Finance and Capital Budgeting Models

This document covers various topics related to finance and capital budgeting models, including variance and standard deviation computation, minimum variance portfolio, beta computation of Woolworth, security market line, modern portfolio theory, CAPM, Fama and French three-factor model, and more. It also includes tables, graphs, and calculations to help readers understand the concepts better.

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
Table of Contents
Part-A.........................................................................................................................................3
Answer to question no1..........................................................................................................3
Answer to question no2..........................................................................................................3
Minimum Variance portfolio.................................................................................................6
Beta Computation of the Woolworth.................................................................................6
Answer to question no-4........................................................................................................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
Answer to question no1
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
Add:- Brokerage $ 60.00
Total cost of the shares $ 50,060.00
Total revenue 61839.81242
Profit earned from sales of Shares $ 11,779.81
Answer to question no2
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
Answer to question no-3
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 WoolworthRegression
Statistics
Multiple R
0.53121
1
R Square
0.28218
6
Adjusted R
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
Coefficien
ts
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
Answer to question no-4
Date
BHP Billiton
Company Adj
Close
Retu
rn
Woolworths
Adjusted Closed
price
Retu
rn
All Ordinary Index
Adjusted Closed price
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

Finance and capital budgeting models 9 | P a g e
2016
08-
02-
2016 20.839157
-
0.00
576 20.533165
0.02
7778 4882.600098
0.02
7777
09-
02-
2016 19.994949
0.04
0511 19.866507
0.03
2467 4826.5
0.01
149
10-
02-
2016 19.866484
0.00
6425 20.079836
-
0.01
074 4870.899902
-
0.00
92
11-
02-
2016 19.444378
0.02
1247 19.706507
0.01
8592 4816.600098
0.01
1148
12-
02-
2016 20.848335
-
0.07
22 19.999836
-
0.01
488 4893.399902
-
0.01
594
16-
02-
2016 21.252089
-
0.01
937 20.293167
-
0.01
467 4961.600098
-
0.01
394
17-
02-
2016 22.133005
-
0.04
145 20.195389
0.00
4818 4938.399902
0.00
4676
18-
02-
2016 22.013716
0.00
539 20.533165
-
0.01
673 5047.100098
-
0.02
201
19-
02-
2016 22.004536
0.00
0417 20.399834
0.00
6493 5008.299805
0.00
7688
22-
02-
2016 23.206621
-
0.05
463 20.453165
-
0.00
261 5056.600098
-
0.00
964
23-
02-
2016 22.105476
0.04
745 20.390945
0.00
3042 5039.100098
0.00
3461
24-
02-
2016 20.921747
0.05
3549 19.848726
0.02
6591 4943.299805
0.01
9011
25-
02-
2016 20.949274
-
0.00
132 19.457619
0.01
9704 4944.700195
-
0.00
028
26-
02-
2016 20.701515
0.01
1827 19.857616
-
0.02
056 4945.100098
-
8.1E-
05
29-
02-
2016 20.747398
-
0.00
222 20.355389
-
0.02
507 4947.899902
-
0.00
057
01-
03-
2016 21.527374
-
0.03
759 20.088724
0.01
31 4989.600098
-
0.00
843
02-
03-
23.30756 -
0.08
20.389166 -
0.01
5083.5 -
0.01

Finance and capital budgeting models 10 | P a g e
2016 269 496 882
03-
03-
2016 23.72049
-
0.01
772 20.590317
-
0.00
987 5142.200195
-
0.01
155
04-
03-
2016 25.399733
-
0.07
079 20.809752
-
0.01
066 5151.100098
-
0.00
173
07-
03-
2016 26.766987
-
0.05
383 21.047472
-
0.01
142 5204.700195
-
0.01
041
08-
03-
2016 24.417881
0.08
7761 21.029186
0.00
0869 5169.5
0.00
6763
09-
03-
2016 25.040167
-
0.02
548 21.349195
-
0.01
522 5215.700195
-
0.00
894
10-
03-
2016 24.650078
0.01
5579 21.15719
0.00
8994 5210.899902
0.00
092
11-
03-
2016 25.281652
-
0.02
562 21.340054
-
0.00
864 5224.799805
-
0.00
267
14-
03-
2016 24.938002
0.01
3593 21.120617
0.01
0283 5242.399902
-
0.00
337
15-
03-
2016 23.229031
0.06
8529 20.837181
0.01
342 5168.600098
0.01
4077
16-
03-
2016 24.148531
-
0.03
958 20.553743
0.01
3603 5175.700195
-
0.00
137
17-
03-
2016 25.346668
-
0.04
962 20.334309
0.01
0676 5226.399902
-
0.00
98
18-
03-
2016 25.467411
-
0.00
476 20.297737
0.00
1799 5239.299805
-
0.00
247
21-
03-
2016 25.151625
0.01
24 19.996014
0.01
4865 5224.899902
0.00
2748
22-
03-
2016 24.80797
0.01
3663 20.178875
-
0.00
914 5230.799805
-
0.00
113
23-
03-
2016 23.702711
0.04
4553 20.462311
-
0.01
405 5204.299805
0.00
5066
24-
03-
2016 23.814165
-
0.00
47 20.526314
-
0.00
313 5151.600098
0.01
0126
28-
03-
23.860607 -
0.00
19.996014 0.02
5835
5076.200195 0.01
4636

Finance and capital budgeting models 11 | P a g e
2016 195
29-
03-
2016 23.897757
-
0.00
156 19.996014 0 5081.5
-
0.00
104
30-
03-
2016 24.427166
-
0.02
215 20.206305
-
0.01
052 5151.799805
-
0.01
383
31-
03-
2016 24.055651
0.01
5209 19.849724
0.01
7647 5073.799805
0.01
514
01-
04-
2016 23.823454
0.00
9652 19.804008
0.00
2303 5070.100098
0.00
0729
04-
04-
2016 22.91324
0.03
8207 19.529715
0.01
385 5000.399902
0.01
3747
05-
04-
2016 22.355965
0.02
4321 19.511429
0.00
0936 5024.600098
-
0.00
484
06-
04-
2016 22.578875
-
0.00
997 19.502285
0.00
0469 5042.299805
-
0.00
352
07-
04-
2016 22.216648
0.01
6043 19.328566
0.00
8908 5018
0.00
4819
08-
04-
2016 23.006119
-
0.03
554 19.035984
0.01
5137 5013.200195
0.00
0957
11-
04-
2016 23.786303
-
0.03
391 18.962839
0.00
3842 5053.700195
-
0.00
808
12-
04-
2016 24.80797
-
0.04
295 19.191416
-
0.01
205 5127.200195
-
0.01
454
13-
04-
2016 26.479794
-
0.06
739 19.996014
-
0.04
192 5187.700195
-
0.01
18
14-
04-
2016 26.739853
-
0.00
982 20.288593
-
0.01
463 5224.100098
-
0.00
702
15-
04-
2016 26.851311
-
0.00
417 20.288593 0 5204.899902
0.00
3675
18-
04-
2016 27.770809
-
0.03
424 20.242878
0.00
2253 5254.700195
-
0.00
957
19-
04-
2016 29.219721
-
0.05
217 20.114874
0.00
6323 5281.200195
-
0.00
504
20-
04-
30.213526 -
0.03
19.904583 0.01
0455
5336.399902 -
0.01

Finance and capital budgeting models 12 | P a g e
2016 401 045
21-
04-
2016 29.489069
0.02
3978 19.858866
0.00
2297 5299.200195
0.00
6971
22-
04-
2016 29.554085
-
0.00
22 19.657717
0.01
0129 5283.600098
0.00
2944
25-
04-
2016 28.365234
0.04
0226 19.438284
0.01
1163 5250.899902
0.00
6189
26-
04-
2016 28.838917
-
0.01
67 20.142303
-
0.03
622 5289.399902
-
0.00
733
27-
04-
2016 28.718176
0.00
4187 20.21545
-
0.00
363 5316
-
0.00
503
28-
04-
2016 28.87607
-
0.00
55 20.343451
-
0.00
633 5312
0.00
0752
29-
04-
2016 29.108269
-
0.00
804 20.361738
-
0.00
09 5415
-
0.01
939
02-
05-
2016 28.950373
0.00
5424 18.935411
0.07
0049 5335.600098
0.01
4663
03-
05-
2016 27.464308
0.05
1331 19.127417
-
0.01
014 5344.5
-
0.00
167
04-
05-
2016 25.662455
0.06
5607 19.392567
-
0.01
386 5358.600098
-
0.00
264
05-
05-
2016 25.690319
-
0.00
109 19.676004
-
0.01
462 5387.799805
-
0.00
545
06-
05-
2016 25.941093
-
0.00
976 19.767435
-
0.00
465 5403.899902
-
0.00
299
09-
05-
2016 24.390017
0.05
9792 20.846323
-
0.05
458 5434.799805
-
0.00
572
10-
05-
2016 25.235214
-
0.03
465 21.0749
-
0.01
096 5423.399902
0.00
2098
11-
05-
2016 25.402397
-
0.00
662 20.453171
0.02
9501 5396.299805
0.00
4997
12-
05-
2016 24.817257
0.02
3035 20.535458
-
0.00
402 5420.299805
-
0.00
445
13-
05-
24.705805 0.00
4491
20.78232 -
0.01
5458.5 -
0.00

