14. Risk assessment in investment appraisal techniques Flashcards
Risk assessment models
All companies face the risk of variable returns. The actual outcome could be better (from upside potential) or worse than expected (from downside risk exposure). For example, a company cannot predict future sales with certainty because they could be higher or lower than expected. An important aspect of risk assessment is to identify and assess potential sources of risk in terms of their potential impact on the company and how likely (probable) they are.
There are several risk assessment models that incorporate risk into decision
making. These techniques involve both non-probabilistic as well as probabilistic
approaches (that use a range of possible values) to project appraisal. They include:
Non-probabilistic approaches
– sensitivity analysis
– scenario analysis
– simulation modelling
Probabilistic approaches
– expected net present value (ENPV) and standard deviation
– event tree diagrams
Risk-adjusted discount rate
Sensitivity analysis
Sensitivity analysis is a non-probabilistic approach used in investment appraisal that allows the analysis of changes in assumptions made in the forecast. It is a tool for quantitative risk assessment that predicts the outcome of a decision by ascertaining the most critical variables and their effect on the decision. It examines how sensitive the returns on a project are to changes made to each of the key variables, such as any increase or decrease in:
capital costs
projected sales volumes
variable costs
What is the methodology for sensitivity analysis?
The methodology follows the steps below.
1. Specify a base case situation and calculate the NPV of the project based on the best estimates and assumptions. Only projects that generate a positive NPV are accepted.
- Calculate the percentage change (or sensitivity) of each of the variables that would result in the breakeven position (with a NPV of zero). Any further change resulting in negative NPV would change the decision.
For example, what impact would the projected sales have on NPV if they decreased or increased by 10%? What if demand fell by 10% compared to the original forecasts? Would the project still be viable? How much of a fall in demand can be accepted before the NPV falls below zero or below the breakeven?
Sensitivity margin = (NPV ÷ PV of flow under consideration) × 100%
The lower the sensitivity margin, the more sensitive the decision to the particular
variable under consideration. A small change in the estimate could change the
NPV from positive (accept) to negative (reject).
Adavantages and disadvatages of sensitivity analysis
Advantages of sensitivity analysis
The analysis is based on a simple theory, can be calculated on a spreadsheet and is easily understood.
It identifies areas and estimates crucial to the success of the project. These critical areas are carefully monitored if the project is chosen.
It provides information to allow management to make subjective judgements based on the likelihood of the various possible outcomes.
The analysis is used by a range of organisations. For example, this technique is popular in the National Health Service (NHS) for capital appraisal.
4.2 Disadvantages
The technique changes one variable at a time which is unlikely to happen in reality. For example, if the cost of materials goes up, the selling price is also likely to go up. However, simulation techniques (discussed later) take into consideration changes in more than one variable at a time.
It also does not identify other possible scenarios.
It considers the impact of all key areas (one at a time). The amount of
information may overwhelm the decision maker.
The probability of each of the assumptions is not tested.
It only provides information to help managers make decisions. It is not a
technique in itself for making a decision.
Scenario analysis
Scenario analysis provides information on possible outcomes for the proposed investment by creating various scenarios that may occur. It evaluates the expected value of a proposed investment in different scenarios expected in a certain situation.
As with sensitivity analysis, the method involves calculating NPV. Unlike
sensitivity analysis, scenario analysis also calculates NPVs in other possible
scenarios or ‘states of the world’. The most used scenario analysis involves
calculating NPVs in three possible states of the world: a most likely view, an
optimistic view and a pessimistic view.
By changing a number of key variables simultaneously, decision makers can examine each possible outcome from the ‘downside’ risk and ‘upside’ potential of a project, as well as the most likely outcome. However, this technique has several key weaknesses:
as the number of variables that are changed increases, the model can become increasingly difficult and time consuming;
it does not consider the probability of each ‘state of the world’ occurring
when evaluating the possible outcomes; and
it does not consider other scenarios that may occur.
Simulation modelling
The Monte Carlo simulation method is an investment modelling technique
that shows the effect of more than one variable changing at the same time.
Complex structures of capital investment are investigated through simulation
techniques, particularly modelling the impact of uncertainty. Simulation models
are programmed on computers to deal with variable factors by use of random
numbers.
The model identifies key variables that drive costs and revenues (such as market
size, selling price, initial investment, changes in material prices, rates of use
of labour and materials and inflation). It then assigns random numbers and
probability statistics to each variable that might affect the success or failure of
a proposed project. For example, if the most likely outcomes are thought to
have a 50% probability, optimistic outcomes a 30% probability and pessimistic
outcomes a 20% probability, then a random number representing those
attributes can be assigned to costs and revenues in those proportions. These
randomly selected values are used to calculate the project NPV. NPV varies under influence of all variable factors.
The key weaknesses of this technique are as follows.
