eBook Check My Work Suppose you are going to invest equal amounts in three stocks. The annual return from each stock is normally distributed with mean 0.01 (1%) and standard deviation 0.06. The annual return on your portfolio, the output variable of interest, is the average of the three stock returns. Run @RISK, using 1000 iterations, on each of the following scenarios. a. The three stock returns are highly correlated. The correlation between each pair is 0.9. If necessary, round your answers to three decimal digits. What is the mean portfolio return of the simulation? 0.01 What is the standard deviation of the simulation? 0.06 b. The three stock returns are practically independent. The correlation between each pair is 0.1. If necessary, round your answers to three decimal digits. What is the mean portfolio return of the simulation? 0.01 What is the standard deviation of the simulation? 0.06 c. The first two stocks are moderately correlated. The correlation between their returns is 0.4. The third stock's return is negatively correlated with the other two. The correlation between its return and each of the first two is -0.8. If necessary, round your answers to three decimal digits. 0.01 What is the mean portfolio return of the simulation? What is the standard deviation of the simulation? 0.06 d. Compare the portfolio distributions from @RISK for these three scenarios. What do you conclude? The mean portfolio return is the same in each case, but the standard deviation is larger as the stocks are more positively correlated. e. You might think of a fourth scenario, where the correlation between each pair of returns is a large negative number such as -0.8. But explain intuitively why this makes no sense. If two stocks are negatively correlated to each other, then the third stock cannot Try to run the simulation with these negative correlations and see what happens. be negatively correlated with both If you try to run @RISK with these correlations, you will get a message that this is an invalid correlation matrix. of them. Hide Feedback