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Simulation Analysis

Simulation analysis is the identification of variables that influence cash inflows and outflows by developing a computer programmed that randomly selects on e value from the probability distribution of each variable and uses these values to calculate the project’s NPV. Simulation analysis is a very useful technique for risk analysis. Unfortunately. Its practical use is limited because of a number of shortcomings. It specifies the formulas that relate variables and indicates the probability distribution for each variable. Simulation analysis, like sensitivity or scenario analysis, considers the risk of any project in isolation of other projects. For example, revenue depends on by sales volume and price: sales volume is given by market size, market share and market growth. Sensitivity and scenario analyses are quite useful to understand the uncertainty of the investment projects. But both Approaches suffer from certain weaknesses.

One of the major shortcomings that are involved in this analysis are the model becomes quite complex to use because the variables are interrelated with each other and each variable depends on its value in the precious periods as well. Second, the model helps in generating a probability distribution of the project’s NPVs. But it does not indicate whether or not the project should be accepted. We know that if we consider the portfolio of projects, the unsystematic risk can be diversified. The computer generates a large; number of such scenarios, calculates NPVs and stores them. The stored value are primed as a probability distribution of the project’s NPVs along with the expected NPV and its standard deviation the rick-free rate should be used as the discount rate to computer the project’s cash flows, the discount rate should reflect only the time value of money.

A risky project may have a negative correlation with the firm’s other projects, and therefore accepting the project may reduce the overall risk of the firm. For example, when a firm introduces a new product in the market these variables are initial investment, market size, market growth, market share, price, variable costs, fixed costs fixed costs, product life cycle, and terminal value. The Monte carol simulation or simple the simulation analysis considers the interactions among variables and probability of the change in variables. It does not given the probability distribution of NPV. Some variables will have more uncertainty than others. For example, it is quite difficult to predict or market growth with confidence. The simulation analysis is an extension of scenario analysis. In simulation analysis a computer generates a very large number of scenarios according to the probability distributions of the variables. Similarly, operating expenses depend on production, sales and variable and fixed costs.