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Risk Assessment Models - Coggle Diagram
Risk Assessment Models
Sensitivity analysis
Non-probabilistic approach used in investment appraisal that allows the analysis of changes in assumptions made in the forecast
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
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The lower the sensitivity margin, the more sensitive the decision to the particular variable under consideration
Advantages
The analysis is based on a simple theory, can be calculated on a spreadsheet and is easily understood
Identifies areas and estimates crucial to the success of the project, these critical areas are carefully monitored if the project is chosen
Provides information to allow management to make subjective judgements based on the likelihood of the various possible outcomes
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Disadvantages
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Only provides information to help managers make decisions, it is not a technique in itself for making a decision
Scenario analysis
Provides information of possible outcomes for the proposed investment by creating various scenarios that may occur
Evaluates the expected value of a proposed investment in different scenarios expected in a certain situation
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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
Seveal 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
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Simulation modelling
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)
Assigns random number and probability statistics to each variable that might affect the success of failure of a proposed project
Computer modelling repeats the decision many times, calculating a different NPV each time
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The resulting set of NPVd can be used to show how the NPV varies under the influence of all the variable factors
A more informed decision can then be taken depending on the managements attitude to risk, this approach can also be used to test the vulnerability of outcomes to possible variations in uncontrolled factors
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Expected NPV
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Most investment appraisal decisions are based on forecasts which are subject to uncertainties resulting in multiple outcomes
Imperative that these uncertainties are reflected in the investment decision, these cn be captured by assigning a probability to each outcome
The project performance is evaluated based on its expected value derived on a probability driven cash flow
Probalities
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Investment managers can assign different probabilities based on their experience and market research - these should be accepted if they are backed up by experience, understanding and good judgement
Probabilitties in an investment decision are measured on risk and return metrics, these measures are
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Expected value
The expected value is the average value of the outcome, calcaulted on probability estimates
The methodology is
- The probability of an outcome and value of that outcome is specified
- The expected value of each outcome is calculated
- All the expected values are added with each probability to arrive at the expected value
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Expected NPV
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Based on NPV under different scenarios, provability weighted to adjust for uncertainties in each of these scenarios
A project with a positive ENPV will be accepted, taking the guesswork out of decision
EPNV produces a more realistic picture by considering any uncertainties inherent in project scenarios
Advanatages
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A positive ENPV increases shareholders wealth if a project proceeds and outcomes follow expectations
Diadvanatges
Expected value and ENPV are measures of return, they do not take the volatility or the risk of a project into consideration
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Standard deviation
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The higher the standard deviation, the larger the variance and the higher the risk of a project
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Calcuated
- Deviation (d) = NPV - Expected value
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- The variance is calculated as pd2 = profitability x squared deviations
- The standard deviation is the square root of the variance
The coefficient of variation is the ratio of standard deviation to the mean and measures the extent of variability or the dispersion of data points in a dataset in relation to the mean of the population
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Event tree diagrams
Commonly used for risk mapping when a project or task has multiple outcomes with different probabilities
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If two events are independent, the outcome of one has no effect on the outcome of the other
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Limitations
It is not normally realistic to identify the various possible outcomes and then attach probabilities to each of them
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An initiating event is identified, the analysis is limited and dependent on one initiating event that leads to further sequential events