Simulation is one of the best methods, which helps to evaluate the risks of investment decisions. This method makes use of probability distribution and imitates the performance of project under assessment . The simulation selects random observations from each distribution that affects the output of a project. The process continues as many times until the generation of a representative distribution of the probable outcome of the project. In the simulation approach, the inputs are various factors that affect the profitability of the project, while the output is a representative probability distribution of the internal rate of return or net present value of the project. The decision maker accepts the project after evaluating the probability distribution if the NPV is either greater than zero or the IRR is more than the required rate of return . The simulation approach is also popular by the name of scenario analysis as it analyzes the best and worst outcomes of every project.
Simulation approach helps the managers to take optimum decisions after analyzing the level of risks in any project. Simulation approach facilitates performing a sensitivity analysis since it cannot alone provide the total risk assessment of a project. Sensitivity analysis involves the determination of how the distribution of a possible net present value and internal rate of return gets affected by a change in any of the input variables for a specific project . In this analysis, the input variable gets changed one at a time assuming the rest of the variables as constant values. The result of the distribution after change in the variable undergoes a comparison with the possible distribution value before change in the variable, thereby ascertaining the impact of the change . Another common name for sensitivity analysis is what-if analysis.
Keown, A. J., Martin, J. D., Petty, J. W., & Jr., D. F. (2003). Foundations of Finance: The Logic and Practice of Financial Management, 6th Edition. San Francisco; CA: Prentice Hall.