Academic journal article Journal of Financial Education

# An Introductory Application of Monte Carlo Simulatoin in Capital Budgeting Analysis

Academic journal article Journal of Financial Education

# An Introductory Application of Monte Carlo Simulatoin in Capital Budgeting Analysis

## Article excerpt

There is a lack of coverage of an application of Monte Carlo simulation in capital budgeting in introductory level finance textbooks. In more advanced level textbooks, the application is not presented in an easy to understand fashion for students with limited technical background. In this paper, we seek to present an easy application of Monte Carlo simulation in capital budgeting analysis that can be performed using Microsoft Excel alone. In addition, we illustrate that Monte Carlo simulation provides an unbiased estimation of the expected net present value as well as other key input variables. However, we demonstrate that Monte Carlo simulation provides more useful information to a decision maker as compared to conventional scenario or sensitivity analysis. Finally, we provide evidence that, due to the assumption of scenario analysis, the probability of observing the best and worst case NPVs will be very slim. This represents a major weakness of scenario analysis.

(ProQuest: ... denotes formulae omitted.)

INTRODUCTION

The key inputs in a capital budgeting analysis using discounted cash flows (DCF) are the projected future cash flows. These projected cash flows depend on assumptions made regarding forecasted unit sales, unit sales price, variable costs and fixed costs. If these forecasts are inaccurate, the resulting computation of Net Present Value (NPV) will likely be incorrect, leading to a suboptimal capital budgeting decision. Conventional DCF analysis is based on deterministic modeling using single point estimates of expected values of unit sales, sale price, variable cost per unit, and fixed operating costs. However, the expected value is often not easily determinable. To compensate forthis inherent uncertainty in the estimation process, the decision-maker might incorporate scenario or sensitivity analysis by asking a series of ?what-if ? questions. Nevertheless, there is a problem associated with conventional scenario or sensitivity analysis. Even though we have a sense of the sensitivity of the NPV to each scenario or variable, we are still in the dark as to which scenario or value for a given variable is most likely to occur. Monte Carlo simulation is a technique that can overcome the limitations of conventional scenario and sensitivity analysis. Monte Carlo simulation in capital budgeting analysis was first promoted by Hertz (1964) in his seminal article on risk analysis in capital investment.

Monte Carlo simulation is apowerful analytical tool which provides more useful information as compared to conventional sensitivity analysis or scenario analysis. However, there is a general lack of coverage of how to apply Monte Carlo simulation techniques to capital budgeting analysis. Many textbooks geared for undergraduate courses in corporate finance outline sensitivity analysis and scenario analysis in great detail, but all make only cursory or no reference to Monte Carlo simulation. For example, we surveyed three best selling undergraduate corporate finance textbooks written by the following authors: (i) Ross, Westerfield, and Jordan (2009); (ii) Brigham and Houston (2009); (iii) Block, Hirt, and Danielsen (2010). The first two texts explain in great detail the techniques of sensitivity analysis and scenario analysis to measure risk in capital budgeting. However, none of these three books geared to undergraduate students gives a detailed description of the Monte Carlo simulation technique with the help of an example. Alternatively, three popular corporate finance texts geared to graduate students, namely (i) Ehrhardt and Brigham (2008); (ii) Ross, Westerfield, and Jaffe (2009), (iii) Brealey and Myers, and Allen (2010) provide a more detailed but rather complicated discussion of the Monte Carlo simulation approach as applied to capital budgeting. Thus, it appears that there is a very limited coverage of the Monte Carlo simulation approach among undergraduate texts of corporate finance.

Unfortunately, there is also not much written in the academic literature on Monte Carlo simulation in capital budgeting analysis. …

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