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RUNNING HEAD: - Financial analysis 0 | P a g e
Financial analysis
Module Number
Financial analysis
Module Number
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Financial analysis 1 | P a g e
Executive summary
This report reveals the key implication of the stock exchange and average stock relation
and how they are interlinked with each other. This report divulges the key aspects of the stock
exchange and return provided by the company and industries stock return. However, it has been
found that the stock return of one industry is different than other and factors affecting the
business return in particular industry also differ. The scatter plot and correlation between the two
gathered variables have been given which reflects the key implication of the joint information
given in the investment decisions. Nonetheless, company giving the higher return will be
undertaken for the investment purpose by the investors.
Executive summary
This report reveals the key implication of the stock exchange and average stock relation
and how they are interlinked with each other. This report divulges the key aspects of the stock
exchange and return provided by the company and industries stock return. However, it has been
found that the stock return of one industry is different than other and factors affecting the
business return in particular industry also differ. The scatter plot and correlation between the two
gathered variables have been given which reflects the key implication of the joint information
given in the investment decisions. Nonetheless, company giving the higher return will be
undertaken for the investment purpose by the investors.
Financial analysis 2 | P a g e
Table of Contents
Executive summary.........................................................................................................................1
Introduction......................................................................................................................................3
Identify the variables and their types and scales of measurement...................................................3
Complete descriptive statistics on ‘stock return’ and ‘firm size......................................................3
two bar charts to graphically represent the frequency distribution of stock exchanges and of
industries..........................................................................................................................................5
Tables providing joint information:.................................................................................................6
Charts providing joint information:.................................................................................................7
Scatter plot and correlation analysis:...............................................................................................9
Recommendations to investors in the U.S. stock market:.............................................................11
References......................................................................................................................................12
Appendix........................................................................................................................................13
Table of Contents
Executive summary.........................................................................................................................1
Introduction......................................................................................................................................3
Identify the variables and their types and scales of measurement...................................................3
Complete descriptive statistics on ‘stock return’ and ‘firm size......................................................3
two bar charts to graphically represent the frequency distribution of stock exchanges and of
industries..........................................................................................................................................5
Tables providing joint information:.................................................................................................6
Charts providing joint information:.................................................................................................7
Scatter plot and correlation analysis:...............................................................................................9
Recommendations to investors in the U.S. stock market:.............................................................11
References......................................................................................................................................12
Appendix........................................................................................................................................13
Financial analysis 3 | P a g e
Introduction
With the increasing business complexities, investors before investing their capital needs to assess
which part of investment options needs to be undertaken by the investors for their investment
purpose, the risk and return associated with the investment needs to be assessed. This report
divulges the scatter plot and correlation between the two gathered variables and undertaken
investment decisions which investor needs to assess for the investment decisions.
Identify the variables and their types and scales of measurement
There are several variables such as market beta, hypothesis and selected return based on the
market ups and down. It has been analyzed that there are several types of variables such as
nominal, ordinal, interval and ratio which is used to assess the financial performance and ups and
down related to the market business position of the company (Bendat, & Piersol, 2011).
In the given case return and beta associated with the company and its index is considered to be
the variables of the company. However, the measures in that case could be charts, beta analysis
and joint information decisions undertaken for the investment assessment program (Bekelman,
Li, & Gross, 2013).
Complete descriptive statistics on ‘stock return’ and ‘firm size
When the Statistics of stock return and past return stock has been taken.
SUMMARY OUTPUT
Introduction
With the increasing business complexities, investors before investing their capital needs to assess
which part of investment options needs to be undertaken by the investors for their investment
purpose, the risk and return associated with the investment needs to be assessed. This report
divulges the scatter plot and correlation between the two gathered variables and undertaken
investment decisions which investor needs to assess for the investment decisions.
Identify the variables and their types and scales of measurement
There are several variables such as market beta, hypothesis and selected return based on the
market ups and down. It has been analyzed that there are several types of variables such as
nominal, ordinal, interval and ratio which is used to assess the financial performance and ups and
down related to the market business position of the company (Bendat, & Piersol, 2011).
In the given case return and beta associated with the company and its index is considered to be
the variables of the company. However, the measures in that case could be charts, beta analysis
and joint information decisions undertaken for the investment assessment program (Bekelman,
Li, & Gross, 2013).
Complete descriptive statistics on ‘stock return’ and ‘firm size
When the Statistics of stock return and past return stock has been taken.
