1.2 Sources of risk in projects The major risks to the success of an investment project will be the variability of the future cash flows.. The cash flows, probabilities, or cost of capi
Trang 1OVERVIEW
Objective
Ü To appraise investment projects where the outcome is not certain
RISK AND UNCERTAINTY
STATISTICAL MEASURES
SENSITIVITY
ANALYSIS
Ü Definition
Ü Method
Ü Advantages
Ü Limitations
SIMULATION
Ü Use
Ü Stages
Ü Advantages
Ü Limitations
Ü Expected values
Ü Standard deviation
Ü Definitions
Ü Sources of risk REDUCTION OF RISK
Trang 21 RISK AND UNCERTAINTY
1.1 Definition
1.1.1 Risk
A condition in which several possible outcomes exist, the probabilities of
which can be quantified from historical data
1.1.2 Uncertainty
The inability to predict possible outcomes due to a lack of historical data
being available for quantification
1.2 Sources of risk in projects
The major risks to the success of an investment project will be the variability of the future cash flows This could be the variability of income streams or the variability of cost cash flows or a combination of both
Definition
The analysis of changes made to significant variables in order to determine
their effect on a planned course of action
The cash flows, probabilities, or cost of capital are varied until the decision changes, i.e the NPV becomes zero This will show the sensitivity of the decision to changes in those
elements
Therefore the estimation of IRR is an example if sensitivity analysis, in this case on the cost
of capital
Sensitivity analysis can also be referred to as “what if?” analysis
2.1 Method
Step 1 Calculate the NPV of the project on the basis of best estimates
Step 2 For each element of the decision (cash flows, cost of capital)
calculate the change necessary for the NPV to fall to zero
The sensitivity can be expressed as a % change
For an individual cash flow in the computation
Trang 3Sensitivity = 100%
considered flow
of PV
Commentary
For change in sales volume, the factor to consider is contribution This may involve
combining a number of flows
Example 1
Williams has just set up a company, JPR Manufacturing Ltd, and estimates its
cost of capital to be 15% His first project involves investing in $150,000 of
equipment with a life of 15 years and a final scrap value of $15,000
The equipment will be used to produce 15,000 deluxe pairs of rugby boots per
annum generating a contribution of $2.75 per pair He estimates that annual
fixed costs will be $15,000 per annum
Required:
(a) Determine, on the basis of the above figures, whether the project is
worthwhile
(b) Calculate what percentage changes in the factors would cause your
decision in (a) change
(i) initial investment
(ii) volume
(iii) fixed costs
(iv) scrap value
(v) cost of capital
Comment on your results
Ignore tax
Trang 4Solution
(a) Time Cash flow DF @ 15% PV
0
1 − 15
1 − 15
15
Initial cost Contribution Fixed costs Scrap value
_
_
(b) The sensitivity of the decision in (a) can be calculated by expressing the
NPV as a percentage of the various factors
(i) Initial investment
Sensitivity =
(ii) Volume
The PV figure of contribution is directly proportional to volume
Sensitivity =
(iii) Fixed costs
Sensitivity =
(iv) Scrap value
Sensitivity =
(v) Sensitivity to cost of capital
This can be found by calculating the project’s IRR:
Year Cash flow factor Present value
0
1-15
15
(150,000) 26,250 15,000
1
_
Trang 5IRR = r
NPV NPV
NPV
1 2 2 1
−
=
2.2 Advantages of sensitivity analysis
X It gives an idea of how sensitive the project is to changes in any of the original estimates
X It directs management attention to checking the quality of data for the most sensitive variables
X It identifies the Critical Success Factors for the project and directs project management
X It can be easily adapted for use in spreadsheet packages
2.3 Limitations
W Although it can be adapted to deal with multi-variable changes, sensitivity is normally only used to examine what happens when one variable changes and others remain constant
W Assumes data for all other variables is accurate
W Without a computer it can be time-consuming
W Probability of changes is not considered.
