The risk analysis using Monte Carlo simulation technique is demonstrated with a hypothetical example of a BOT road project. First of all, the probability distribution functions for the inputs required to estimate the project outcome, IRR, are to be defined. The inputs (independent variables) are estimated capital and operating costs, revenues, and possible concession period. For each of the input, the estimated range of the values along with their associated probabilities is given below. Table 5 shows the details relating to the normal function for each of the input.

Table: 5 Discrete Probability Values of the Independent Variables

In order to initiate the simulation, the values of the inputs are assigned a series of numbers in order to facilitate sampling from a two digit random number table. For example, the operating cost value of 1500 is assigned the series of number from 00 to 19, while 1700 is assigned the series of number from 20 to 69, and 70 to 99 to the value 1800. Similarly, the series of two digits numbers are assigned to the various values of the other remaining inputs.

The outcome of the project in terms of internal rate of return is dependent on the independent variables capital cost, operating cost, annual revenue, and concession period. The internal rate of return is obtained by equating the present value of the project revenue with the present value of the project costs.

In order to compute the project IRR, a sample of four two digits number from a random number is taken. For example, the four two digits are 27, 15, 56, and 34. The corresponding operating cost values for these four two digits numbers are 1700, 1500, 1700, and 1700. In the similar fashion the values for the remaining input are also selected. Using the input value from the sample for each of the inputs, the project IRR is computed. Table 6 shows the IRR computed using the input values for a single sampling.

Table: 6 Results of the Simulation

In the similar fashion, a large number of samples (say about 100 samples) can be drawn to estimate the probability distribution of the project outcome, IRR. The range of probability distribution will reflect the impact of the risks on the project outcome and will also give a measure of the chance that project outcome will fall within a given range which will help them in making decision on selecting the project.