SUMMARY OUTPUT
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Financial analysis 4 | P a g e
Regression
Statistics
Multiple R 0.111621
R Square 0.012459
Adjusted R
Square 0.012109
Standard
Error 12.23185
Observatio
ns 2824
ANOVA
df SS MS F
Significan
ce F
Regression 1 5326.9 5326.9
35.60
33 2.72E-09
Residual 2822
422222.
4
149.61
82
Regression
Statistics
Multiple R 0.111621
R Square 0.012459
Adjusted R
Square 0.012109
Standard
Error 12.23185
Observatio
ns 2824
ANOVA
df SS MS F
Significan
ce F
Regression 1 5326.9 5326.9
35.60
33 2.72E-09
Residual 2822
422222.
4
149.61
82
Financial analysis 5 | P a g e
Total 2823
427549.
3
Coefficie
nts
Standar
d Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept -12.4907
0.23017
7
-
54.265
7 0 -12.942
-
12.03
94 -12.942
-
12.039
4
X Variable
1 0.098162
0.01645
1
5.9668
5
2.72E-
09 0.065904
0.130
42
0.0659
04
0.1304
2
(Please excel file attached)
Total 2823
427549.
3
Coefficie
nts
Standar
d Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept -12.4907
0.23017
7
-
54.265
7 0 -12.942
-
12.03
94 -12.942
-
12.039
4
X Variable
1 0.098162
0.01645
1
5.9668
5
2.72E-
09 0.065904
0.130
42
0.0659
04
0.1304
2
(Please excel file attached)
Financial analysis 6 | P a g e
When the Statistics of stock return and firm size has been taken.
SUMMARY
OUTPUT
Regression
Statistics
Multiple R
0.2474
44
R Square
0.0612
29
Adjusted R
Square
0.0142
9
Standard
Error
14.699
94
Observations 22
ANOVA
df SS MS F
Significa
nce F
Regression 1 281.8745
281.8
745
1.304
442
0.26689
3
When the Statistics of stock return and firm size has been taken.
SUMMARY
OUTPUT
Regression
Statistics
Multiple R
0.2474
44
R Square
0.0612
29
Adjusted R
Square
0.0142
9
Standard
Error
14.699
94
Observations 22
ANOVA
df SS MS F
Significa
nce F
Regression 1 281.8745
281.8
745
1.304
442
0.26689
3
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Financial analysis 7 | P a g e
Residual 20 4321.762
216.0
881
Total 21 4603.637
Coeffic
ients
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
-
3.3126
3 3.713869
-
0.891
96
0.383
019 -11.0596
4.4343
62
-
11.0596
4.43436
2
X Variable 1
-
0.0028
4 0.002486
-
1.142
12
0.266
893 -0.00803
0.0023
47
-
0.00803
0.00234
7
two bar charts to graphically represent the frequency distribution of stock exchanges and
of industries.
3 183 363 543 723 903 1083126314431623180319832163234325232703
-100000
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
Stock frequency and distribution of
stock exchange
Axis Title
Residual 20 4321.762
216.0
881
Total 21 4603.637
Coeffic
ients
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
-
3.3126
3 3.713869
-
0.891
96
0.383
019 -11.0596
4.4343
62
-
11.0596
4.43436
2
X Variable 1
-
0.0028
4 0.002486
-
1.142
12
0.266
893 -0.00803
0.0023
47
-
0.00803
0.00234
7
two bar charts to graphically represent the frequency distribution of stock exchanges and
of industries.
