Thursday, July 29, 2010


Simulation Analysis

The sensitivity analysis and scenario analyses are quite useful to understand the uncertainty of the investment projects. But both approaches suffer from certain weakness. They do not consider the interactions between variables and also, they do not reflect on the profitability of the change in variables.

Simulation analysis considers the interactions among variables and profitability of the change in variables. It does not give the projects net present value as a single number rather it computes the profitability distribution of value. The simulation analysis is an extension of scenario analysis. In simulation analysis a computer generates a very large number of scenarios according to the profitability distributions of the variables. The analysis involves the following steps:
  • First, you should identify variables that influence cash inflows and outflows. 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, product life cycle, and terminal variable.
  • Second, specify the formulae that relative variables. For example, revenue depends on by sales volume and price; sales volume is given by market size, market share, and market growth. Similarly, operating expenses depend on production, sales and variable and fixed costs.
  • Third, indicate the profitability distribution for each variable. Some variables will have more uncertainty than others, For example, it is quite difficult to predict price or market growth with confidence.
  • Fourth, develop a computer programme that randomly selects one variable from the profitability distinction of each variable and uses these values to calculate the projects’ net present value. The computer generates a large number of such scenarios, calculates net present values and stores them. The stored values are printed as a profitability distribution of the projects’ values along with the expected value and its standard deviation. The risk-free rate should be used as the discount rate to compute the projects’ value. Since simulation is performed to account for the risk of the projects’ cash flows, the discount rate should reflect only the time value of money.

That analysis is a very useful technique for risk analysis. Unfortunately, its practical use is limited because of a number of shortcomings. First, the model becomes quite complex to use because the variable depends are interrelated with each other, and each variable depends on its values in the previous periods as well. Identifying all possible relationships and estimating probability distribution is a difficult task; its time consuming as well as expensive. Second, the model helps to generating a profitability distribution of the projects’ net present values. But it does not indicate whether or not the project should be accepted. Third, considers the risk of any project in isolation of other projects.

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