The purpose of investment appraisal is to assess the financial prospects of a proposed investment project. It is a methodology for calculating the anticipated come back based on cash flow forecasts of many, often inter-related, task variables. Risk emanates from the uncertainty encompassing these projected variables. The evaluation of task risk thus depends, on the one hand, on our ability to recognize and understand the nature of uncertainty surrounding the key task variables and on the other, on having the tools and methodology to process its risk implications on the come back of the project.
The first task of task evaluation is to estimate the future values of the projected variables.(Bierman, 1971, 12) Generally, we utilize information regarding a specific happening of the past to forecast a possible future conclusion of the same or similar event. The approach usually engaged in investment appraisal is to calculate a “best estimate” based on the available data and use it as an input in the evaluation model. These single-value estimates are usually the mode1 (the most probable outcome), the average, or a conservative estimate.
In selecting a single value although, a range of other probable outcomes for each task variable (data which are often of vital importance to the investment decision as they pertain to the risk aspects of the project) are not encompassed in the analysis. By relying absolutely on single values as inputs it is implicitly assumed that the values used in the appraisal are certain. The conclusion of the task is, thus, also presented as a certainty with no possible variance or margin of mistake associated with it.(Donald, 1998,54)
Question 2
Recognizing the fact that the values projected are not certain, an appraisal report is usually supplemented to encompass sensitivity and scenario analysis tests. Sensitivity analysis, in its simplest pattern, involves changing the value of a variable in alignment to test its impact on the final result. It is thus used to recognise the project's most important, highly sensitive, variables. Scenario analysis remedies one of the shortcomings of sensitivity analysis3 by allowing the simultaneous change of values for a number of key task variables thereby constructing an alternative scenario for the project. Pessimistic and optimistic scenarios are usually presented.
Sensitivity and scenario analyses compensate to a large span for the analytical limitation of having to strait-jacket a host of possibilities into single numbers. However useful though, both tests are static and rather arbitrary in their nature. The use of risk analysis in investment appraisal carries sensitivity and scenario analyses through to their logical conclusion. Monte Carlo simulation adds the dimension of dynamic analysis to task evaluation by making it possible construct up random scenarios which are consistent with the analyst's key assumptions about risk. A risk analysis application utilises a wealth of information, be it in the pattern of target data or professional attitude, to quantitatively describe the uncertainty surrounding the key task variables as probability distributions, and to calculate in a consistent ...