Home » **ANALYSIS OF RISK AND UNCERTAINTY**

Certainty-Equivalent Approach
The certainty-equivalent approach (CEA), as an alternative to the risk-adjusted rate method, overcomes some of the weaknesses of the latter method. Under the former approach, the riskiness the project is taken into consideration by adjusting the expected cash flows and not the discount rate. This method eliminates the problem arising out of the inclusion of risk premium in the discou

Evaluation
The Risk-adjusted Discount Rate Approach to incorporate risk in the capital budgeting analysis has certain virtues. First, it is simple to calculate and easy to understand. Moreover companies in actual practice apply different standards of cost of capital for different projects. It has, therefore, the merit of operational feasibility.
However, it is beset with certain operational and conceptual diffic

Accept reject Decision
The Risk-adjusted Discount Rate Approach can be used with both the NPV and the IRR. If the NPV method is used to evaluate capital expenditure decision. NPV would be calculated using the risk-adjusted rate. If the NPV is positive the proposal would qualify for acceptance. A negative NPV would signify that the project should be rejected. In case of the IRR as a decision criterion, the inter

RISK EVALUATION APPROACHES
Once the nature of risk is understood and its quantum estimated, it is to be incorporated within the decision making framework. This section examines the popular techniques to handle risk. They are:
1. Risk-adjusted Discount Rate Approach
2. Certainty-Equivalent Approach
3. Probability Distribution Approach
4. Decision-tree Approach.
Risk-adjusted Discount Rate Approach
‘The Risk-a

Coefficient of Variation: A Relative Measure of Risk
Standard deviation can be misleading in comparing the uncertainty of alternative projects, if they differ in size. The coefficient of variation (V) is a correct technique in such cases. It is calculated as follows:
The coefficient of variation for projects X and Y are 0.516 (Rs 10,756.4 + Rs 20.848) and 2,06 (Rs 43,026 + Rs 20,848). The higher the coeffici

Standard Deviation: Absolute Measure of Risk
In statistical terms, standard deviation is defined as the square root of the mean of the squared deviation, where deviation is the difference between an outcome and the expected mean value of all outcomes. Further, to calculate the value of standard deviation, we provide weights to the square of each deviation by its probability of occurrence.
Assume there are n pos

Precise Measures of Risk: Standard Deviation and Coefficient of Variation
Assigning probabilities to cash flow estimates, as a measure of variability of future returns, represents a further improvement over sensitivity analysis, which, as already mentioned was itself superior to the method which involved the estimation of future cash flows in the form of a single figure. The assignment of probabilities and the c

SIMULATION
Simulation is a statistical technique employed to have an insight into risk in a capital budgeting decisions, This technique applies predetermined probability distributions and random numbers to estimate risky outcomes.
A simulation model is akin to sensitivity analysis as it attempts to answer what is questions. However, the advantage of simulation is that, it is, more comprehensive than sensitivity a

Assigning Probability
It has been shown above that sensitivity analysis provides more than one estimate of the future return of a project. It is, therefore, superior to single figure forecast as it gives a more precise idea regarding the variability of the returns. But it has a limitation in that it does not disclose the chances of occurrence of these variations. To remedy this shortcoming of sensitivity analys

Sensitivity Analysis
One measure which expresses risk in more precise terms is sensitivity analysis. It provides information as to how sensitive the estimated project parameters, namely, the expected cash flow, discount rate and the project life are to estimation errors. The analysis on these lines is important as the future is always uncertain and there will always be estimation errors. Sensitivity a takes care