Finance and capital budgeting models 13 | P a g e
2016 202 705
16-
05-
2016 25.513849
-
0.03
271 20.444027
0.01
6278 5420.5
0.00
6962
17-
05-
2016 26.294031
-
0.03
058 20.270308
0.00
8497 5385.600098
0.00
6439
18-
05-
2016 25.393106
0.03
4263 20.352596
-
0.00
406 5415.200195
-
0.00
55
19-
05-
2016 25.383821
0.00
0366 20.279449
0.00
3594 5384.899902
0.00
5595
20-
05-
2016 24.928713
0.01
7929 20.10573
0.00
8566 5361.899902
0.00
4271
23-
05-
2016 25.03088
-
0.00
41 20.37088
-
0.01
319 5436.799805
-
0.01
397
24-
05-
2016 25.1702
-
0.00
557 20.124018
0.01
2118 5451.899902
-
0.00
278
25-
05-
2016 26.247595
-
0.04
28 20.188017
-
0.00
318 5469.700195
-
0.00
326
26-
05-
2016 25.978245
0.01
0262 20.471455
-
0.01
404 5473.600098
-
0.00
071
27-
05-
2016 25.541716
0.01
6804 20.224592
0.01
2059 5447.799805
0.00
4714
31-
05-
2016 25.049456
0.01
9273 19.932011
0.01
4467 5395.200195
0.00
9655
01-
06-
2016 24.742954
0.01
2236 19.72172
0.01
055 5354.200195
0.00
7599
02-
06-
2016 24.854412
-
0.00
45 19.849724
-
0.00
649 5392.5
-
0.00
715
03-
06-
2016 25.829639
-
0.03
924 19.941154
-
0.00
461 5431
-
0.00
714
06-
06-
2016 27.102081
-
0.04
926 19.767435
0.00
8712 5441
-
0.00
184
07-
06-
2016 26.71199
0.01
4393 19.767435 0 5441.100098
-
1.8E-
05
08-
06-
27.538612 -
0.03
19.86801 -
0.00
5437.399902 0.00
068

Finance and capital budgeting models 14 | P a g e
2016 095 509
09-
06-
2016 25.987534
0.05
6324 19.694292
0.00
8744 5391.600098
0.00
8423
10-
06-
2016 24.826546
0.04
4675 19.346851
0.01
7642 5282.5
0.02
0235
13-
06-
2016 24.938002
-
0.00
449 19.218847
0.00
6616 5230.399902
0.00
9863
14-
06-
2016 24.343575
0.02
3836 19.291992
-
0.00
381 5231.700195
-
0.00
025
15-
06-
2016 25.003016
-
0.02
709 19.200562
0.00
4739 5248.299805
-
0.00
317
16-
06-
2016 24.956579
0.00
1857 19.548
-
0.01
81 5335.600098
-
0.01
663
17-
06-
2016 25.736759
-
0.03
126 19.374281
0.00
8887 5353.299805
-
0.00
332
20-
06-
2016 26.349764
-
0.02
382 19.200562
0.00
8966 5349.5
0.00
071
21-
06-
2016 26.284746
0.00
2467 19.063414
0.00
7143 5358.600098
-
0.00
17
22-
06-
2016 26.052549
0.00
8834 18.798262
0.01
3909 5192.799805
0.03
0941
23-
06-
2016 27.306416
-
0.04
813 18.907982
-
0.00
584 5216.200195
-
0.00
451
24-
06-
2016 25.290939
0.07
381 18.862267
0.00
2418 5179.700195
0.00
6997
27-
06-
2016 24.371439
0.03
6357 18.944553
-
0.00
436 5221
-
0.00
797
28-
06-
2016 25.383821
-
0.04
154 19.099987
-
0.00
82 5310.399902
-
0.01
712
29-
06-
2016 25.783199
-
0.01
573 18.962839
0.00
7181 5327
-
0.00
313
30-
06-
2016 26.52623
-
0.02
882 19.035984
-
0.00
386 5365.200195
-
0.00
717
01-
07-
26.581959 -
0.00
18.853123 0.00
9606
5312.799805 0.00
9767

Finance and capital budgeting models 15 | P a g e
2016 21
05-
07-
2016 25.829639
0.02
8302 18.743404
0.00
582 5284.700195
0.00
5289
06-
07-
2016 26.535519
-
0.02
733 18.898838
-
0.00
829 5311
-
0.00
498
07-
07-
2016 25.801775
0.02
7651 18.843981
0.00
2903 5315.600098
-
0.00
087
08-
07-
2016 27.250687
-
0.05
616 19.483997
-
0.03
396 5417.5
-
0.01
917
11-
07-
2016 27.724369
-
0.01
738 19.383425
0.00
5162 5433.200195
-
0.00
29
12-
07-
2016 28.643873
-
0.03
317 19.511429
-
0.00
66 5470.299805
-
0.00
683
13-
07-
2016 28.708887
-
0.00
227 19.630287
-
0.00
609 5491.799805
-
0.00
393
14-
07-
2016 28.746038
-
0.00
129 19.685148
-
0.00
279 5510.100098
-
0.00
333
15-
07-
2016 28.328083
0.01
454 20.069159
-
0.01
951 5538.899902
-
0.00
523
18-
07-
2016 28.095884
0.00
8197 20.297737
-
0.01
139 5533.899902
0.00
0903
19-
07-
2016 26.674837
0.05
0578 20.590317
-
0.01
441 5565.899902
-
0.00
578
20-
07-
2016 26.303322
0.01
3928 20.718321
-
0.00
622 5588.700195
-
0.00
41
21-
07-
2016 26.907034
-
0.02
295 20.526314
0.00
9267 5574.299805
0.00
2577
22-
07-
2016 26.516943
0.01
4498 22.217791
-
0.08
241 5607.5
-
0.00
596
25-
07-
2016 26.256884
0.00
9807 21.486341
0.03
2922 5612.600098
-
0.00
091
26-
07-
2016 27.362139
-
0.04
209 21.413197
0.00
3404 5615
-
0.00
043
27-
07-
27.631491 -
0.00
21.394913 0.00
0854
5636.700195 -
0.00

Finance and capital budgeting models 16 | P a g e
2016 984 386
28-
07-
2016 27.455021
0.00
6387 21.404055
-
0.00
043 5644
-
0.00
13
29-
07-
2016 27.575764
-
0.00
44 21.550344
-
0.00
683 5670.100098
-
0.00
462
01-
08-
2016 27.148521
0.01
5493 21.605204
-
0.00
255 5622.100098
0.00
8465
02-
08-
2016 27.129942
0.00
0684 21.367483
0.01
1003 5551.399902
0.01
2575
03-
08-
2016 27.752234
-
0.02
294 21.550344
-
0.00
856 5563.399902
-
0.00
216
04-
08-
2016 28.077309
-
0.01
171 21.404055
0.00
6788 5585.600098
-
0.00
399
05-
08-
2016 28.811054
-
0.02
613 21.394913
0.00
0427 5625.700195
-
0.00
718
08-
08-
2016 29.238298
-
0.01
483 21.212049
0.00
8547 5636.700195
-
0.00
196
09-
08-
2016 29.015387
0.00
7624 21.120617
0.00
431 5628.200195
0.00
1508
10-
08-
2016 28.699598
0.01
0884 21.120617 0 5599.399902
0.00
5117
11-
08-
2016 29.303312
-
0.02
104 21.394913
-
0.01
299 5626.299805
-
0.00
48
12-
08-
2016 28.764614
0.01
8384 21.4772
-
0.00
385 5633.799805
-
0.00
133
15-
08-
2016 28.978235
-
0.00
743 21.367483
0.00
5109 5625.700195
0.00
1438
16-
08-
2016 29.256872
-
0.00
962 21.550344
-
0.00
856 5628.100098
-
0.00
043
17-
08-
2016 29.637676
-
0.01
302 21.71492
-
0.00
764 5607.299805
0.00
3696
18-
08-
2016 30.19495
-
0.01
88 21.852068
-
0.00
632 5625.399902
-
0.00
323
19-
08-
29.665543 0.01
7533
22.034929 -
0.00
5612.299805 0.00
2329