3 183 363 543 723 903 1083126314431623180319832163234325232703
-100000
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
Stock frequency and distribution of
stock exchange
Axis Title
Financial analysis 8 | P a g e
3 171 339 507 675 843 10111179134715151683185120192187235525232691
-100000
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
Stock frequency, distribution of stock exchanges
and of industries
Stock return Firm size Past return
Tables providing joint information:
a. Stock exchanges and average stock return:
Exchang
e Name Average return
1 NYSE -12.36809075
2 AMEX -15.34414464
3 NASDAQ -12.25445335
b. Different industries and average stock return:
3 171 339 507 675 843 10111179134715151683185120192187235525232691
-100000
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
Stock frequency, distribution of stock exchanges
and of industries
Stock return Firm size Past return
Tables providing joint information:
a. Stock exchanges and average stock return:
Exchang
e Name Average return
1 NYSE -12.36809075
2 AMEX -15.34414464
3 NASDAQ -12.25445335
b. Different industries and average stock return:
Financial analysis 9 | P a g e
Industry
code Industry name
Average
return
1 Agriculture, Forestry and Fishing -5.588479119
2 Mining -21.02784752
3 Construction -12.93519151
4 Manufacturing -13.00209053
5 Transportation, communications, electric, gas and sanitary service -10.58379599
6 Wholesale Trade -11.69227980
7 Retail Trade -13.80213902
8 Finance, Insurance and Real Estate -10.38312141
9 Services -12.01556899
10 Public Administration -14.40859921
Industry
code Industry name
Average
return
1 Agriculture, Forestry and Fishing -5.588479119
2 Mining -21.02784752
3 Construction -12.93519151
4 Manufacturing -13.00209053
5 Transportation, communications, electric, gas and sanitary service -10.58379599
6 Wholesale Trade -11.69227980
7 Retail Trade -13.80213902
8 Finance, Insurance and Real Estate -10.38312141
9 Services -12.01556899
10 Public Administration -14.40859921
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Financial analysis 10 | P a g e
Charts providing joint information:
NYSE AMEX NASDAQ
-18.00000000
-16.00000000
-14.00000000
-12.00000000
-10.00000000
-8.00000000
-6.00000000
-4.00000000
-2.00000000
0.00000000
Stock exchange and average return
Average return
Agriculture, Forestry and Fishing
Mining
Construction
Manufacturing
Transportation, communications, electric, gas and sanitary service
Wholesale Trade
Retail Trade
Finance, Insurance and Real Estate
Services
Public Administration
-25.00000000
-20.00000000
-15.00000000
-10.00000000
-5.00000000
0.00000000
Industries and average return
Average return
Charts providing joint information:
NYSE AMEX NASDAQ
-18.00000000
-16.00000000
-14.00000000
-12.00000000
-10.00000000
-8.00000000
-6.00000000
-4.00000000
-2.00000000
0.00000000
Stock exchange and average return
Average return
Agriculture, Forestry and Fishing
Mining
Construction
Manufacturing
Transportation, communications, electric, gas and sanitary service
Wholesale Trade
Retail Trade
Finance, Insurance and Real Estate
Services
Public Administration
-25.00000000
-20.00000000
-15.00000000
-10.00000000
-5.00000000
0.00000000
Industries and average return
Average return
Financial analysis 11 | P a g e
Financial analysis 12 | P a g e
Scatter plot and correlation analysis:
a. Stock return and firm size –
Correlation coefficient of stock return and firm size is 0.058392344. For calculation, refer
attached excel sheet (Nowak, 2018).
Scatter plot of stock return and firm size is as follows-
1 10 100 1000 10000 100000 1000000
-10000
0
10000
20000
30000
40000
50000
60000
70000
f(x) = 1.79404161758118E-05 x − 12.6534658675671
R² = 0.00340966587127844
f(x) = 190.055004179696 x + 11664.6218551481
R² = 0.00340966587128144 Stock return and firm size
Stock return
Linear (Stock return)
Firm size
Linear (Firm size)
Scatter plot and correlation analysis:
a. Stock return and firm size –
Correlation coefficient of stock return and firm size is 0.058392344. For calculation, refer
attached excel sheet (Nowak, 2018).
Scatter plot of stock return and firm size is as follows-
1 10 100 1000 10000 100000 1000000
-10000
0
10000
20000
30000
40000
50000
60000
70000
f(x) = 1.79404161758118E-05 x − 12.6534658675671
R² = 0.00340966587127844
f(x) = 190.055004179696 x + 11664.6218551481
R² = 0.00340966587128144 Stock return and firm size
Stock return
Linear (Stock return)
Firm size
Linear (Firm size)
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Financial analysis 13 | P a g e
b. Stock return and past return –
Correlation coefficient of stock return and firm size is 0.111620548. For calculation, refer
attached excel sheet (Chung, Cox, & Mitchell, 2011).
Scatter plot of stock return and past return is as follows-
-100 -50 0 50 100 150 200
-100
-50
0
50
100
150
200
f(x) = 0.126924465018835 x + 1.62484314242898
R² = 0.0124591467535605f(x) = 0.0981619008731765 x − 12.4906965710689
R² = 0.012459146753562
Stock return and past return
Past return
Linear (Past return)
Stock return
Linear (Stock return)
c. Stock return and past trading value –
Correlation coefficient of stock return and firm size is 0.044369817. For calculation, refer
attached excel sheet.
