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Hello, I am looking for someone to write an article on Risk Assessment of Strident Marks. It needs to be at least 500 words.
Hello, I am looking for someone to write an article on Risk Assessment of Strident Marks. It needs to be at least 500 words. Risk Assessment of Strident Marks July 25, 2006 The risk assessment of Strident Marks is completed using the Capital Asset Pricing Model. This model is based on a regression analysis function performed in Microsoft Excel. Primarily, the regr4ession between Stock Total Return and Stock Excess Return is conducted. Market Total Return and Market Excess Return follow this. Every stock in the market has a certain return. This return is assumed to have a normal distribution. This means that the return can be described by two terms. The first term is the mean (expected return) and the second is the variance of returns. This also computes a covariance of returns between any the stocks and the market value where they have positive covariance, and those that move in opposite directions will have negative covariance. The expected return and variance of several stocks, a portfolio of these stocks that has a desired variance (risk) with a certain expected return. The expected return is the measurement of investment risk, what variances can be expected by the amount of investment. CAPM formula. The CAPM formula is:
Expected Security Return = Riskless Return + Beta x (Expected Market Risk Premium)
or:
r = Rf + Beta x (RM - Rf)
where:
- r is the expected return rate on a security.
Rf is the rate of a "risk-free" investment, i.e. cash.
RM is the return rate of the appropriate asset class.
(Bennings 2006)
Beta is the overall risk in investing in a large market, like the New York Stock Exchange Beta is the R-squared statistic found in the regression analysis. The Beta of a Strident Marks is risk compared to the Beta (Risk) of the overall market. Beta indicates the volatility of the security, relative to the asset class (Frontline Systems, Inc. 2006).
The regression analysis of Stock Total Return and Stock Excess Return yields the following:
Regression Statistics
Multiple R
0.066948141
R Square
0.004482054
Adjusted R Square
-0.012682049
Standard Error
1.928341146
Observations
60
By the above analysis, the residual r shows that there is a risk of expected loss based on the predictor Y (percentage of return).
Secondly, the Market regression analysis of Market Total Return and Market Excess Return yields the following:
Regression Statistics
Multiple R
1
R Square
1
Adjusted R Square
1
Standard Error
8.27025E-16
Observations
60
This can further be shown by the prediction of Y (return) based on the Residual (Risk) for both Market and Stock as shown:
Observation
Predicted Y Market
Residuals Market
Predicted Y Stock
Residuals Stock
1
0.15
-4.718E-16
0.27633392
-0.1063339
2
0.165
8.6042E-16
0.17620434
0.00379566
3
0.17
1.3323E-15
0.12613955
0.05886045
4
0.165
8.6042E-16
0.22626913
-0.0512691
5
0.16
4.1633E-16
0.27633392
-0.1063339
6
0.168
1.138E-15
0.32639871
-0.1613987
7
0.16
4.1633E-16
0.27633392
-0.1063339
8
0.153
-2.22E-16
0.3764635
-0.2164635
9
0.145
-9.437E-16
0.42652829
-0.2715283
10
0.153
-2.22E-16
0.3764635
-0.2164635
11
0.16
4.1633E-16
0.27633392
-0.1063339
12
0.161
4.996E-16
0.26632096
-0.095321
13
0.169
1.2212E-15
0.16619138
0.01480862
14
0.176
1.8319E-15
0.11612659
0.06987341
15
0.169
1.2212E-15
0.21625617
-0.0402562
16
0.161
4.996E-16
0.26632096
-0.095321
17
0.169
1.2212E-15
0.31638575
-0.1503858
18
0.161
4.996E-16
0.26632096
-0.095321
19
0.154
-1.388E-16
0.36645054
-0.2054505
20
0.146
-8.604E-16
0.41651533
-0.2605153
21
0.154
-1.388E-16
0.36645054
-0.2054505
22
0.161
4.996E-16
0.26632096
-0.095321
23
0.15
-4.718E-16
0.47659308
-0.3265931
24
0.158
2.2204E-16
0.3764635
-0.2164635
25
0.165
8.6042E-16
0.32639871
-0.1613987
26
0.158
2.2204E-16
0.42652829
-0.2715283
27
0.15
-4.718E-16
0.47659308
-0.3265931
28
0.158
2.2204E-16
0.52665787
-0.3816579
29
0.15
-4.718E-16
0.47659308
-0.3265931
30
0.143
-1.11E-15
0.57672267
-0.4367227
31
0.135
-1.804E-15
0.62678746
-0.4917875
32
0.143
-1.11E-15
0.57672267
-0.4367227
33
0.15
-4.718E-16
0.47659308
-0.3265931
34
0.15
-4.718E-16
0.47659308
-0.3265931
35
0.158
2.2204E-16
0.3764635
-0.2164635
36
0.165
8.6042E-16
0.32639871
-0.1613987
37
0.158
2.2204E-16
0.42652829
-0.2715283
38
0.15
-4.718E-16
0.47659308
-0.3265931
39
0.158
2.2204E-16
0.52665787
-0.3826579
40
0.15
-4.718E-16
0.47659308
-0.3265931
41
0.143
-1.11E-15
0.57672267
-0.4367227
42
0.135
-1.804E-15
0.62678746
-0.4917875
43
0.143
-1.11E-15
0.57672267
-0.4367227
44
0.15
-4.718E-16
0.47659308
-0.3265931
45
0.15
-4.718E-16
0.47659308
-0.3265931
46
0.158
2.2204E-16
0.3764635
-0.2164635
47
0.165
8.6042E-16
0.32639871
-0.1613987
48
0.158
2.2204E-16
0.42652829
-0.2715283
49
0.15
-4.718E-16
0.47659308
-0.3265931
50
0.158
2.2204E-16
0.52665787
-0.3816579
51
0.15
-4.718E-16
0.47659308
14.5234069
52
0.143
-1.11E-15
0.57672267
-0.4367227
53
0.135
-1.804E-15
0.62678746
-0.4917875
54
0.143
-1.11E-15
0.57672267
-0.4367227
55
0.15
-4.718E-16
0.47659308
-0.3265931
56
0.15
-4.718E-16
0.47659308
-0.3265931
57
0.158
2.2204E-16
0.3764635
-0.2164635
58
0.165
8.6042E-16
0.32639871
-0.1613987
59
0.158
2.2204E-16
0.42652829
-0.2715283
60
0.15
-4.718E-16
0.47659308
-0.3265931
In conclusion, the Beta statistic defined by R-Square is positive 1 in the Market analysis, and 0.004 in the Stock analysis, it can be assumed, provided that the stock and market follow a normal distribution, that the stock holds a 40% greater risk than that market
References
Bennings, Simon (2006) Principles of Finance with Excel: Includes CD (Hardcover)
Oxford University Press, USA
Frontline Systems, Inc. (2006) Optimization Solutions with the Microsoft Excel Solver Retrieved July 25, 2006 from www.solver.