Finance and capital budgeting models 17 | P a g e
2016 837
22-
08-
2016 29.396193
0.00
908 22.144648
-
0.00
498 5647.100098
-
0.00
62
23-
08-
2016 30.362131
-
0.03
286 22.144648 0 5653.600098
-
0.00
115
24-
08-
2016 29.702692
0.02
1719 23.013245
-
0.03
922 5631.399902
0.00
3927
25-
08-
2016 30.046341
-
0.01
157 22.76638
0.01
0727 5607.399902
0.00
4262
26-
08-
2016 29.804859
0.00
8037 22.592659
0.00
7631 5561.5
0.00
8186
29-
08-
2016 29.916311
-
0.00
374 22.062359
0.02
3472 5573.5
-
0.00
216
30-
08-
2016 29.247583
0.02
2353 21.678347
0.01
7406 5529.399902
0.00
7912
31-
08-
2016 28.113667
0.03
877 21.86121
-
0.00
844 5511.200195
0.00
3291
01-
09-
2016 28.329205
-
0.00
767 21.925211
-
0.00
293 5470.600098
0.00
7367
02-
09-
2016 28.694683
-
0.01
29 21.989214
-
0.00
292 5524.399902
-
0.00
983
06-
09-
2016 29.613062
-
0.03
201 22.053217
-
0.00
291 5510.399902
0.00
2534
07-
09-
2016 29.088274
0.01
7722 22.053217 0 5521.100098
-
0.00
194
08-
09-
2016 29.266327
-
0.00
612 21.700182
0.01
6008 5484.600098
0.00
6611
09-
09-
2016 28.807135
0.01
569 21.308516
0.01
8049 5440.5
0.00
8041
12-
09-
2016 29.069532
-
0.00
911 20.81427
0.02
3195 5319.100098
0.02
2314
13-
09-
2016 27.523281
0.05
3191 20.907524
-
0.00
448 5310
0.00
1711
14-
09-
28.094925 -
0.02
20.982126 -
0.00
5326.600098 -
0.00

Finance and capital budgeting models 18 | P a g e
2016 077 357 313
15-
09-
2016 28.657198
-
0.02
001 20.972803
0.00
0444 5337.100098
-
0.00
197
16-
09-
2016 28.085552
0.01
9948 21.000778
-
0.00
133 5396.700195
-
0.01
117
19-
09-
2016 28.572857
-
0.01
735 21.010103
-
0.00
044 5393.700195
0.00
0556
20-
09-
2016 29.116386
-
0.01
902 21.243238
-
0.01
11 5397.299805
-
0.00
067
21-
09-
2016 30.156593
-
0.03
573 21.224588
0.00
0878 5429.399902
-
0.00
595
22-
09-
2016 30.418985
-
0.00
87 21.215261
0.00
0439 5466.299805
-
0.00
68
23-
09-
2016 30.493958
-
0.00
246 21.774786
-
0.02
637 5518.600098
-
0.00
957
26-
09-
2016 30.578299
-
0.00
277 21.308516
0.02
1413 5519.100098
-
9.1E-
05
27-
09-
2016 30.568926
0.00
0307 21.000778
0.01
4442 5493.700195
0.00
4602
28-
09-
2016 31.955866
-
0.04
537 21.40177
-
0.01
909 5500.200195
-
0.00
118
29-
09-
2016 32.237003
-
0.00
88 21.756134
-
0.01
656 5558.200195
-
0.01
055
30-
09-
2016 32.471287
-
0.00
727 21.700182
0.00
2572 5525.200195
0.00
5937
03-
10-
2016 32.658707
-
0.00
577 21.793438
-
0.00
43 5564.799805
-
0.00
717
04-
10-
2016 32.471287
0.00
5739 21.700182
0.00
4279 5569.899902
-
0.00
092
05-
10-
2016 33.08041
-
0.01
876 21.728157
-
0.00
129 5537
0.00
5907
06-
10-
2016 32.864876
0.00
6515 22.297007
-
0.02
618 5564.799805
-
0.00
502
07-
10-
33.136642 -
0.00
22.278357 0.00
0836
5548.5 0.00
2929

Finance and capital budgeting models 19 | P a g e
2016 827
10-
10-
2016 33.652058
-
0.01
555 22.352961
-
0.00
335 5555.5
-
0.00
126
11-
10-
2016 32.780537
0.02
5898 22.47419
-
0.00
542 5562.200195
-
0.00
121
12-
10-
2016 32.808647
-
0.00
086 22.586094
-
0.00
498 5555.200195
0.00
1258
13-
10-
2016 31.909008
0.02
7421 22.586094 0 5518.299805
0.00
6642
14-
10-
2016 31.852785
0.00
1762 22.642048
-
0.00
248 5518.5
-
3.6E-
05
17-
10-
2016 31.749701
0.00
3236 22.614071
0.00
1236 5470.899902
0.00
8626
18-
10-
2016 32.321346
-
0.01
8 22.71665
-
0.00
454 5492
-
0.00
386
19-
10-
2016 32.752422
-
0.01
334 23.089664
-
0.01
642 5518.399902
-
0.00
481
20-
10-
2016 32.818016
-
0.00
2 23.229546
-
0.00
606 5526.200195
-
0.00
141
21-
10-
2016 32.761791
0.00
1713 23.583912
-
0.01
525 5513.899902
0.00
2226
24-
10-
2016 32.771168
-
0.00
029 23.509306
0.00
3163 5489.100098
0.00
4498
25-
10-
2016 33.464634
-
0.02
116 23.54661
-
0.00
159 5523.299805
-
0.00
623
26-
10-
2016 33.033558
0.01
2882 23.425381
0.00
5148 5442.100098
0.01
4701
27-
10-
2016 32.471287
0.01
7021 23.126966
0.01
2739 5378.399902
0.01
1705
28-
10-
2016 32.677452
-
0.00
635 22.595419
0.02
2984 5370.899902
0.00
1394
31-
10-
2016 32.818016
-
0.00
43 22.054546
0.02
3937 5402.399902
-
0.00
586
01-
11-
32.668083 0.00
4569
21.88669 0.00
7611
5375.200195 0.00
5035

Finance and capital budgeting models 20 | P a g e
2016
02-
11-
2016 32.105804
0.01
7212 21.532326
0.01
6191 5311
0.01
1944
03-
11-
2016 32.218262
-
0.00
35 21.439072
0.00
4331 5306.600098
0.00
0828
04-
11-
2016 31.843412
0.01
1635 21.411095
0.00
1305 5263.100098
0.00
8197
07-
11-
2016 33.32407
-
0.04
65 21.504351
-
0.00
436 5330.899902
-
0.01
288
08-
11-
2016 34.401752
-
0.03
234 21.495022
0.00
0434 5342.200195
-
0.00
212
09-
11-
2016 35.47945
-
0.03
133 21.196609
0.01
3883 5238.299805
0.01
9449
10-
11-
2016 35.732468
-
0.00
713 21.62558
-
0.02
024 5408.899902
-
0.03
257
11-
11-
2016 35.142082
0.01
6522 21.802761
-
0.00
819 5446.600098
-
0.00
697
14-
11-
2016 35.366997
-
0.00
64 21.68153
0.00
556 5420.299805
0.00
4829
15-
11-
2016 34.289303
0.03
0472 21.784111
-
0.00
473 5399.799805
0.00
3782
16-
11-
2016 33.427151
0.02
5143 21.728157
0.00
2569 5399.600098
3.7E-
05
17-
11-
2016 33.661427
-
0.00
701 21.737486
-
0.00
043 5408.899902
-
0.00
172
18-
11-
2016 33.2491
0.01
2249 21.64423
0.00
429 5427.5
-
0.00
344
21-
11-
2016 34.148731
-
0.02
706 21.308516
0.01
5511 5419.299805
0.00
1511
22-
11-
2016 35.901157
-
0.05
132 21.690859
-
0.01
794 5480.600098
-
0.01
131
23-
11-
2016 36.294743
-
0.01
096 21.821413
-
0.00
602 5549.899902
-
0.01
264
25-
11-
36.304115 -
0.00
21.914665 -
0.00
5549 0.00
0162

