Lab021011A - The sample data given below are daily stock...

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The sample data given below are daily stock returns (%) of three companies. Please do the fo 1. Compute the mean and variance for every single stock in the sample, as well as the covaria (MS-Nike, Coca_cola-Nike and Coca_cola-MS). 2. Consider the following two portfolios which are linear combination of different stocks: Nike MS Coca_Cola Portfolio A 35% 65% Portfolio B 65% 35% Compute the expected return and uncertainty (variance) of both portfolios. 3. Which portfolio would you choose to invest when you take into account both profitability and 4.Suppose the returns of these three stocks are independent with each other, then please red 5. Comparing your answers in 3 and 4, what do you think contribute to the change? Nike MS Coca_Cola Answers: -0.3 0.59 0.22 1. Nike 0.06 0.45 0.06 Mean 0.02 0.4 0 0.13 -0.18 -0.55 -0.1 Population Covariance 0.31 -0.36 -0.05 Nike 0.06 0.37 0.18 Nike 0.1 0.52 0.5 0.31 MS -0.01 0.36 0.25 -0.36 Coca_Cola 0 0 0.01 0.23 -0.04 -0.09 0.48 0.53 0.14 -0.09 2. A = 35%*Nike + 65%* -0.18 -0.6 0.09 E(A) = .35*E(Nike) + .6 -0.11 -0.38 -0.22 Var(A) = .35^2*Var(Nik -0.34 0.52 -0.01 -0.02 0.06 0.01 B = 65%*MS + 35%*C 0.5 0.02 -0.03 E(B) = .65*E(MS) + .3 -0.09 0.27 -0.36 Var(B) = 65%^2*Var(M -0.51 -0.13 0.14 -0.16 0.23 -0.11 In Summary, 0.16 -0.25 -0.12 0.51 0.72 0.14 -0.37 0.05 0.04 -0.38 0.42 0.29 0.25 -0.87 0.4 3. Portfolio A will be chos 0.38 -0.6 0.19 -0.11 1 0.13
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0.23 0.31 -0.12 4. The expected return w 0.25 -0.12 0.35 Var(A) = 35%^2*Var(N 0.24 0.35 -0.04 Var(B) = 65%^2*Var(M 0.01 -0.12 0.13 -0.47 -0.15 -0.37 In Summary, 0.6 -0.02 -0.58 0.45 -0.78 -0.16 -0.28 0.39 0.39 Conclusion: to maximi 0.23 -0.47 -0.41 to minimiz 0.03 -0.81 -0.04 -0.53 0.14 0.01 5. The negative covarian -0.47 0.03 -0.34 thus decreases the ris 0.55 -0.39 0.17 On the other hand, th 0.08 -0.03 0.06 variance of portfolio B -0.33 0.47 0.29 Conclusion: as an inve 0.15 -0.28 -0.05 negatively -0.2 0.76 0.01 -0.34 -0.06 -0.15 -0.13 0.76 0.38 0.2 -0.37 -0.02 -0.43 -0.24 -0.3 0.11 0.23 -0.3 0.12 0.89 0.29 0.48 0.11 0.27 0.07 0.21 -0.22 -0.4 -0.03 0.16 -0.28 0.38 -0.05 0.37
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