# Finance and Capital Budgeting Models

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FinanceTest PrepStatistics and ProbabilityPolitical Science
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RUNNING Head: Finance and capital budgeting models
1 | P a g e
Name of the Student
University Name-
Topic-
Finance and capital budgeting models 2 | P a g e
Part-A.........................................................................................................................................3
Minimum Variance portfolio.................................................................................................6
Beta Computation of the Woolworth.................................................................................6
Beta Calculation of the BHP....................................................................................................34
Security Market line.................................................................................................................35
Portfolio risk Using SIM......................................................................................................37
Part-2........................................................................................................................................38
Modern portfolio theory...........................................................................................................38
Capital Asset Pricing Model....................................................................................................39
CAPM and multi-factor models...............................................................................................42
Fama and French three factor model....................................................................................43
References................................................................................................................................45
Finance and capital budgeting models 3 | P a g e
Part-A
b
) Variance and standards deviation computation
Variance analysis 0.001854774
Standard Deviation 0.043067085
C
)
Calculate the Arithmetic Average and Geometric Average returns for the
company
Arithmetic Average -0.010153002
Geometric Average Return .25
D) Computation of the gain or lose based on the last market price of the
share
Invested amount \$ 50,000.00
Share price at the beginning 21.582048
Total shares purchased 2316.740283
Total cost of shares \$ 50,000.00
Total cost of the shares \$ 50,060.00
Total revenue 61839.81242
Profit earned from sales of Shares \$ 11,779.81
Computation of the Parametric VaR
Parametric VaR
-
1268.86 Please See the tab Attached for Parametric VaR)
Express the VaR calculated in (a) as Dollar VaR and compare the VaR for both stocks
Variance Calculation for BHP and
AUD \$ to USD\$
0.00
035
Variance Calculation for Woolworth
Company and AUD \$ to USD\$
0.42498
9772
Finance and capital budgeting models 4 | P a g e
Express the VaR calculated in (a) as DollarVaR and compare the VaR for both stocks
Correlation and Covariance Calculation for BHP 2.2013999E-05
Efficient frontline
Variance Covariance Matrix (of asset returns)
1 2 3 4 5
1 2.2 0.9 -0.3 0.65 -0.42
2 0.9 1.5 -0.39 0.2 0.47
3 -0.3 -0.39 1.8 0.8 0.27
4 0.65 0.2 0.8 1.5 -0.5
5 -0.42 0.47 0.27 -0.5 1.7
ER 8.5 18.3 12.7 10.8 9.5
Correlation Matrix (of asset returns)
1 2 3 4 5
1 1 0.4954 -0.1508 0.3578 -0.2172
Finance and capital budgeting models 5 | P a g e
2 0.4954 1 -0.2373 0.1333 0.2943
3 -0.1508 -0.2373 1 0.4869 0.1543
4 0.3578 0.1333 0.4869 1 -0.3131
5 -0.2172 0.2943 0.1543 -0.3131 1
Determining The Portfolio Weights for Two Portfolios on the
Efficient Frontier
ONES Return BHP Woolworth w1 w2
1 8.5 0.3902 -1.3839 0.1774 -0.0576
1 18.3 0.2073 16.1736 0.0942 0.6730
1 12.7 0.3091 10.6532 0.1406 0.4433
1 10.8 0.5519 -0.3817 0.2510 -0.0159
1 9.5 0.7406 -1.0294 0.3368 -0.0428
Sum 2.1991 24.0319 1 1
Portfolio
w1 w2
Portfolio
Variance 0.45473
0.70231
6
Portfolio Std.
Dev.
0.67433
6
0.83804
3
Portfolio Return 10.928
16.8779
6
Finance and capital budgeting models 6 | P a g e
0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2-5
0
5
10
15
20
25
30
35
40
Efficient Frontier
Portfolio Risk (std. dev.)
Portfolio Returns
Minimum Variance portfolio
Beta Computation of the Woolworth
Regression
Statistics
Multiple R
0.53121
1
R Square
0.28218
6
Square
0.28070
3
Standard Error
0.00628
7
Observations 486
Finance and capital budgeting models 7 | P a g e
ANOVA
df SS MS F Significance F
Regression 1 0.00752 0.00752 190.269 9.7E-37
Residual
48
4 0.019129 3.95E-05
Total
48
5 0.026649
Coefficient
s
Standar
d Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept -0.00014
0.00028
5
-
0.4998
2
0.6174
3 -0.0007
0.00041
8 -0.0007
0.00041
8
X Variable 1 0.319581
0.02316
8
13.793
8 9.7E-37
0.27405
7
0.36510
4
0.27405
7
0.36510
4
Date
BHP Billiton
Close
Retu
rn
Woolworths
price
Retu
rn
All Ordinary Index
Retu
rn
31-
12-
2015 23.637901 21.46649 5322.799805
04-
01-
2016 23.380968
0.01
087 21.048717
0.01
9462 5239.200195
0.01
5706
05-
01-
2016 23.188267
0.00
8242 20.773165
0.01
3091 5178
0.01
1681
06-
01-
2016 21.802662
0.05
9755 20.177612
0.02
8669 5068.799805
0.02
1089
07-
01-
2016 20.609755
0.05
4714 20.328724
-
0.00
749 5049.399902
0.00
3827
08-
01-
2016 20.150944
0.02
2262 20.328724 0 4990.700195
0.01
1625
11-
01-
2016 19.637077
0.02
5501 20.355389
-
0.00
131 4982.200195
0.00
1703
12-
01-
18.939686 0.03
5514
20.666498 -
0.01
5041.600098 -
0.01
Finance and capital budgeting models 8 | P a g e
2016 528 192
13-
01-
2016 18.701103
0.01
2597 20.382053
0.01
3764 4964.100098
0.01
5372
14-
01-
2016 19.894011
-
0.06
379 20.142059
0.01
1775 4948.5
0.00
3143
15-
01-
2016 18.526756
0.06
8727 21.022049
-
0.04
369 4911.799805
0.00
7416
19-
01-
2016 18.416641
0.00
5944 20.755388
0.01
2685 4955.100098
-
0.00
882
20-
01-
2016 17.783482
0.03
438 20.959829
-
0.00
985 4896.899902
0.01
1746
21-
01-
2016 19.270029
-
0.08
359 21.226494
-
0.01
272 4917.600098
-
0.00
423
22-
01-
2016 19.710487
-
0.02
286 21.235382
-
0.00
042 4969.600098
-
0.01
057
25-
01-
2016 19.040627
0.03
3985 21.590937
-
0.01
674 5057.100098
-
0.01
761
26-
01-
2016 20.196827
-
0.06
072 21.430937
0.00
7411 5000.799805
0.01
1133
27-
01-
2016 19.591194
0.02
9987 21.759825
-
0.01
535 5028.100098
-
0.00
546
28-
01-
2016 19.994949
-
0.02
061 21.582048
0.00
817 5056.600098
-
0.00
567
29-
01-
2016 20.105062
-
0.00
551 21.715378
-
0.00
618 5094.299805
-
0.00
746
01-
02-
2016 19.939892
0.00
8215 21.46649
0.01
1461 5044
0.00
9874
02-
02-
2016 18.655222
0.06
4427 20.968718
0.02
3188 4930.799805
0.02
2443
03-
02-
2016 19.627899
-
0.05
214 21.270937
-
0.01
441 5029.299805
-
0.01
998
04-
02-
2016 21.004332
-
0.07
013 21.119829
0.00
7104 5025.600098
0.00
0736
05-
02-
20.71987 0.01
3543
21.119829 0 5022.100098 0.00
0696

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