Finance and capital budgeting models 21 | P a g e
2016 026 427
28-
11-
2016 35.929268
0.01
0325 21.914665 0 5570.5
-
0.00
387
29-
11-
2016 35.067112
0.02
3996 21.68153
0.01
0638 5532.600098
0.00
6804
30-
11-
2016 35.179569
-
0.00
321 21.495022
0.00
8602 5520.5
0.00
2187
01-
12-
2016 35.423218
-
0.00
693 21.345818
0.00
6941 5502.399902
0.00
3279
02-
12-
2016 35.629383
-
0.00
582 21.578953
-
0.01
092 5560.399902
-
0.01
054
05-
12-
2016 36.304115
-
0.01
894 21.392447
0.00
8643 5502.600098
0.01
0395
06-
12-
2016 35.929268
0.01
0325 21.159311
0.01
0898 5458
0.00
8105
07-
12-
2016 36.472794
-
0.01
513 20.888874
0.01
2781 5486.600098
-
0.00
524
08-
12-
2016 36.454056
0.00
0514 21.36447
-
0.02
277 5535.399902
-
0.00
889
09-
12-
2016 36.060463
0.01
0797 21.588278
-
0.01
048 5599
-
0.01
149
12-
12-
2016 37.081924
-
0.02
833 21.36447
0.01
0367 5615.799805
-
0.00
3
13-
12-
2016 36.33223
0.02
0217 21.308516
0.00
2619 5619.100098
-
0.00
059
14-
12-
2016 35.207684
0.03
0952 21.280539
0.00
1313 5600.700195
0.00
3275
15-
12-
2016 34.701637
0.01
4373 21.411095
-
0.00
613 5639.700195
-
0.00
696
16-
12-
2016 34.111252
0.01
7013 21.495022
-
0.00
392 5595
0.00
7926
19-
12-
2016 33.652058
0.01
3462 21.40177
0.00
4338 5589.700195
0.00
0947
20-
12-
34.233074 -
0.01
21.672207 -
0.01
5612.799805 -
0.00

Finance and capital budgeting models 22 | P a g e
2016 727 264 413
21-
12-
2016 33.914452
0.00
9307 22.054546
-
0.01
764 5640
-
0.00
485
22-
12-
2016 33.399036
0.01
5198 22.026571
0.00
1268 5662
-
0.00
39
23-
12-
2016 33.183495
0.00
6454 22.362284
-
0.01
524 5691.799805
-
0.00
526
27-
12-
2016 33.399036
-
0.00
65 22.241055
0.00
5421 5675.100098
0.00
2934
28-
12-
2016 33.94257
-
0.01
627 22.670023
-
0.01
929 5732.399902
-
0.01
01
29-
12-
2016 33.989426
-
0.00
138 22.837881
-
0.00
74 5746.700195
-
0.00
249
30-
12-
2016 33.530235
0.01
351 22.47419
0.01
5925 5719.100098
0.00
4803
03-
01-
2017 34.692265
-
0.03
466 22.725977
-
0.01
12 5784.600098
-
0.01
145
04-
01-
2017 34.832832
-
0.00
405 22.707325
0.00
0821 5788.200195
-
0.00
062
05-
01-
2017 35.160828
-
0.00
942 22.642048
0.00
2875 5805.100098
-
0.00
292
06-
01-
2017 34.636036
0.01
4925 22.558119
0.00
3707 5809
-
0.00
067
09-
01-
2017 34.532951
0.00
2976 22.744625
-
0.00
827 5857.700195
-
0.00
838
10-
01-
2017 36.135433
-
0.04
64 22.576767
0.00
738 5813
0.00
7631
11-
01-
2017 36.903873
-
0.02
127 22.753952
-
0.00
785 5823.700195
-
0.00
184
12-
01-
2017 37.241238
-
0.00
914 22.632721
0.00
5328 5821.600098
0.00
0361
13-
01-
2017 37.334949
-
0.00
252 22.7353
-
0.00
453 5776.799805
0.00
7696
17-
01-
37.344318 -
0.00
22.819229 -
0.00
5803 -
0.00

Finance and capital budgeting models 23 | P a g e
2017 025 369 454
18-
01-
2017 37.634827
-
0.00
778 22.772602
0.00
2043 5754.700195
0.00
8323
19-
01-
2017 37.531746
0.00
2739 22.660696
0.00
4914 5733.700195
0.00
3649
20-
01-
2017 37.419289
0.00
2996 22.753952
-
0.00
412 5745.399902
-
0.00
204
23-
01-
2017 37.784767
-
0.00
977 22.7353
0.00
082 5709.700195
0.00
6214
24-
01-
2017 38.937431
-
0.03
051 22.94046
-
0.00
902 5668
0.00
7303
25-
01-
2017 39.059254
-
0.00
313 23.126966
-
0.00
813 5706.299805
-
0.00
676
26-
01-
2017 38.553211
0.01
2956 22.987087
0.00
6048 5726
-
0.00
345
27-
01-
2017 38.646919
-
0.00
243 23.462679
-
0.02
069 5765.600098
-
0.00
692
30-
01-
2017 38.065903
0.01
5034 23.229546
0.00
9936 5714.299805
0.00
8898
31-
01-
2017 38.693775
-
0.01
649 22.94046
0.01
2445 5675
0.00
6877
01-
02-
2017 38.806229
-
0.00
291 23.397404
-
0.01
992 5704
-
0.00
511
02-
02-
2017 38.356411
0.01
1591 23.583912
-
0.00
797 5696.399902
0.00
1332
03-
02-
2017 36.913246
0.03
7625 23.677162
-
0.00
395 5672.5
0.00
4196
06-
02-
2017 36.828899
0.00
2285 23.649189
0.00
1181 5665.399902
0.00
1252
07-
02-
2017 36.71645
0.00
3053 23.639864
0.00
0394 5672.600098
-
0.00
127
08-
02-
2017 36.266632
0.01
2251 23.649189
-
0.00
039 5703.399902
-
0.00
543
09-
02-
36.744564 -
0.01
23.54661 0.00
4338
5717.700195 -
0.00

Finance and capital budgeting models 24 | P a g e
2017 318 251
10-
02-
2017 37.569229
-
0.02
244 23.621212
-
0.00
317 5771.600098
-
0.00
943
13-
02-
2017 37.887852
-
0.00
848 23.779743
-
0.00
671 5812.899902
-
0.00
716
14-
02-
2017 37.925339
-
0.00
099 23.798397
-
0.00
078 5810.899902
0.00
0344
15-
02-
2017 38.17836
-
0.00
667 23.649189
0.00
627 5859.100098
-
0.00
829
16-
02-
2017 38.41264
-
0.00
614 23.649189 0 5863
-
0.00
067
17-
02-
2017 37.74728
0.01
7321 23.770418
-
0.00
513 5851
0.00
2047
21-
02-
2017 38.187733
-
0.01
167 23.779743
-
0.00
039 5840.5
0.00
1795
22-
02-
2017 37.306839
0.02
3067 23.779743 0 5835.399902
0.00
0873
23-
02-
2017 36.650852
0.01
7584 24.833513
-
0.04
431 5850.100098
-
0.00
252
24-
02-
2017 35.582535
0.02
9148 24.712284
0.00
4882 5832.5
0.00
3009
27-
02-
2017 36.172916
-
0.01
659 24.712284 0 5786.899902
0.00
7818
28-
02-
2017 35.441963
0.02
0207 24.423195
0.01
1698 5773.799805
0.00
2264
01-
03-
2017 36.379086
-
0.02
644 24.022203
0.01
6418 5761
0.00
2217
02-
03-
2017 35.63876
0.02
035 23.78907
0.00
9705 5750.899902
0.00
1753
03-
03-
2017 36.603996
-
0.02
708 24.212769
-
0.01
781 5820.700195
-
0.01
214
06-
03-
2017 35.929268
0.01
8433 24.155731
0.00
2356 5775.399902
0.00
7783
07-
03-
35.760582 0.00
4695
24.431416 -
0.01
5788.5 -
0.00

