Essentials of Investments (The Mcgraw-hill/Irwin Series in Finance, Insurance, and Real Estate)
10th Edition
ISBN: 9780077835422
Author: Zvi Bodie Professor, Alex Kane, Alan J. Marcus Professor
Publisher: McGraw-Hill Education
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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.
Expert Solution & Answer
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.
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Chapter 7 Solutions
Essentials of Investments (The Mcgraw-hill/Irwin Series in Finance, Insurance, and Real Estate)
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