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Instructions: The focus of this lab is portfolio theory and the impact of diversification. Use Microsoft Excel to complete this assignment. Submit your Excel file and Word file online in Blackboard for grading. There are up to 5 points possible to Exam 1. Due by Friday, Ianuary.25, 2019 by 11pm. Absolutely, no late work will be accepted. Suppose you have the following information about two securities St Expected Sta Return Deviation 20% 45% 1. Using Microsoft Excel, create a spreadsheet program for calculating the expected return and standard deviation for portfolios consisting of the two stocks. Use the following format. (Hint: You must enter the information for the stocks and the correlations in individual cells in Excel then setup a table similar to the one below. You should have enough rows such that the weight in Stock A increases in increments of.05 until you get to 1.) It will look ing like this in Excel. Be sure to program the formula using the cell references for full credit. Do not code in humbers St | Rho=-0.5 | Rho-0 | Rho= 0.5 Deviations wi ations --| Weight of Stock A 0.0 0.05 0.1 0.15 Return 1.00 2. Plot the standard deviation and expected returns of your portfolios against each other. What do you observe? Comment on the pattern and the potential for obtaining benefits from diversification depending on the correlation of your two assets. Include a discussion about the shape of the graph for each correlation. (i.e. is the line straight or curved) 3. What are the weight combinations of the minimum variance portfolios at the various correlations (i.e. what are the weights invested in Stock A and B for the minimum variance (least risky) portfolio when the correlation is -1, 0.5, 0, 0.5, and 1)? 4. What do you notice about the relationship between the weights in the portfolio and the correlations? That is what happens to your weights in Stock A and B as the correlation changes from -1 to +1? 5. Suppose there exists a large number of assets that are exact clones of asset A, i.e. they have the same expected return and the same standard deviation as stock A. What is the standard deviation of a large, well-diversified portfolio of these securities if the correlation between any pair of the assets is -1-0.5, 0, 0.5, and 1? What do you observe regarding the shape of the graph? (You will have to do this in another spreadsheet. Just repeat Part 2 with the new assets.) You will have to create a new graph. What are your new weight combinations of the minimum variance portfolio? What is the new relationship between the weights in Stock A and B as the correlation changes?

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Stock ahdaro Devlations with COrrelatiohs(uslhg Ezjah EXPEC TED RETUR N Equatio Rho-- SIBLE 1OS Rho 0 Rho-1 0.5 Rho=1 W1 Weight Weight Percent Percent Percent Percent Percent Percent of StockA StockB wy of age(%) lage(%) lage(96) lage(96) lage(96) age(96) 45 45 42 42.38 42.757 43.13 39 39.771 40.528 41.27 36 37.176 38.316 39.423 33 34.59836.125 37.59 30 32.04 33.95835.773 T 29.508 31.82 33.974 24 27.01 29.717 32.198 21 24.556 27.65930.447 18 22.16 25.654 28.726 15 19.843 23.717 27.042 12 17.637 21.866 25.401 915.588 20.125 23.812 6 13.768 18.524 22.286 3 12.278 17.103 20.839 0 11.25 15.9119.486 45 45 45 20 19.6 0.15 0.85 40.5 39 18.8 18.4 36 34.5 17.6 0.65 31.5 30 28.5 16.4 0.45 15.6 0.65 14.8 14.4 21 19.5 0.85 0.15 6 11.048 14.427 17.152 911.906 14.23 16.225 12 13.26914.427 15.498 13.2 12.8 12.4 0.95 0.05 16.5A=Asset 1,Stock B=Asset 2
Return of asset 1=R1=12%
Return of asset 2=R2=20%
Standard deviation of asset 1=S1=15%
Standard deviation of asset 2=S2=45%
Correlation of asset 1 and 2=Corr(1,2) Covariance(1,2)=Corr(1,2)*S1*S2 S1*2=15*45=675
-1 -675
-0.5 -337.5
0 0
0.5 337.5
1 675
w1=Investment in asset 1(A)
w2=Investment in asset 2(B)
Portfolio Return
w1*R1+w2*R2=w1*12+w2*20 ……..Equation (1)
Portfolio Variance=(w1^2)*(S1^2)+(w2^2)*(S2^2)+2*w1*w2*Cov(1,2)=45
Portfolio Variance=(w1^2)*(15^2)+(w2^2)*(45^2)+2*w1*w2*Cov(1,2)
Portfolio Variance=(w1^2)*225+(w2^2)*2025+2*w1*w2*Cov(1,2)……………Equation (2)
Portfolio Standard Deviation=Square root of Variance…..Eq(3)
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