Finance and capital budgeting models 25 | P a g e
2017 141 227
08-
03-
2017 34.879971
0.02
4625 24.81167
-
0.01
556 5801.899902
-
0.00
231
09-
03-
2017 34.142933
0.02
1131 24.773645
0.00
1533 5799.5
0.00
0414
10-
03-
2017 34.114216
0.00
0841 24.783152
-
0.00
038 5780.5
0.00
3276
13-
03-
2017 34.82254
-
0.02
076 25.115877
-
0.01
343 5811.200195
-
0.00
531
14-
03-
2017 34.602386
0.00
6322 25.068346
0.00
1892 5794.600098
0.00
2857
15-
03-
2017 36.334896
-
0.05
007 25.030317
0.00
1517 5798.100098
-
0.00
06
16-
03-
2017 36.287041
0.00
1317 25.049332
-
0.00
076 5813.700195
-
0.00
269
17-
03-
2017 36.545479
-
0.00
712 24.840189
0.00
8349 5827.5
-
0.00
237
20-
03-
2017 36.803921
-
0.00
707 24.593025
0.00
995 5840.799805
-
0.00
228
21-
03-
2017 35.377708
0.03
8752 24.564505
0.00
116 5820.5
0.00
3476
22-
03-
2017 35.483002
-
0.00
298 24.545494
0.00
0774 5819.5
0.00
0172
23-
03-
2017 35.243702
0.00
6744 24.174744
0.01
5105 5732
0.01
5036
24-
03-
2017 34.946972
0.00
8419 24.34586
-
0.00
708 5754
-
0.00
384
27-
03-
2017 34.296089
0.01
8625 24.659571
-
0.01
289 5796.100098
-
0.00
732
28-
03-
2017 34.966118
-
0.01
954 24.659571 0 5789.200195
0.00
119
29-
03-
2017 35.310703
-
0.00
985 24.954268
-
0.01
195 5860.399902
-
0.01
23
30-
03-
35.320282 -
0.00
25.049332 -
0.00
5910.700195 -
0.00

Finance and capital budgeting models 26 | P a g e
2017 027 381 858
31-
03-
2017 34.765106
0.01
5718 25.382055
-
0.01
328 5931.799805
-
0.00
357
03-
04-
2017 34.879971
-
0.00
33 25.191927
0.00
7491 5903.799805
0.00
472
04-
04-
2017 35.28199
-
0.01
153 25.353535
-
0.00
642 5909.700195
-
0.00
1
05-
04-
2017 35.530861
-
0.00
705 25.410572
-
0.00
225 5895.799805
0.00
2352
06-
04-
2017 35.569145
-
0.00
108 25.448601
-
0.00
15 5915.899902
-
0.00
341
07-
04-
2017 35.387283
0.00
5113 25.258472
0.00
7471 5897.299805
0.00
3144
10-
04-
2017 36.622055
-
0.03
489 25.210939
0.00
1882 5902.600098
-
0.00
09
11-
04-
2017 36.74649
-
0.00
34 25.267977
-
0.00
226 5948.899902
-
0.00
784
12-
04-
2017 35.013981
0.04
7148 25.096863
0.00
6772 5964.600098
-
0.00
264
13-
04-
2017 34.544952
0.01
3395 25.267977
-
0.00
682 5968.899902
-
0.00
072
17-
04-
2017 34.698105
-
0.00
443 25.163406
0.00
4138 5925.899902
0.00
7204
18-
04-
2017 34.047215
0.01
8759 25.058838
0.00
4156 5868.700195
0.00
9652
19-
04-
2017 33.922783
0.00
3655 24.887722
0.00
6829 5839.899902
0.00
4907
20-
04-
2017 34.449238
-
0.01
552 24.982788
-
0.00
382 5854.399902
-
0.00
248
21-
04-
2017 34.229084
0.00
6391 25.201433
-
0.00
875 5885.600098
-
0.00
533
24-
04-
2017 34.611958
-
0.01
119 25.353535
-
0.00
604 5900.700195
-
0.00
257
25-
04-
34.784252 -
0.00
25.648233 -
0.01
5936.799805 -
0.00

Finance and capital budgeting models 27 | P a g e
2017 498 162 612
26-
04-
2017 34.506668
0.00
798 25.648233 0 5944.399902
-
0.00
128
27-
04-
2017 33.511189
0.02
8849 25.553169
0.00
3706 5947.600098
-
0.00
054
28-
04-
2017 34.075932
-
0.01
685 25.695766
-
0.00
558 5976.399902
-
0.00
484
01-
05-
2017 34.305656
-
0.00
674 25.999969
-
0.01
184 5971.399902
0.00
0837
02-
05-
2017 33.865353
0.01
2835 25.296497
0.02
7057 5919.899902
0.00
8624
03-
05-
2017 32.716724
0.03
3918 25.363043
-
0.00
263 5904.5
0.00
2601
04-
05-
2017 32.372135
0.01
0533 24.954268
0.01
6117 5863.799805
0.00
6893
05-
05-
2017 33.013454
-
0.01
981 25.258472
-
0.01
219 5897.799805
-
0.00
58
08-
05-
2017 32.573143
0.01
3337 25.306005
-
0.00
188 5874.5
0.00
3951
09-
05-
2017 32.927303
-
0.01
087 25.477118
-
0.00
676 5911.100098
-
0.00
623
10-
05-
2017 33.597336
-
0.02
035 25.771818
-
0.01
157 5912
-
0.00
015
11-
05-
2017 33.673912
-
0.00
228 25.610209
0.00
6271 5870.899902
0.00
6952
12-
05-
2017 33.693058
-
0.00
057 25.467611
0.00
5568 5868.399902
0.00
0426
15-
05-
2017 34.17165
-
0.01
42 25.458107
0.00
0373 5882.200195
-
0.00
235
16-
05-
2017 34.544952
-
0.01
092 24.944759
0.02
0164 5821.200195
0.01
037
17-
05-
2017 33.903637
0.01
8565 24.849697
0.00
3811 5775.5
0.00
7851
18-
05-
34.363091 -
0.01
24.574013 0.01
1094
5768.899902 0.00
1143

Finance and capital budgeting models 28 | P a g e
2017 355
19-
05-
2017 35.138409
-
0.02
256 24.621542
-
0.00
193 5811.200195
-
0.00
733
22-
05-
2017 35.310703
-
0.00
49 24.659571
-
0.00
154 5802.799805
0.00
1446
23-
05-
2017 35.090549
0.00
6235 24.954268
-
0.01
195 5811.600098
-
0.00
152
24-
05-
2017 34.92783
0.00
4637 24.81167
0.00
5714 5828.799805
-
0.00
296
25-
05-
2017 34.659813
0.00
7673 24.764139
0.00
1916 5792.100098
0.00
6296
26-
05-
2017 34.305656
0.01
0218 24.602531
0.00
6526 5747.700195
0.00
7666
30-
05-
2017 34.430092
-
0.00
363 24.583519
0.00
0773 5756
-
0.00
144
31-
05-
2017 33.587769
0.02
4465 24.764139
-
0.00
735 5761.299805
-
0.00
092
01-
06-
2017 33.702629
-
0.00
342 24.840189
-
0.00
307 5772.5
-
0.00
194
02-
06-
2017 33.951496
-
0.00
738 25.220446
-
0.01
531 5821.100098
-
0.00
842
05-
06-
2017 33.568619
0.01
1277 25.220446 0 5792.100098
0.00
4982
06-
06-
2017 33.7122
-
0.00
428 24.830685
0.01
5454 5708.100098
0.01
4503
07-
06-
2017 33.386757
0.00
9654 24.659571
0.00
6891 5707.799805
5.26
E-05
08-
06-
2017 34.066357
-
0.02
036 24.783152
-
0.00
501 5714.799805
-
0.00
123
09-
06-
2017 33.874924
0.00
5619 24.669077
0.00
4603 5715.5
-
0.00
012
12-
06-
2017 33.578194
0.00
876 24.79266
-
0.00
501 5801.799805
-
0.01
51
13-
06-
33.999355 -
0.01
24.992294 -
0.00
5862.200195 -
0.01

