Reference no: EM131981731

Assignment: Details

Which stock should I invest in?

(Topics included: Statistical Inference, Simple Regression Analysis)

You have been asked by your client to flickr photo shared by ota_photos under a Creative Commons ( BY-SA ) license recommend which of two available stocks will perform better over time, relative to risk. You will need to compare risk and return relationship of the two stocks over time and present your findings as a formal written report (detailing your calculations and findings).

The goal of this assignment is to

1. give you practice in performing the different types of quantitative analysis tasks often undertaken by Business graduates,
2. provide you with feedback on your ability to carry out such tasks, and
3. learn how and when to use different quantitative techniques covered in the last six (6) modules of the subject.

Now perform the following tasks.

Task A: Downloading the data

Download the data for S&P 500 index, Boeing Stock Price, General Dynamics Corp. Stock Price, and US TN (10 Year), using the links provided above and choosing Monthly Historical Data for all variables covering the period related to a group your Student ID belongs to.

Data Group	Data Period		Students with ID Between (inclusive)
	Start Date	End Date
Group 01	01/01/2013	01/01/2018	17520962	19131650
Group 02	01/07/2012	01/07/2017	19138221	19243202
Group 03	01/01/2012	01/01/2017	19244070	19545727
Group 04	01/07/2011	01/07/2016	19545883	19573974
Group 05	01/01/2011	01/01/2016	19574258	19598885
Group 06	01/07/2010	01/07/2015	19598945	19957077

Example: Suppose a student's ID is 19560001. This ID falls in an interval corresponding to group 04 and therefore, this student would download monthly data covering the period 01/07/2011 to 01/07/2016.

Task B: Perform the following.

1. Calculate returns for these three series in Excel or any software of your choice using the transformation: rt = 100*ln(Pt / Pt-1) and perform the Jarque-Berra test of normally distributed returns for each of Boeing and GD. What do you infer about the distribution of the two stock returns series? Describe also the risk and average return relationship in each of the two stocks.

Hints:

We have performed a similar task in Workshop 01.
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. But you would not put a percentage sign in your data. For example, returns for two periods are

0.35% and 0.41% but we would use 0.35 and 0.41 after omitting % sign in our excel worksheet.

2. Test a hypothesis that the average return on GD stock is different from 2.8%. Which test statistic would you choose to perform this hypothesis test and why? Also, specify the distribution of the test statistic under the null hypothesis.

3. Before investing in one of the two stocks, you first want to compare risk associated with each of the two stocks. Perform an appropriate hypothesis test using 5% significance level and interpret your results.

4. Besides, you want to determine whether both stocks have same population average return. Perform an appropriate hypothesis test using information in your sample of 60 observations on returns. Report your findings and also mention which stock will you prefer and why?

5. Compute excess return on your preferred stock as yt = rt - rf,t and excess market return as xt = rM,t - rf,t and perform the following tasks.

a. Estimate the CAPM using linear regression by regressing the excess return on your preferred stock (yt) on excess market return (xt) and properly report your regression results.

b. Interpret the estimated CAPM beta-coeficient in terms of the stock's riskiness in comparison with the market.

c. Interpret the value of R2.

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

6. 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 test a hypothesis)

7. One of the assumptions of ordinary least squares (OLS) method is; normally distributed error term in the model. Perform an appropriate hypothesis test to determine whether it is plausible to assume normally distributed errors.

Analyse Data & Submit Report

Prepare your written report in two Parts:

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.