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Transcript of TISA June 2012 ACCA P4 Mark Fielding-Pritchard mefielding.com1.
mefielding.com 1
TISA June 2012ACCA P4
Mark Fielding-Pritchard
mefielding.com 2
Part A
Steps
Take of Elfu, take out Elfu gearing
Gives for new industry. Complication here is that there are combined industries. Assume all a weighted average
for project finance to get of project
Put in CAPM , get
Combine with to get WACC
That is your discount rate
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Elfu . Therefore 1.4 is a weighted average of the 2 divisions
1.4= (1.25 x 75%) + (components x 25%)
components = 1.86
= 1.86 (480/ (480 + (96 x 75%)) = 1.62
Now put in Tisa’s capital structure
1.62= (18000/18000+(3600x75%))= 1.86
= (1.86x 5.8%) + 3.5%= 14.3%
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WACC
=14.3% = 4.5% post tax WACC/ Discount rate= (14.3 x 18/18+3.6) + 4.5
(3.6/18+3.6) = 12.7 (use 13 in exam)
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Part B IRR10% 20%
0 (3800) (3800) (3800)
1 1220 1109 1016
2 1153 952 800
3 1386 1041 802
4 3829 2615 1846
1917 664
IRR = 10% + ((1917/1917-664)) = 25.3% (27% from excel)
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Part B MIRR
@13%
T0 (3800) (3800)
T1 1220 1760
T2 1153 1472
T3 1386 1566
T4 3829 3829
8673
Assume all inflows occur at the end of the project
Therefore 3800 k= 23%
13% is the WACC calculated in a)
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Part B Conclusion
IRR% MIRR%
Omega 25.3% 23%
Zeta 26.6 23.3
Zeta has a higher IRR so maybe choose this one, though difference is marginalConsider duration analysis as Omega has higher cashflows in early yearsMIRR is irreverent as the project has only 1 IRRI recommend Omega
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Value at Risk VaR was developed on trading desks on Wall St. Our fear is that the market crashes 20+% in on
day. We know this will happen 1 day every 3 years Our aim is to maximise the risk on the 749 days when this doesn’t happen and minimise it on
the 1 day it does This is done by stress testing portfolios and VaR is 1 technique for highlighting potential
problems Trading desks do this after the close of business every day so we assume no trading and
normal distributions We set a maximum permitted allowable daily loss and then statistically calculate the
probability of exceeding that loss The problem is that market crashes occur so infrequently they will fall outside the norm so VaR
will specifically exclude them, & Data at the <1% end of the probability tail will probably not behave rationally,& Models may have been designed where we link to one stock, say Apple, the probability that
Apple falls 20% is immaterial and the system does not aggregate. The sum of individual risks may be greater than the whole
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TISA
-4 -3 -2 -1 0 1 2 3 40
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
Chart Title
Calculating the probability of this being greater than 1%
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Tisa Look at stats tables, we need 0.49 from the body of the table
On the side we get this at 2.33. Therefore 2.33 standard deviations will give us 99% confidence
2.33 x 800000 = 1864
Therefore we set our VaR at 1864
In our example it tells us in principle that we are 99% confident that in 1 time period losses will not exceed 1864
Over a 5 year period we get 1864 x = $4168
Our risk is a function of volatility which is measures as variance. Standard deviation is the so we must take the as well