It is not a technique for decision making, rather providing information about the possible outcomes upon which management makes a decision.
It is a complex method which is not simple to calculate.
The time and costs involved may outweigh the benefits gained from the
improved decision making.
Expected net present value
Uses probabilities, the project performance is evaluated based on its expected value derived on a probability-driven cash flow. Probabilities in an investment decision are measured on return and risk metrics.
These measures are:
expected value and expected net present value (ENPV): these measure return
standard deviation: this measures risk or volatility
Expected value
The expected value is the average value of the outcome, calculated on
probability estimates. The methodology is as follows.
1. The probability of an outcome and value of that outcome is specified.
2. The expected value of each outcome is calculated.
3. All the expected values are added with each probability to arrive at the
expected value.
The formula for calculating expected value is:
Expected value = ΣPX
Where:
Σ = the sum of
P = the probability of outcome
X = the value of the outcome
Expected net present value
Expected net present value (ENPV) is a capital budgeting and appraisal
technique. It is a simple tool to evaluate the feasibility of a project. It is based
on net present value under different scenarios, probability weighted to adjust
for uncertainties in each of these scenarios. A project with a positive ENPV will
be accepted, taking the much of guesswork out of decision making. Unlike
traditional NPV, ENPV produces a more realistic picture by considering any
uncertainties inherent in project scenarios.
7.3 Advantages
ENPV provides a clear ‘rule’ to aid decision making.
The expected value and ENPV tools are simple and easy to calculate.
A positive ENPV increases shareholder wealth if a project proceeds and
outcomes follow expectations.
Limitations
Expected value and ENPV are measures of return. They do not take the
volatility or the risk of a project into consideration. Variability (volatility) or
dispersion is measured by standard deviation.
While ENPV takes probabilities into account, they are subjective and may
be difficult to estimate.
Event tree diagrams
Event tree diagrams are a commonly used tool for risk mapping when a
project or task has multiple outcomes with different probabilities. Tree diagrams
represent all possible outcomes of an event, allowing managers to calculate
their probability. Each branch in a tree diagram represents one possible outcome
of the project. If two events are independent, the outcome of one has no effect
on the outcome of the other.
This diagrammatic approach allows all possible outcomes to be accurately
mapped. The construction of event tree diagram follows the steps below:
1. An initiating event or a project that leads to further sequential events is
identified (such as a product launch).
2. The sequential events or outcomes associated with the specific scenarios
are identified, building the event tree diagram.
3. Probabilities for the sequential events (rate of success and failure) are
determined.
4. The expected value for each sequential event is calculated.
5. The sum of all expected values gives the expected value for the project.
8.1 Limitations
It is not normally realistic to identify the various possible outcomes and
then attach probabilities to each of them.
Success or failure probabilities are difficult to find.
Event tree diagrams require an analyst with practical training and
experience.
Event tree diagrams are not efficient where many events must occur in
combination.
All events are assumed to be independent, which may not be always the
case.
An initiating event is identified. The analysis is limited and dependent on
one initiating event that leads to further sequential events.
Portfolio management
A portfolio is a mix of investments or projects in a company. It can refer to external or internal portfolios of investments or projects. When a company has surplus funds available, it may make external investments in a portfolio of assets such as banknotes, bonds, debentures and stocks. These external portfolios are also referred to as passive investments as they do not entail active management from the issuing company. An internal portfolio refers to a group of projects managed together to achieve an organisation’s strategic objectives.
Objectives of portfolio management
The objective of portfolio management is to select the right investments in the right proportions to generate optimum returns while minimising risk. The key elements of a good portfolio are listed below.
Return: the portfolio should yield steady returns that at least match the opportunity cost of the funds invested. In general, the better the growth prospects of the company, the better the expected returns.
Risk reduction: minimisation of risks is the most important objective of portfolio management. A good portfolio tries to minimise the overall risk to an acceptable level in relation to the levels of return obtained.
Liquidity and marketability: it is desirable to invest in assets which can be marketed without difficulty. A good portfolio ensures that there are enough funds available at short notice.
Tax shelter: the portfolio should be developed considering the impact from taxes. A good portfolio enables companies to enjoy a favourable tax shelter from income tax, capital gains tax and gift tax.
Appreciation in the value of capital: a balanced portfolio must consist of certain investments that appreciate in value, protecting investor from any erosion in purchasing power due to inflation.
Elements of portfolio management, asset allocation and diversification
Effective portfolio management increases the probability of higher returns through risk reduction. Portfolio theory helps investment managers to construct portfolios that best meet the requirements of investors in terms of risk and return. Portfolio management reduces risk and uncertainties through a number of strategies.
Asset allocation
Effective portfolio management increases the probability of higher returns through risk reduction. Portfolio theory helps investment managers to construct portfolios that best meet the requirements of investors in terms of risk and return. Portfolio management reduces risk and uncertainties through a number of strategies.