Finance and capital budgeting models 29 | P a g e
2017 254 805 041
14-
06-
2017 33.559052
0.01
295 24.897228
0.00
3804 5796.700195
0.01
1173
15-
06-
2017 33.042171
0.01
5402 24.954268
-
0.00
229 5808
-
0.00
195
16-
06-
2017 33.214462
-
0.00
521 24.079679
0.03
5048 5835.5
-
0.00
473
19-
06-
2017 33.41547
-
0.00
605 23.908564
0.00
7106 5792.299805
0.00
7403
20-
06-
2017 32.2477
0.03
4947 23.861032
0.00
1988 5703.200195
0.01
5382
21-
06-
2017 32.228558
0.00
0594 23.984615
-
0.00
518 5742.299805
-
0.00
686
22-
06-
2017 32.486996
-
0.00
802 24.108198
-
0.00
515 5754.600098
-
0.00
214
23-
06-
2017 32.697578
-
0.00
648 24.326845
-
0.00
907 5758.399902
-
0.00
066
26-
06-
2017 32.525284
0.00
5269 24.307833
0.00
0782 5752.5
0.00
1025
27-
06-
2017 32.936878
-
0.01
265 24.402897
-
0.00
391 5796.100098
-
0.00
758
28-
06-
2017 33.941925
-
0.03
051 24.564505
-
0.00
662 5855.899902
-
0.01
032
29-
06-
2017 34.085506
-
0.00
423 24.279316
0.01
161 5764
0.01
5694
30-
06-
2017 34.066357
0.00
0562 23.975107
0.01
253 5727.5
0.00
6332
03-
07-
2017 34.631104
-
0.01
658 24.421909
-
0.01
864 5819.600098
-
0.01
608
05-
07-
2017 34.841686
-
0.00
608 24.355364
0.00
2725 5801
0.00
3196
06-
07-
2017 35.368141
-
0.01
511 24.288818
0.00
2732 5797.5
0.00
0603
07-
07-
35.626579 -
0.00
24.241287 0.00
1957
5743.899902 0.00
9245

Finance and capital budgeting models 30 | P a g e
2017 731
10-
07-
2017 36.028599
-
0.01
128 24.497961
-
0.01
059 5762.899902
-
0.00
331
11-
07-
2017 36.535904
-
0.01
408 24.478949
0.00
0776 5768.5
-
0.00
097
12-
07-
2017 36.823063
-
0.00
786 24.412405
0.00
2718 5717.700195
0.00
8806
13-
07-
2017 36.985786
-
0.00
442 24.716608
-
0.01
246 5779.100098
-
0.01
074
14-
07-
2017 37.713253
-
0.01
967 25.068346
-
0.01
423 5808.700195
-
0.00
512
17-
07-
2017 37.942974
-
0.00
609 25.1539
-
0.00
341 5800.799805
0.00
136
18-
07-
2017 37.741966
0.00
5298 24.954268
0.00
7936 5738.200195
0.01
0792
19-
07-
2017 38.105698
-
0.00
964 24.954268 0 5779.399902
-
0.00
718
20-
07-
2017 37.531387
0.01
5072 25.163406
-
0.00
838 5805.700195
-
0.00
455
21-
07-
2017 37.129364
0.01
0712 25.001799
0.00
6422 5771.200195
0.00
5942
24-
07-
2017 37.225082
-
0.00
258 24.954268
0.00
1901 5738
0.00
5753
25-
07-
2017 38.488571
-
0.03
394 25.058838
-
0.00
419 5775.299805
-
0.00
65
26-
07-
2017 39.015026
-
0.01
368 25.248964
-
0.00
759 5823.299805
-
0.00
831
27-
07-
2017 39.053314
-
0.00
098 25.410572
-
0.00
64 5832.200195
-
0.00
153
28-
07-
2017 39.378761
-
0.00
833 25.201433
0.00
823 5755.200195
0.01
3203
31-
07-
2017 39.876499
-
0.01
264 25.382055
-
0.00
717 5773.899902
-
0.00
325
01-
08-
39.618057 0.00
6481
25.695766 -
0.01
5820.600098 -
0.00

Finance and capital budgeting models 31 | P a g e
2017 236 809
02-
08-
2017 39.397903
0.00
5557 25.619715
0.00
296 5794.5
0.00
4484
03-
08-
2017 39.053314
0.00
8746 25.638727
-
0.00
074 5786.799805
0.00
1329
04-
08-
2017 39.445763
-
0.01
005 25.667246
-
0.00
111 5773.299805
0.00
2333
07-
08-
2017 40.192371
-
0.01
893 25.572182
0.00
3704 5824.5
-
0.00
887
08-
08-
2017 39.69463
0.01
2384 25.610209
-
0.00
149 5795.700195
0.00
4945
09-
08-
2017 39.589344
0.00
2652 25.638727
-
0.00
111 5816.399902
-
0.00
357
10-
08-
2017 38.88102
0.01
7892 25.429586
0.00
8157 5810.600098
0.00
0997
11-
08-
2017 38.622581
0.00
6647 25.543663
-
0.00
449 5743.5
0.01
1548
14-
08-
2017 38.727871
-
0.00
273 25.572182
-
0.00
112 5778.600098
-
0.00
611
15-
08-
2017 38.354568
0.00
9639 25.752804
-
0.00
706 5804
-
0.00
44
16-
08-
2017 39.407475
-
0.02
745 25.800335
-
0.00
185 5830.799805
-
0.00
462
17-
08-
2017 38.727871
0.01
7246 25.638727
0.00
6264 5827.200195
0.00
0617
18-
08-
2017 38.670444
0.00
1483 25.68626
-
0.00
185 5798.5
0.00
4925
21-
08-
2017 39.158607
-
0.01
262 25.6007
0.00
3331 5780
0.00
319
22-
08-
2017 39.637199
-
0.01
222 25.724285
-
0.00
483 5804.799805
-
0.00
429
23-
08-
2017 39.962643
-
0.00
821 25.610209
0.00
4435 5792.700195
0.00
2084
24-
08-
39.924358 0.00
0958
24.735622 0.03
415
5801.700195 -
0.00

Finance and capital budgeting models 32 | P a g e
2017 155
25-
08-
2017 40.737972
-
0.02
038 24.79266
-
0.00
231 5803.399902
-
0.00
029
28-
08-
2017 40.996414
-
0.00
634 24.564505
0.00
9203 5771.200195
0.00
5548
29-
08-
2017 41.159134
-
0.00
397 24.298325
0.01
0836 5733.600098
0.00
6515
30-
08-
2017 40.986835
0.00
4186 24.355364
-
0.00
235 5733.799805
-
3.5E-
05
31-
08-
2017 41.637726
-
0.01
588 24.716608
-
0.01
483 5776.299805
-
0.00
741
01-
09-
2017 42.26947
-
0.01
517 24.516973
0.00
8077 5786.100098
-
0.00
17
05-
09-
2017 42.183323
0.00
2038 24.469442
0.00
1939 5763.799805
0.00
3854
06-
09-
2017 42.633205
-
0.01
066 24.574013
-
0.00
427 5767.799805
-
0.00
069
07-
09-
2017 43.091942
-
0.01
076 24.488453
0.00
3482 5752.899902
0.00
2583
08-
09-
2017 41.95974
0.02
6274 24.737095
-
0.01
015 5753.799805
-
0.00
016
11-
09-
2017 42.652725
-
0.01
652 24.766428
-
0.00
119 5739.399902
0.00
2503
12-
09-
2017 42.896732
-
0.00
572 24.795761
-
0.00
118 5779
-
0.00
69
13-
09-
2017 42.223267
0.01
57 24.649097
0.00
5915 5806.399902
-
0.00
474
14-
09-
2017 41.549805
0.01
595 24.854425
-
0.00
833 5804
0.00
0413
15-
09-
2017 40.81778
0.01
7618 24.825092
0.00
118 5798.399902
0.00
0965
18-
09-
2017 41.256996
-
0.01
076 24.825092 0 5755.799805
0.00
7347
19-
09-
41.217953 0.00
0946
24.72732 0.00
3938
5779 -
0.00

Finance and capital budgeting models 33 | P a g e
2017 403
20-
09-
2017 41.042267
0.00
4262 24.619766
0.00
435 5772.399902
0.00
1142
21-
09-
2017 40.700657
0.00
8323 24.717543
-
0.00
397 5769.700195
0.00
0468
22-
09-
2017 40.681133
0.00
048 24.737095
-
0.00
079 5716.700195
0.00
9186
25-
09-
2017 40.28096
0.00
9837 24.785984
-
0.00
198 5740.600098
-
0.00
418
26-
09-
2017 39.568455
0.01
7688 24.629543
0.00
6312 5741.700195
-
0.00
019
27-
09-
2017 39.568455 0 24.737095
-
0.00
437 5729.600098
0.00
2107
28-
09-
2017 39.519653
0.00
1233 24.668653
0.00
2767 5725.5
0.00
0716
29-
09-
2017 39.558693
-
0.00
099 24.541546
0.00
5153 5731.5
-
0.00
105
02-
10-
2017 39.880787
-
0.00
814 24.649097
-
0.00
438 5744.899902
-
0.00
234
03-
10-
2017 40.085751
-
0.00
514 24.60021
0.00
1983 5791.299805
-
0.00
808
04-
10-
2017 40.144314
-
0.00
146 24.443771
0.00
6359 5764.200195
0.00
4679
05-
10-
2017 40.26144
-
0.00
292 23.994007
0.01
84 5719.600098
0.00
7737
06-
10-
2017 40.349281
-
0.00
218 24.121113
-
0.00
53 5720.299805
-
0.00
012
09-
10-
2017 40.124794
0.00
5564 24.306887
-
0.00
77 5777.399902
-
0.00
998
10-
10-
2017 40.534729
-
0.01
022 24.29711
0.00
0402 5805.100098
-
0.00
479
11-
10-
2017 39.939346
0.01
4688 24.160223
0.00
5634 5807.100098
-
0.00
034
12-
10-
40.046711 -
0.00
24.326441 -
0.00
5840.799805 -
0.00