3.1 Use of simulation
Simulation is a technique which allows more than one variable to change at the same time One example of simulation is the “Monte Carlo” method Calculations will not be required
in the exam, an awareness of the stages is sufficient
3.2 Stages in a Monte Carlo simulation
(1) Specify the major variables
(2) Specify the relationship between the variables
(3) Attach probability distributions to each variable and assign random numbers to reflect the distribution
(4) Simulate the environment by generating random numbers
Trang 6(5) Record the outcome of each simulation
(6) Repeat simulation many times to obtain a probability distribution of the likely outcomes
3.3 Advantages
X It gives more information about the possible outcomes and their relative probabilities
X It is useful for problems which cannot be solved analytically
3.4 Limitations
W It is not a technique for making a decision, only for obtaining more information about the possible outcomes
W It can be very time-consuming without a computer
W It could prove expensive in designing and running the simulation, even on a computer
W Simulations are only as good as the probabilities, assumptions and estimates made
4.1 Expected values
The quantitative result of weighting uncertain events by the probability of their occurrence
4.1.1 Calculation
Expected value = weighted arithmetic mean of possible outcomes
=∑x p(x)
Where x = value of an outcome, p(x) = probability of that outcome , ∑ = sum
Example 2
State of market Diminishing Static Expanding
Figures represent the net present value of projects under each market state in
$m
Required:
Determine which is the best project based on expected values
Trang 7Solution
Project 1 Expected value =
Project 2 Expected value =
Project 3 Expected value =
The best project based on expected values is
4.1.2 Advantages
X It reduces the information to one number for each choice
X The idea of an average is readily understood
4.1.3 Limitations
W The probabilities of the different possible outcomes may be difficult to estimate
W The average may not correspond to any of the possible outcomes
W Unless the same decision has to be made many times, the average will not be achieved;
it is therefore not a valid way of making a decision in “one-off” situations
W The average gives no indication of the spread of possible results, i.e it ignores risk
4.2 Standard deviation
A measure of variation of numerical values from a mean value
A measure of spread i.e it indicates the likely level of variation from an expected value
Exam questions are more likely to provide standard deviation for interpretation, rather than
to require its calculation
4.2.1 Calculation
σ = standard deviation = ∑(x−x)2 prob( x)
Prob (x) = probability of each observation
Note that variance = σ2
Trang 8Example 3
Using the information from Example 2, calculate the standard deviation for
each project
Solution
Project 1
Project 2
Project 3
4.2.2 Advantages
X It gives an idea of the spread of possible results around the average
X It can be used in further mathematical analysis, in particularly using Normal
Distributions.”
4.2.3 Limitations
W The calculation of standard deviation can be difficult
W The exact meaning is not widely understood by non-financial managers
Ways of reducing project risk:
Ü Setting a maximum payback period
Ü Use of a higher discount rate − therefore reducing the influence of distant cash flows
Ü Select projects with a combination of low standard deviation and acceptable average predicted outcome
Ü More effort directed to Critical Success Factors indicated by sensitivity analysis
Trang 9Key points
ÐExam calculations on project risk are likely to focus on sensitivity analysis
i.e finding the value of key variables at which NPV = 0
ÐAdjusting the discount rate to reflect a project’s risk is dealt with later in
the session on the Capital Asset Pricing Model (CAPM)
FOCUS
You should now be able to:
Ü distinguish between risk and uncertainty;
Ü evaluate the sensitivity of project NPV to changes in key variables;
Ü explain the role of simulation in generating a probability distribution for the NPV of a project;
Ü apply the probability approach to calculating expected NPV of a project and the
associated standard deviation
Trang 10EXAMPLE SOLUTIONS
Solution 1 — Sensitivity analysis
(a) Time Cash flow DF @ 15% PV
0
1 − 15
1 − 15
15
Initial cost Contribution Fixed costs Scrap value
(150,000) 41,250 (15,000) 15,000
1 5.847 5.847 0.123
(150,000) 241,189 (87,705) 1,845 _
5,329 _
The project is worthwhile as NPV is positive
(b) The sensitivity of the decision in (a) can be calculated by expressing
the NPV as a percentage of the various factors
(i) Initial investment
If the initial investment rises by more than $5,329, the project would be
rejected
Sensitivity =
000 , 150
329 ,
5 × 100 = 3.6%
(ii) Volume
The PV figure of contribution $241,189 is directly proportional to
volume If this PV is reduced by more than $5,329, the project would
be rejected
Sensitivity =
189 , 241
329 ,
5 × 100 = 2.2%
(iii) Fixed costs
Sensitivity =
705 , 87
329 ,
5 × 100 = 6.1%
Trang 11(iv) Scrap value
Sensitivity =
845 , 1
329 ,
5 × 100 = 289%
From the above calculations the decision to accept the project is
extremely sensitive to most of the figures given in the question The
project will be rejected in the event of small rises in the initial
investment or fixed cost figures or falls in contribution or volume It
could be seen, for instance, that the project just breaks even if fixed
costs become $15,000 × 1.06 = $15,900
The scrap value is relatively irrelevant to the investment decision – we
would have to pay to have the plant taken away before the project
would be rejected
(v) Sensitivity to cost of capital
This can be found by calculating the project’s IRR, which is probably
only marginally above 15%
Year Cash flow 16% factor Present value
0
1-15
15
(150,000) 26,250 15,000
1 5.575 0.108
(150,000) 146,344 1,620
(2,036) _
IRR = r
2 1
NPV NPV
−
2,036 + 5,329
= 15.7%
If the cost of capital rises from 15% to more than 15.7% the project
would be rejected
Solution 2 — Expected values
Project 1 Expected value = 100 × 0.4 + 200 × 0.3 + 1,000 × 0.3 = 400
Project 2 Expected value = 0 × 0.4 + 500 × 0.3 + 600 × 0.3 = 330
Project 3 Expected value = 180 × 0.4 + 190 × 0.3 + 200 × 0.3 = 189
Therefore, based on expected values, Project 1 should be adopted
Trang 12Solution 3 — Standard deviation
Project 1 (100−400)2×0.4+(200−400)2×0.3+(1,000−400)2×3
= 156,000 = 395 Project 2 (0−330)2×0.4+(500−330)2×0.3+(600−330)2×0.2
= 74,100 = 272
Project 3 (180−189)2×0.4+(190−189)2×0.3+(200−189)2 ×0.3
= 69 = 8.3