Each row of the data matrix S = stocks is a statistically normalized vector. Therefore, the...
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Each row of the data matrix S = stocks is a statistically normalized vector. Therefore, the sample 5x5 covariance matrix Cov(S) can be computed as follows: Cov(S) = SST N-1 where N is the length of each stock data. Can you also find sample correlation matrix, Cor(S)? Explain how? Now examine the Cor(S) matrix. What do you see in diagonal elements? Why? Compare the estimated Correlation value between stocks 1 and 2 in the previous section with the element at (1,2) or (2,1) of the Cor(S) matrix. Are they identical? Why not? Which one is a better estimate for the cross correlation? Why? According to the Cor(S) matrix, which pair of stocks have the highest correlation. Is Cor(S) and Cxy matrices are identical? If not, which one do you think is a better estimate of the cross- correlation? Finally, how can you use the "stock correlation" information for investment (to reduce the risks -OR- maximize the profits) and to become a millionaire? Briefly discuss. Each row of the data matrix S = stocks is a statistically normalized vector. Therefore, the sample 5x5 covariance matrix Cov(S) can be computed as follows: Cov(S) = SST N-1 where N is the length of each stock data. Can you also find sample correlation matrix, Cor(S)? Explain how? Now examine the Cor(S) matrix. What do you see in diagonal elements? Why? Compare the estimated Correlation value between stocks 1 and 2 in the previous section with the element at (1,2) or (2,1) of the Cor(S) matrix. Are they identical? Why not? Which one is a better estimate for the cross correlation? Why? According to the Cor(S) matrix, which pair of stocks have the highest correlation. Is Cor(S) and Cxy matrices are identical? If not, which one do you think is a better estimate of the cross- correlation? Finally, how can you use the "stock correlation" information for investment (to reduce the risks -OR- maximize the profits) and to become a millionaire? Briefly discuss.
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To find the sample correlation matrix CorS we can use the following formula CorS CovS where CovS is the sample covariance matrix and and are the stand... View the full answer
Related Book For
Probability and Random Processes With Applications to Signal Processing and Communications
ISBN: 978-0123869814
2nd edition
Authors: Scott Miller, Donald Childers
Posted Date:
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