1.48 3.58 2.15 -0.19 0.28 -0.07 -1.86 -1.05 0.23 -0.49 -0.91 1.75 0.14 -0.81 -2.77 1.34 0.46 -0.78 13.66 -1.41 -1.11 1.44 3.17 7.23 3.72 -2.83 -4.22 3.28 -1.33 -3.96 2.01 -0.16 0.61 0.25 -0.05 -1.56 1.54 -0.61 2.16 -0.1 0.08 1.23 -0.35 0.03 -1.51 -0.45 0.95 0.18 1.32 -0.08 -0.8 1.53 0.23 -0.47 -0.24 0.09 0.09 0.08 0.09 0.09 0.09 0.1 0.09 0.1 0.1 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mickeygabz (5272)
UC Berkeley
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It’s my second time using SP and the work has been great back to back :) The one and only resource on the Interwebs for the work that needs to be done!

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