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S3odz S3odz
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7 years ago
Suppose you are going to invest equal amounts in three stocks. The annual return from each stock is normally distributed with a mean of 0.01 (1) and a standard deviation of 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 scenarios described in the questions below, and report few results from the summary report sheets.
 

(A) The three stock returns are highly correlated. The correlation between each pair is 0.9
 
   (B) The three stock returns are practically independent. The correlation between each pair is 0.1
 
   (C) The first two stocks are moderately correlated. The correlation between their returns is 0.4. The third stocks return is negatively correlated with the other two. The correlation between its return and each of the first two is -0.8.


   
 

(D) Compare the portfolio distributions from RISK for the three scenarios in (A), (B) and (C). What do you conclude?
 
   (E) You might think of a fourth scenario, where the correlation between each pair of returns is a large negative number such as -0.80. But explain intuitively why this makes no sense. Try running a simulation with these negative correlations to see what happens.
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#1
7 years ago
(A)

(B)

(C)

(D) The mean portfolio return is the same in each case, but the standard deviation is larger as the stocks are more positively correlated. When the stocks are closer to being independent or are negatively correlated, you get to diversify and get less risk (variance).
(E) The three stocks can't all be going in the opposite direction from each other. When we try to run RISK with these correlations, we get a message that this is an invalid correlation matrix.
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