Scatter plot of stock return and past trading value is as follows-
b. Stock return and past return –
Correlation coefficient of stock return and firm size is 0.111620548. For calculation, refer
attached excel sheet (Chung, Cox, & Mitchell, 2011).
Scatter plot of stock return and past return is as follows-
-100 -50 0 50 100 150 200
-100
-50
0
50
100
150
200
f(x) = 0.126924465018835 x + 1.62484314242898
R² = 0.0124591467535605f(x) = 0.0981619008731765 x − 12.4906965710689
R² = 0.012459146753562
Stock return and past return
Past return
Linear (Past return)
Stock return
Linear (Stock return)
c. Stock return and past trading value –
Correlation coefficient of stock return and firm size is 0.044369817. For calculation, refer
attached excel sheet.
Scatter plot of stock return and past trading value is as follows-
Financial analysis 14 | P a g e
1 10 100 1000 10000 100000 1000000
-5000
0
5000
10000
15000
20000
25000
30000 Stock return and past trading value
Stock return
Linear (Stock return)
Past trading volume
Linear (Past trading volume)
Recommendations to investors in the U.S. stock market:
Research findings in the literature related to U.S. stock market emphasis on the less volatility of
market and stability of U.S. economy, further it gives an intuition to investors of stable and
strong stock market with good potential returns. However, the results of calculation and analysis
of stock exchange data, suggests something different; despite being strong and stable economy,
U.S. stock exchange data of various industries have not indicated about providing a volatility
free and positive return (Gajigo, Mutambatsere, & Adjei, 2011). As the analysis of change in
stock return suggests volatility in U.S. stock market; and negative average return of all three
stock exchanges fails to provide an assurance about return. Industry wise average return is also
negative for all the industries, highest loser was mining industry as it faced whopping decline of
21%. Therefore, it is advised that the investing in the stock market should be done by the
investors only when they are more inclined to have higher return with the higher volatility. In
context with the less return, it would be harder for the investors to capture this investment
proposal. However, in context with the Correlation coefficient of stock return and firm size is
0.111620548 which reveals that investing in this firm would give less risk and more return to
investors.
1 10 100 1000 10000 100000 1000000
-5000
0
5000
10000
15000
20000
25000
30000 Stock return and past trading value
Stock return
Linear (Stock return)
Past trading volume
Linear (Past trading volume)
Recommendations to investors in the U.S. stock market:
Research findings in the literature related to U.S. stock market emphasis on the less volatility of
market and stability of U.S. economy, further it gives an intuition to investors of stable and
strong stock market with good potential returns. However, the results of calculation and analysis
of stock exchange data, suggests something different; despite being strong and stable economy,
U.S. stock exchange data of various industries have not indicated about providing a volatility
free and positive return (Gajigo, Mutambatsere, & Adjei, 2011). As the analysis of change in
stock return suggests volatility in U.S. stock market; and negative average return of all three
stock exchanges fails to provide an assurance about return. Industry wise average return is also
negative for all the industries, highest loser was mining industry as it faced whopping decline of
21%. Therefore, it is advised that the investing in the stock market should be done by the
investors only when they are more inclined to have higher return with the higher volatility. In
context with the less return, it would be harder for the investors to capture this investment
proposal. However, in context with the Correlation coefficient of stock return and firm size is
0.111620548 which reveals that investing in this firm would give less risk and more return to
investors.
Financial analysis 15 | P a g e
References
Bekelman, J. E., Li, Y., & Gross, C. P. (2013). Scope and impact of financial conflicts of interest in
biomedical research: a systematic review. Jama, 289(4), 454-465.
Bendat, J. S., & Piersol, A. G. (2011). Random data: analysis and measurement procedures (Vol. 729).
John Wiley & Sons.
Chung, K. H., Cox, R. A., & Mitchell, J. B. (2011). Citation patterns in the finance literature. Financial
Management, 99-118.
Gajigo, O., Mutambatsere, E., & Adjei, E. (2011). Manganese industry analysis: Implications for
project finance. African Development Bank.
Nowak, E. (2018). Finance, investment, and firm value in Germany and the US: A comparative
analysis. Humboldt University SBF, 373.
Powell, J., Jones, M., & Kimberlee, R. (2013). Not asking and not counting: The problem of DAT needs
analysis for drug services for young people. Youth and Policy, 79.
