Monte Carlo Simulation

Monte Carlo analysis may be used to determine a project’s NPV with the real options by building all of the possible payoffs under the real options into the Monte Carlo analysis model. The result is an averaged approximate NPV with the real options.

A Monte Carlo simulation employs computer simulation to help decision-makers consider all possible combinations of project outcomes. When used in capital budgeting, this simulation utilizes a model where all the variables are defined: market size, product price, market share, unit variable cost, and fixed cost. The probabilities of each possible outcome for each variable are specified and the effect of all the possible events on subsequent years’ results is determined. After all relevant information is built into the model, the computer creates random scenarios and calculates the resulting cash flows for each period. After multiple iterations, an estimate of the probability distributions of the project’s cash flows emerges. The accuracy of the estimate will depend upon the accuracy of the model and the interrelationships among the variables.

The probability distributions of the cash flows help an analyst calculate expected cash flows, which can then be discounted to find their present values. Several NPVs are calculated based on the random choices of variables, and the NPVs are averaged to get an approximate NPV for the project.

However, because a Monte Carlo simulation emphasizes expected value, its results can be less than realistic if variables such as market growth, market share, costs, and so forth diverge from expected levels.