3.) Assume we have month end price data for 12 months for two financial assets (Asset A and Asset B, with no intermediate cash flows) as follows: Month 0 1 2 3 4 5 6 7 8 9 10 11 12 Asset Prices Asset A Asset B 25.00 45.00 24.12 44.85 23.37 46.88 24.75 45.25 26.62 50.87 26.50 58.50 28.00 57.25 28.88 62.75 29.75 65.50 31.38 74.38 36.25 78.50 37.13 78.00 36.88 78.12 a.) Using Excel, calculate the continuously compounded monthly price return on each asset as well as the mean of those returns. If you are using Jupyter Notebook, make sure your code is well commented and has proper markdown. Note that in general, the continuously compounded return equals r. = ln (P/P-1). b.) Calculate the monthly variance and standard deviation for each asset, assuming population mean and variance in your calculations. Assume that the return data calculated in a.) represents the distribution of returns for the coming month., so use your answer in a.) as E() in your calculations. c.) Calculate the covariance and correlation coefficient for Assets A and B. Note that the covariance is defined as: Cov(raire) = tre E (1.)] [ree E(r)] t With M equal to the number of observations, and the correlation coefficient is: PAB = Cov(TAT) d.) How would you interpret the relationship between price changes in A and B based upon the latter result