It can be conjectured that the annual return a security and the market return are related by the following regression model y=mx+b+ε Where y is the annual return of the security, x is the annual return of the market, b is the intercept, Ɛ is the normally distributed noise, and Return = value at end of the year + received dividends during the year - value at the beginning of the year. Test this model by retrieving annual data on a security of your choice. Choose a financial index such as S&P 500 as the indicator of the market, and retrieve the data. Use the most recent 20 years as the time span of the data. Perform regression analysis and make sure to include the hypothesis in your study. Provide your results and write your conclusions. Include all relevant information and conclusions, significances, the final regression model, coefficient of determination, graph of the regression line accompanied in the scatterplot, extent of residuals, and normality of residuals. Does the model seem to be valid according to your study? If so, is the influence positive or adverse? If you conclude influence, then your regression model indicates outperformance or underperformance of the market? Explain all your work in detail.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
It can be conjectured that the annual return a security and the market return are related by the following regression model
y=mx+b+ε
Where y is the annual return of the security, x is the annual return of the market, b is the intercept, Ɛ is the
Return = value at end of the year + received dividends during the year - value at the beginning of the year.
Test this model by retrieving annual data on a security of your choice. Choose a financial index such as S&P 500 as the indicator of the market, and retrieve the data. Use the most recent 20 years as the time span of the data. Perform
![Average
Annual %
Year
Stock Price
Year Open
Year High
Year Low
Year Close
Change
2020
327.1864
300.3500
497.4800
224.3700
497.4800
69.41%
2019
208.2559
157.9200
293.6500
142.1900
293.6500
86.16%
2018
189.0534
172.2600
232.0700
146.8300
157.7400
-6.79%
2017
150.5511
116.1500
176.4200
116.0200
169.2300
46.11%
2016
104.6040
105.3500
118.2500
90.3400
115.8200
10.03%
2015
120.0385
109.3300
133.0000
103.1200
105.2600
-4.64%
2014
92.2646
79.0186
119.0000
71.3974
110.3800
37.72%
2013
67.5193
78.4329
81.4414
55.7900
80.1457
5.42%
2012
82.2928
58.7471
100.3000
58.7471
76.0247
31.40%
2011
52.0006
47.0814
60.3200
45.0457
57.8571
25.56%
2010
37.1203
30.5729
46.4957
27.4357
46.0800
53.07%
2009
20.9736
12.9643
30.2343
11.1714
30.1046
146.90%
2008
20.2827
27.8343
27.8471
11.4986
12.1929
-56.91%
2007
18.3249
11.9714
28.5471
11.8957
28.2971
133.47%
2006
10.1160
10.6786
13.1157
7.2386
12.1200
18.01%
2005
6.6680
4.5207
10.7114
4.5207
10.2700
123.26%
2004
2.5376
1.5200
4.8886
1.5200
4.6000
201.36%
2003
1.3245
1.0571
1.7729
0.9371
1.5264
49.12%
2002
1.3671
1.6643
1.8650
0.9714
1.0236
-34.56%
2001
1.4442
1.0629
1.8993
1.0629
1.5643
47.17%
2000
3.2651
3.9979
5.1496
1.0000
1.0629
-71.05%](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4f8c0254-ec8b-40b6-90de-18b633187918%2F347c7718-febb-4fa7-8af0-02b014eb0a4d%2Flmzr75_processed.png&w=3840&q=75)
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