Diversification
Spreading the risk across multiple investments within an asset class is known as diversification. This is based on the well-known rule of thumb ‘don’t put all
your eggs in one basket’. Effective diversification includes investments across
different asset classes, securities, sectors and geography. This will not only help
to boost the returns but also lower the level of risk of a portfolio.
For example, a portfolio that is comprised of only bonds carries less risk (and
lower returns) than a portfolio of only equities. If the percentage of equities is
increased to, say, 20%, the risk of the portfolio increases but it will also increase
the potential returns. A unit trust typically spreads its funds among a large
number of investments.
Rebalancing
Rebalancing is this continuous process of comparing portfolio weightings with planned asset allocation. Rebalancing is usually done on an annual basis.
Portfolio risk and return and correlation
The relationship between the risk and return of the individual investments determines the overall risk and return of the portfolio. A company can measure the average return for the portfolio by calculating the correlation among the individual investments.
Correlation, in terms of portfolio management, is a statistical tool that measures the degree to which two securities move in relation to each other. One reason for this might be that two securities have generally opposite reactions to the same external news or event. For instance, financial stocks such as banks or insurance companies tend to get a boost when interest rates rise, while the real estate and utilities sector get hit particularly hard when interest rates increase.
Correlation is computed by using the correlation coefficient, which has a value that ranges between minus 1 and plus 1. The correlation coefficient is a statistical measure of the strength of the relationship between the relative movements of two variables. The values range between minus 1.0 and 1.0. You will not need to know how to calculate a correlation coefficient, but you do need to understand the meaning of the results.
There are three possible results of a correlational study.
Positive correlation (Coefficient = 1)
The correlation of investments in a portfolio is positive (or +1) when their prices move in same direction or offer same kind of return in the specified period.
Usually, the investments in the same industries, or with same set of products that can substitute each other, demonstrate positive correlation. For example, if the price of stock A increases by 5% and price of stock Z also increases by 5% in a month, stock A and stock Z are said to have a positive correlation of +1. When a company invests in Stock A and Z at the same time, the portfolio price will increase by 5% (assuming the same amount of investment in both stocks).
Negative correlation (Coefficient = minus 1)
The correlation of investments in a portfolio is negative (or minus 1) when their prices move in opposite directions. There is an inverse relationship between two variables. Usually, the investments in industries which are dependent on each other for raw materials or services offer negative correlation. When the price of oil rises, it is likely to result in the rise of the price of an oil company’s shares (ignoring other factors), but the shares of companies such as airlines are likely to fall in value.
Zero correlation
Zero correlation (Coefficient = 0):
Zero correlation applies where underlying investments have no relationship that
indicates any kind of correlation. Usually, investments in different asset classes or
different geographic locations have zero correlation. With zero correlation, each
investment performance holds the price and risk without any dependency on
the performance of other investments.
The efficient frontier
The ‘efficient frontier’ is a modern portfolio theory tool that shows investors the best possible return they can expect from their portfolio for a defined level of risk. The
efficient frontier aims for optimum correlation between risk and return.
The portfolio manager scouts for the investment opportunities which offer optimum correlation to maximise return for the portfolio. The efficient frontier is curved (see Figure 14.4), representing a diminishing marginal return to risk.
Portfolios that do not provide enough return for the level of risk are considered
as suboptimal (they lie below the efficient frontier). Each point on the efficient
frontier line represents optimal portfolio.
The applicaiton and limitation of portfolio theory
The core principles of portfolio theory are based on asset allocation, diversification and rebalancing – diversifying away the risk with carefully selected investments or optimum portfolios. It can be applied to a selection of projects and company ventures as well as securities. Companies can reduce risk and stabilise profits by investing in negatively correlated companies.
Limitations of portfolio theory
It is a single-period framework.
Probabilities are only estimates.
It is based on several assumptions, including:
– investors are risk-averse and behave rationally
– the risk of bankruptcy, legal and administrative constraints are ignored
Portfolio theory assumes that the correlation between assets is constant.
This may not be applicable in the real world as every variable is constantly
changing.
Correlation analysis requires computation of the coefficient of each underlying security. It is very complex in terms of gathering historical numbers, model selection and calculating with accuracy.
The theory does not assume any tax payouts or legal and administrative costs. These are essential factors in determining investment decisions.
The theory ignores the timeframes (short term, medium term or long term) of the investments. Return expectations may change depending on these timeframes. Some randomly selected portfolios may have performed better than optimally selected portfolios, at least for a short time.
Despite the availability of software programs to perform the calculations, the portfolio model is still not widespread as portfolio managers are sceptical about the accuracy of the forecast data. They may prefer to use their own judgement in selecting investments.