Finance and capital budgeting models 34 | P a g e
2017 269 688 58
13-
10-
2017 41.188671
-
0.02
852 24.365551
-
0.00
161 5864.100098
-
0.00
399
16-
10-
2017 41.627888
-
0.01
066 24.492659
-
0.00
522 5884.700195
-
0.00
351
17-
10-
2017 41.403397
0.00
5393 24.707764
-
0.00
878 5917.200195
-
0.00
552
18-
10-
2017 40.505447
0.02
1688 24.903313
-
0.00
791 5958.100098
-
0.00
691
19-
10-
2017 40.564011
-
0.00
145 24.952202
-
0.00
196 5954.799805
0.00
0554
20-
10-
2017 40.28096
0.00
6978 25.040199
-
0.00
353 5959.799805
-
0.00
084
23-
10-
2017 40.232159
0.00
1212 25.059753
-
0.00
078 5968.600098
-
0.00
148
24-
10-
2017 40.534729
-
0.00
752 24.893536
0.00
6633 5957.200195
0.00
191
25-
10-
2017 39.773422
0.01
8782 24.697987
0.00
7855 5962.5
-
0.00
089
26-
10-
2017 39.900307
-
0.00
319 24.590433
0.00
4355 5972.700195
-
0.00
171
27-
10-
2017 39.685577
0.00
5382 24.60021
-
0.00
04 5982.5
-
0.00
164
30-
10-
2017 39.812462
-
0.00
32 24.541546
0.00
2385 5969.299805
0.00
2206
31-
10-
2017 39.99791
-
0.00
466 24.737095
-
0.00
797 5983.700195
-
0.00
241
01-
11-
2017 41.022743
-
0.02
562 25.304192
-
0.02
292 5976.399902
0.00
122
02-
11-
2017 41.774292
-
0.01
832 25.714846
-
0.01
623 6005.5
-
0.00
487
03-
11-
2017 41.139874
0.01
5187 25.450855
0.01
0266 6002.200195
0.00
0549
06-
11-
42.369675 -
0.02
25.480186 -
0.00
6030.299805 -
0.00

Finance and capital budgeting models 35 | P a g e
2017 989 115 468
07-
11-
2017 42.193989
0.00
4147 25.519297
-
0.00
153 6027.200195
0.00
0514
08-
11-
2017 42.730804
-
0.01
272 25.529076
-
0.00
038 6087.399902
-
0.00
999
09-
11-
2017 41.881657
0.01
9872 25.548628
-
0.00
077 6089.100098
-
0.00
028
10-
11-
2017 41.754772
0.00
303 25.646404
-
0.00
383 6122.399902
-
0.00
547
13-
11-
2017 41.676689
0.00
187 25.656181
-
0.00
038 6104.299805
0.00
2956
14-
11-
2017 40.690891
0.02
3653 25.724625
-
0.00
267 6097.200195
0.00
1163
15-
11-
2017 40.222397
0.01
1513 25.695293
0.00
114 6048.700195
0.00
7954
16-
11-
2017 40.388325
-
0.00
413 25.529076
0.00
6469 6012.299805
0.00
6018
17-
11-
2017 40.388325 0 25.27486
0.00
9958 6023.5
-
0.00
186
20-
11-
2017 40.134552
0.00
6283 25.255304
0.00
0774 6038.299805
-
0.00
246
21-
11-
2017 40.661613
-
0.01
313 25.284637
-
0.00
116 6028
0.00
1706
22-
11-
2017 41.256996
-
0.01
464 25.333525
-
0.00
193 6044.200195
-
0.00
269
24-
11-
2017 41.686447
-
0.01
041 25.519297
-
0.00
733 6067.600098
-
0.00
387
27-
11-
2017 40.886101
0.01
9199 25.617073
-
0.00
383 6067.5
1.65
E-05
28-
11-
2017 40.993465
-
0.00
263 25.724625
-
0.00
42 6063.100098
0.00
0725
29-
11-
2017 40.446884
0.01
3333 25.685514
0.00
152 6070.399902
-
0.00
12
30-
11-
40.554249 -
0.00
26.174391 -
0.01
6066.700195 0.00
0609

Finance and capital budgeting models 36 | P a g e
2017 265 903
01-
12-
2017 41.554249
-
0.02
466 26.360161
-
0.00
71 6096.100098
-
0.00
485
02-
12-
2017 42.554249
-
0.02
406 26.311275
0.00
1855 6057.200195
0.00
6381
03-
12-
2017 43.554249
-
0.02
35 26.272165
0.00
1486 6075.5
-
0.00
302
Beta Calculation of the BHP
Regression
Statistics
Multiple R
0.34441417
4
R Square
0.11862112
3
Adjusted R
Square
0.11680009
3
Standard Error
0.00696620
7
Observations 486
ANOVA
df SS
MS
F
Significance F
Regression 1 0.003161095 0.003161095 65.13955034 5.56117E-15
Residual
48
4 0.023487572 4.8528E-05
Total
48
5 0.026648667
Coefficie
nts
Standard
Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Interce
pt
-
0.00013
2598
0.000316
671
-
0.41872
4971
0.67560
2891
-
0.00075
4817
0.00048
9621
-
0.00075
4817
0.00048
9621
X 0.10905 0.013512 8.07090 5.56117 0.08250 0.13561 0.08250 0.13561

Finance and capital budgeting models 37 | P a g e
Variabl
e 1 9495 668 7653 E-15 8759 0232 8759 0232
Security Market line
-0.14
-0.1
-0.09
-0.08
-0.06
-0.04
-0.03
-0.03
-0.01
-0.01
0
0.01
0.02
0.03
0.04
0.04
0.05
0.05
0.06
0.07
0.1
0.11
0.13
0.15
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
f(x) = 0.00471739130434783 x − 0.0527173913043478
R² = 0.816001524944981
The Basic Capital Asset Pricing Model
Excess Return on Stock
Excess Return on Market Portfolio

Finance and capital budgeting models 38 | P a g e
-0.14
-0.1
-0.09
-0.08
-0.06
-0.04
-0.03
-0.03
-0.01
-0.01
0
0.01
0.02
0.03
0.04
0.04
0.05
0.05
0.06
0.07
0.1
0.11
0.13
0.15
-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
4.00%
6.00%
8.00%
f(x) = − 6.08847674065066E-05 x² + 0.00623951048951049 x
− 0.0593132411067194
R² = 0.82118485946791
f(x) = − 6.08847674065066E-05 x² + 0.00623951048951049 x
− 0.0593132411067194
R² = 0.82118485946791
f(x) = 0.000028311731 x³ − 0.001122575 x² + 0.01707441 x − 0.084156785
R² = 0.862037705890271
Security market Frontline for these two
Stocks
Excess Return on Stock
Excess Return on Market Portfolio

Finance and capital budgeting models 39 | P a g e
Portfolio risk Using SIM
Earnings History
BHP
Woolwort
h
Average earning 0.5 0.5
Jan 0.485 0.224
Feb 0.103 0.29
Mar 0.235 0.215
Apr -0.055 -0.272
May -0.085 0.145
Jun 0.056 0.107
Jul 0.038 0.321
Aug 0.089 0.305
Sep 0.09 0.195
Oct 0.082 0.39
Nov 0.035 -0.072
Dec 0.176 0.715
Portfolio risk by
usingSIM
0.15414
0 0.13179
Portfolio return by
usingSIM 0.03396 0.01802

