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1. 1.Create the line charts for each of S&P, Boeing and IBM series using Close prices against time in Excel and comment on your observations (focusing on different features a time series can exhibit).
2. 2a. Calculate returns for these three series in Excel using the transformation: rt = 100 ln[Pt/Pt-1]

Hints:

• If there are say “n+1” observations on prices, then the return series would have “n” observations.
• These numbers would represent percentages after multiplication with 100 in the formula above. However, you would not put a percentage sign in your data. For example, returns for two periods are 0.35% and 0.41% but we omit % sign in our excel worksheet and use 0.35 and 0.41.

b. Obtain the summary statistics for returns series in your sample and briefly discuss the risk and average return relationship in each stock. Which stock (Boeing or IBM) is relatively riskier than the other?

c. Perform the Jarque-Berra test of normally distributed returns for each of Boeing and IBM. Discuss your findings and also explain why do you test normality test.

3. 3.Test the hypothesis that average return on Boeing stock is at least 3%. Which test statistic would you use to perform this hypothesis test and why? Also, specify the distribution of the test statistic under the null.
4. 4.Before investing in one of the two stocks, you first want to compare risk associated to each of the two stocks. Perform any appropriate hypothesis test using 5% significance level and interpret your results.
5. 5.You further want to determine whether both stocks have same population average return. Perform an appropriate hypothesis test using information in your sample of 65 observations on returns and report your findings. Also, which stock will you prefer and why?
6. 6.Compute excess return on your preferred stock as yt = rt – rf,t and excess market return as xt = rM,t – rf,t (that is, you subtract the 10-year T-Bill rate from return on your preferred stock and the market return that is the return on S&P 500).
7. 7a. Estimate the CAPM using linear regression where the dependent variable is excess return on your preferred stock while the independent variable is excess market return (computed as return on S&P 500 minus the risk fee rate) and report your results.
b. Interpret the estimated coefficients in relation to the profitability of the Stock and its riskiness in comparison with the market.
c. Interpret the value of R2.

d. Interpret 95% confidence interval for the slope coefficient.

8. 8.Using the confidence interval approach to hypothesis testing, perform the hypothesis test to determine whether your preferred stock is a neutral stock. (Note: You would not be given any marks if you do not use CI approach to hypothesis testing)
9. 9.One of the assumptions of ordinary least squares (OLS) method is; normally distributed error term in the model. Verify that the error term follows normal distribution using any appropriate test.

### Analyse Data & Submit Report

Your written report must include: 1500 words

Part A: Calculations

• Set out all your calculations for each of the tasks (listed above) using Data Analysis Tool in Excel. Present your results in graphs and charts as appropriate

Part B: Interpretation

• Explain what your results mean, in language that your client can understand. For example, what conclusions can you draw from each of your findings?
• Your written report must be no more than TWELVE (12) pages in total, including all appendices, graphs, tables and written answers. Answer the questions directly. Do not present unnecessary graphs or numerical measures, undertake inappropriate tests or discuss irrelevant matters.

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