References
Bekelman, J. E., Li, Y., & Gross, C. P. (2013). Scope and impact of financial conflicts of interest in
biomedical research: a systematic review. Jama, 289(4), 454-465.
Bendat, J. S., & Piersol, A. G. (2011). Random data: analysis and measurement procedures (Vol. 729).
John Wiley & Sons.
Chung, K. H., Cox, R. A., & Mitchell, J. B. (2011). Citation patterns in the finance literature. Financial
Management, 99-118.
Gajigo, O., Mutambatsere, E., & Adjei, E. (2011). Manganese industry analysis: Implications for
project finance. African Development Bank.
Nowak, E. (2018). Finance, investment, and firm value in Germany and the US: A comparative
analysis. Humboldt University SBF, 373.
Powell, J., Jones, M., & Kimberlee, R. (2013). Not asking and not counting: The problem of DAT needs
analysis for drug services for young people. Youth and Policy, 79.
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Financial analysis 16 | P a g e
Appendix
When the Statistics of stock return and past return stock has been taken.
SUMMARY OUTPUT
Regression
Statistics
Multiple R 0.111621
R Square 0.012459
Adjusted R
Square 0.012109
Standard
Error 12.23185
Observatio
ns 2824
ANOVA
df SS MS F
Significan
ce F
Appendix
When the Statistics of stock return and past return stock has been taken.
SUMMARY OUTPUT
Regression
Statistics
Multiple R 0.111621
R Square 0.012459
Adjusted R
Square 0.012109
Standard
Error 12.23185
Observatio
ns 2824
ANOVA
df SS MS F
Significan
ce F
Financial analysis 17 | P a g e
Regression 1 5326.9 5326.9
35.60
33 2.72E-09
Residual 2822
422222.
4
149.61
82
Total 2823
427549.
3
Coefficie
nts
Standar
d Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept -12.4907
0.23017
7
-
54.265
7 0 -12.942
-
12.03
94 -12.942
-
12.039
4
X Variable
1 0.098162
0.01645
1
5.9668
5
2.72E-
09 0.065904
0.130
42
0.0659
04
0.1304
2
Regression 1 5326.9 5326.9
35.60
33 2.72E-09
Residual 2822
422222.
4
149.61
82
Total 2823
427549.
3
Coefficie
nts
Standar
d Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept -12.4907
0.23017
7
-
54.265
7 0 -12.942
-
12.03
94 -12.942
-
12.039
4
X Variable
1 0.098162
0.01645
1
5.9668
5
2.72E-
09 0.065904
0.130
42
0.0659
04
0.1304
2
Financial analysis 18 | P a g e
(Please excel file attached)
When the Statistics of stock return and firm size has been taken.
SUMMARY
OUTPUT
Regression
Statistics
Multiple R
0.2474
44
R Square
0.0612
29
(Please excel file attached)
When the Statistics of stock return and firm size has been taken.
SUMMARY
OUTPUT
Regression
Statistics
Multiple R
0.2474
44
R Square
0.0612
29
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Financial analysis 19 | P a g e
Adjusted R
Square
0.0142
9
Standard
Error
14.699
94
Observations 22
ANOVA
df SS MS F
Significa
nce F
Regression 1 281.8745
281.8
745
1.304
442
0.26689
3
Residual 20 4321.762
216.0
881
Total 21 4603.637
Coeffic
ients
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
-
3.3126
3 3.713869
-
0.891
96
0.383
019 -11.0596
4.4343
62
-
11.0596
4.43436
2
Adjusted R
Square
0.0142
9
Standard
Error
14.699
94
Observations 22
ANOVA
df SS MS F
Significa
nce F
Regression 1 281.8745
281.8
745
1.304
442
0.26689
3
Residual 20 4321.762
216.0
881
Total 21 4603.637
Coeffic
ients
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
-
3.3126
3 3.713869
-
0.891
96
0.383
019 -11.0596
4.4343
62
-
11.0596
4.43436
2
Financial analysis 20 | P a g e
X Variable 1
-
0.0028
4 0.002486
-
1.142
12
0.266
893 -0.00803
0.0023
47
-
0.00803
0.00234
7
X Variable 1
-
0.0028
4 0.002486
-
1.142
12
0.266
893 -0.00803
0.0023
47
-
0.00803
0.00234
7
1 out of 21
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