Finance and capital budgeting models 40 | P a g e
Part-2
Modern portfolio theory
Investment portfolio is not a new term for investors. It is a collection or combination
of income producing assets that are bought to meet he financial goals. In the investment
market the major risk is the deviation of purchased stokes. The investors always have a risk
of stokes getting deviation lower than the average value of stokes. The modern portfolio
theory is the tool to identify the risks of investment market using different theories or other
market analysis (Petković, 2015). Modern portfolio theory defined in the hypothesis made by
Harry Markowitz in his research paper “Portfolio Selection”, as an investment practice theory
which is based on idea that the investors concerned with risk-averse can construct a portfolio
in order to maximize or optimize their expected return on their stokes in market. Modern
portfolio theory or the portfolio management theory suggests that it is not impossible to
create or construct an efficient frontier for the most favourable portfolio which can give you
the expected return for your investment. This theory includes only four pages of theory
assessment and rest 8 pages are describing the different graphs and analytical discussion
about the market progress or behaviours. This complex structure makes it difficult to
understand for individuals not belonging from the investment market. But in investment
market it is the key element used to make a good profit using its theories for portfolio
preparation (Omar,et al. 2014).
Source: https://www.forexlive.com/education/!/modern-portfolio-theory-has-it-wrong-
20131102

Finance and capital budgeting models 41 | P a g e
In investment market each stock has its own standards deviation from the mean value
of stock and this deviation of stock from their mean value, in modern portfolio theory, is
defined as risk. In the portfolio of wide range of individual stocks, risk will be less than that
of in the individual stock portfolio. According to Markowitz, investment is not only about
picking the random stocks from the market but in true sense it is the selection of right
combination of the individual stocks among the available stocks. Modern portfolio theory is
therefore defined as an efficient frontier. The efficient frontier is defined as a set of optimal
portfolios which are offering the maximum expected return for the given risk level or at the
lowest risk which is associated with the expected return. These sub optimal portfolios lying
below the efficient frontiers are not sufficient to provide the enough or expected return for the
given level of risk. In the investment market it is assumed that higher the level of risk, higher
will be the potential return. In other words it is said that the investors who take risks of low
level also have a low potential return.
Source: http://www.assignmentpoint.com/business/finance/modern-portfolio-theory.html
The optimal portfolio simply does not include the securities of potential return or low risk
securities. Instead of this, it aims to balance the securities of greatest potential returns with
the lowest degree of risk or an acceptable degree of risk (Magni, 2016).
Capital Asset Pricing Model
The capital asset pricing model was first worked out by the financial economist,
William Sharpe. He discussed about his work in his book “Portfolio Theory and Capital
Marketers” on the capital asset pricing model. The capital asset pricing model defines that the
individual investment in the market is associated with two major risks which are as

Finance and capital budgeting models 42 | P a g e
 Systematic risk: This type of risks cannot be diversified. The reduced interest rates, wars, and
recession in the market (Irvin, 2016).
 Unsystematic risks: These risks also known as the Specific Risk as this risk is specified for an
individual stock and can be diversified using the modern portfolio theory in which investors
use a number of stocks in their portfolio (Higgins, (2012).
On the analysis of two types of risks the capital asset pricing model presents a simple theory
which is used to deliver simple results. The theory of CAPM suggests that the only reason, an
investor should earn more from one stock rather than the other one, is that the one giving
more earning is riskier. Although the model has dominated the modern financial theories but
still it is not clear that the model will work all the time. Some studies on CAPM show doubts
on the model but still it is used by most of the investors and making money for them as well.
Since the theory of capital asset pricing model is not perfect but its spirit is correct (Gotze,
Northcott, & Schuster, 2016).

Finance and capital budgeting models 43 | P a g e
It presents a usable measure of risk which helps investors to determine about the kind of
returns they deserve for the money they put at risk in the market. According to the theory of
capital asset pricing model, he expected return of a particular portfolio or security is given by
the rate on the risk free security plus the risk premium associate with the riskier stock
(Storey, & Greene, 2010). In this theory if the portfolio or security fails to meet or exceed
the required or expected return then the investment should not be made in that particular
portfolio. This model can be summarised by the formula (Goldmann, 2017).
Required or expected return= RF rate + (Market return-RF rate)*Beta
Here market return-RF rate is defined as the risk premium (Goldmann, 2017).
Expected return calculated using the CAPM formula is representing the expected return of
the capital asset for the given time. It is a long term assumption describing the behaviour of
investment having over its life time. Risk free rate is equal to yield based on 10 years
government bond. And the beta notation is the presentation of the risk availability in market.
For every investment there are some market risks associated with it, if not then the beta value
will be zero otherwise it will have a real number value (Gitman, Juchau, & Flanagan, 2015).
This CAPM if often used in finance industry by the professionals of the industry like
investment bankers, accountants, and financial analysts. This is a part of the weighted
average cost of capital (WACC) as it calculates the equity cost for the investment (Finnie,
2012).

Finance and capital budgeting models 44 | P a g e
Source: https://www.slidegeeks.com/business/product/business-framework-capm-capital-
asset-pricing-model-powerpoint-presentation
CAPM and multi-factor models
The modern portfolio theory is used to construct a portfolio of different stocks to be used for
the selection. In similar way multi-factor model is a financial model which applies multiple
factors for the calculation, used to explain the equilibrium asset pieces and/or market
phenomena (Sartori, et al. 2014). This model can be divided into three different categories
as: macroeconomic model, statistical model and fundamental models. The fundamental
model analyse relationship between a security return and its underlying financials like
earnings etc. Macroeconomic model compares the security return for the factors like
employment, interest, inflation etc. And the Statistical models are used to compare returns of
different securities based on the statistical performance of each security (Enqvist, Graham, &
Nikkinen, 2014).
The formula used in multiple-factor model is given as:
Ri=ai+_i(m)*Rm+_i(1)*F1+_i(2)*F2….+_i(N)*FN+ei

Finance and capital budgeting models 45 | P a g e
Where
Ri is the return of security i
Rm is the Market return
F(1,2,3,….N) is used for each of the factors used in the model
e is denoting the error term in the formula
a is the intercept (Dayananda, 2012).
Fama and French three factor model
The only factor which makes the Fama and French Three Factor model extraordinary if that
id provides the strategy for using the primary factors which drive the stock return calculated
from the same as well as the other models. This unique feature of Fama and French three
factor model is only of this kind in other multi-factor models. The Fama and French three
factor model expands on CAPM with addition of the size and value factor to the market
factor of CAPM. By adding these two factors the model is adjusted for the outperformance
tendency which is the key tool making it better tool for the evaluation of manager
performance. This can be stated that theism model is based on the arbitrage pricing theory
and one which is widely used multi-factor model (Brown, 2018). The arbitrage pricing
theory stated that the systematic risk is multidimensional in character and therefore dependent
on various economic risk factors. This model concerned about three factors as; book to
market value, excess return on the market, and size of the firms or these three factors can be
defined as SMB (small minus big), the portfolio’s return lass the risk free rate of return, and
HML ( high minus low) (REDDY, & SHARMA, 2014).
These risk factor used in this model are defined as Beta is a measure of volatility of the stock
compared to the market volatility as a whole, Size is the extra risk associated with the small
companies (Pollitt, & Bouckaert, 2017). It is assumed that the larger companies have a low
risk in comparison to the small companies. Value is defined as the owning of the out-of-
favour stocks due to their attractive valuation. The value stocks are of the companies which
tend to have a lower growth rate, lower price compared to their book value, and higher
dividends (Brooks, 2015).

Finance and capital budgeting models 46 | P a g e
This model found that on an average Beta is the only reason for almost 70% of the stock
returns. But the non-satisfaction made the investors to think about the better explanation and
they discover this method to increase this number to 95% using the size and value factor with
beta (Adekola, Samy, & Knight, 2017).

Finance and capital budgeting models 47 | P a g e
References
Adekola, A., Samy, M., & Knight, D. (2017). Efficient working capital management as the
tool for driving profitability and liquidity: a correlation analysis of Nigerian
companies. International Journal of Business and Globalisation, 18(2), 251-275.
Brooks, R. (2015). Financial management: core concepts. Pearson.
Brown, D. R. (2018). Evaluating institutional sustainability in development programmes:
Beyond dollars and cents. Journal of International Development, 10(1), 55-69.
Dayananda, D. (2012). Capital budgeting: financial appraisal of investment projects.
Cambridge University Press.
Enqvist, J., Graham, M., & Nikkinen, J. (2014). The impact of working capital management
on firm profitability in different business cycles: Evidence from Finland. Research in
International Business and Finance, 32, 36-49.
Finnie, J. (2012). The role of financial appraisal in decisions to acquire advanced
manufacturing technology. Accounting and Business Research, 18(70), 133-139.
Gitman, L. J., Juchau, R., & Flanagan, J. (2015). Principles of managerial finance. Pearson
Higher Education AU.
Goldmann, K. (2017). Financial liquidity and profitability management in practice of polish
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