Chapter 7, Problem 2WM

Summary Introduction

In this problem we have to get the data from yahoo finance for Alcoa and S&P 500 for 60 months and calculate their returns by using this formula:

Returns = ln(Return in current year/return in previous year)

Here ln stands for natural logarithm.

Explanation of Solution

The data is shown below:

Date	Returns Alcoa	Returns S&P
12/1/2013	0	0
1/1/2014	0	0
2/1/2014	0.019785587	0.042213375
3/1/2014	0.094520691	0.006908249
4/1/2014	0.045565745	0.006181643
5/1/2014	0.010340052	0.020812196
6/1/2014	0.09213958	0.018878997
7/1/2014	0.09598186	-0.015194687
8/1/2014	0.013333413	0.036963644
9/1/2014	-0.029980428	-0.015635436
10/1/2014	0.040797065	0.022936399
11/1/2014	0.031133233	0.024237474
12/1/2014	-0.088938172	-0.004197385
1/1/2015	-0.008906032	-0.031532779
2/1/2015	-0.056519624	0.053438876
3/1/2015	-0.133367024	-0.017549197
4/1/2015	0.037969704	0.008484722
5/1/2015	-0.071017427	0.01043673
6/1/2015	-0.112097041	-0.021235559
7/1/2015	-0.121939527	0.019549683
8/1/2015	-0.043485446	-0.064624731
9/1/2015	0.025067099	-0.026798731
10/1/2015	-0.078577301	0.079719379
11/1/2015	0.047029033	0.000504742
12/1/2015	0.056257819	-0.017685659
1/1/2016	-0.302996218	-0.052067617
2/1/2016	0.202912827	-0.004136906
3/1/2016	0.074574737	0.06390499
4/1/2016	0.153553957	0.002695762
5/1/2016	-0.18644828	0.015208367
6/1/2016	0.002902807	0.000910506
7/1/2016	0.135955619	0.034990433
8/1/2016	-0.052185714	-0.001219987
9/1/2016	0.008845955	-0.001235213
10/1/2016	-0.12794767	-0.019616837
11/1/2016	0.301002453	0.033603545
12/1/2016	-0.027282474	0.018037111
1/1/2017	0.260883907	0.017726315
2/1/2017	-0.052376863	0.036523001
3/1/2017	-0.005508	-0.000389273
4/1/2017	-0.019668973	0.009050132
5/1/2017	-0.023699955	0.011509759
6/1/2017	-0.008842777	0.004802226
7/1/2017	0.108723913	0.019164018
8/1/2017	0.186889829	0.000546284
9/1/2017	0.060570954	0.019119039
10/1/2017	0.024577509	0.02194556
11/1/2017	-0.121820059	0.003713141
12/1/2017	0.241786656	0.033766015
1/1/2018	-0.034945458	0.054657399
2/1/2018	-0.145632637	-0.039726108
3/1/2018	-0.00022244	-0.027252497
4/1/2018	0.129966368	0.002715086
5/1/2018	-0.06308127	0.021378191
6/1/2018	-0.025067115	0.004830749
7/1/2018	-0.080131612	0.035387951
8/1/2018	0.031842536	0.029814315
9/1/2018	-0.100472256	0.004285093
10/1/2018	-0.143767471	-0.071929346
11/1/2018	-0.095281689	0.017701752
12/1/2018	-0.098711084	-0.047137951

For First half of the data that is for 30 months, we run the regression between Alcoa and S&P to get this as an output.

Regression equation for the first 30 months is

Y = 0.6203X − 0.0098

From this equation the

Beta = slope of regression line = 0.6203

Alpha = intercept of regression line = 0.0098

For next half of the data that is for 30 months, we run the regression between Alcoa and S&P to get this as an output.

Regression equation for the first 30 months is

Y = 1.9944X − 0.0058

From this equation the

Beta = slope of regression line = 0.1.9944

Alpha = intercept of regression line = 0.0058

Conclusion

From this we can interpret that the for the first 30 months beta is quite lower as compared to the next 30 months. Also Alpha increased from negative 0.0098 to negative 0.0058 for the last 30 months meaning that the stock became more volatile and riskier and was giving more returns.