Risk is inherent in almost every business more so in capital budgeting decisions as they involves costs and benefits extending over a long period of time during which many things can change in unanticipated ways for the sake of expository conveniences, we consider capital budget had the same risk as those of the existing investments on the firm.

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The single most difference between successful project and unsuccessful project is “Management of risk” before crisis happens. Hence the average cost of capital was used for evaluating every project. Investment proposals however differ in risk. Risk analysis one of the most complex and slippery aspects of capital budgeting. No single technology can be deemed as a best in all situations. Risks calls for, apperception of risks, understanding the sources of risks, restraining them using specific techniques, develop a positive attitude among the team members to handle risks.

There are varieties of techniques to handle risks in capital budgeting of the project that fall in two categories

1. Techniques that consider the standalone risk of a project.
2. Techniques that consider the risk of a project in the context of the firm or the project.

Process in risk analysis

§ Identification of risk.
§ Analysis of the risk.
§ Take corrective actions to minimize risk.
§ Allocation of appropriate contingency.

There are several sources of risk in a project. Some of the important risks in the project are, project-specific risk, competitive risk, industry specific risks, market risk, and international risk. Risks refer variability. It is a complex and multifaceted phenomenon.

A variety of measures have been used to capture different facets of risk. The more important ones are range, standard deviation, and coefficient of variance, semi variance. The principal measure used is Standard deviation, despite having some limitations. It is commonly used in finance. Reasons for using SD are...

1. If a variable is normally distributed, its mean and SD contains all the information about the probability distribution.
2. If the utility of money is represented by a quadratic function, then the expected utility is a function of the mean and SD.
3. SD is analytically easily tractable.

(a) Sensitivity analysis: Since the is uncertain, you may like to know what will happen to the viability of the project when some variables deviates from its expected values. It shows how robust or vulnerable a project is to change values of underlying variables. It explores how the variability of variables may be contained.

(b) Scenario analysis: If a variable are interrelated as they are more likely to be, it will be helpful to look at some plausible scenario, each scenario represents consisting combination of variables. The objective of scenario is to get the feel of what happens under most favourable conditions or most adverse configuration of key variables.

Procedure:

1. Select an important factor around which the scenario will be built.
2. Estimate the values of each variable in investment analysis for each scenario.
3. Calculate the net present value of each variable.

Best scenario: High demand, High selling price, and low cost etc.

Normal scenario: Average demand, Average selling price, and average cost etc.

Worst scenario: Low demand, Low selling price, and low cost etc.

(c) Simulation analysis: Information can be generated using the simulation analysis, which may be used for developing the profitability profile of a criterion of merit by randomly combining the value of the variables which have a bearing on the chosen criteria.

(d) Decision tree analysis: It is a useful tool for analyzing sequential decisions in the face of risk.

Steps, identification of problem and alternatives for the problems, delineation of decision tree, specification of probabilities and monetary outcomes, evaluation of various decision alternatives.

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