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My Approach to Teaching Capital Budgeting

Many of you, at some point in your career, will be called on to justify an investment of your company's money. The investment might be as simple as a new pump or it might be as complex as a new plant. Capital budgeting is the set of techniques for justifying such investments.

Like most (if not all) of you, my first exposure to capital budgeting came during my senior design class in chemical engineering. It was not called capital budgeting but rather was lumped under the name of engineering economics. Regardless of what the subject matter was called, it turned out to be some of the most valuable knowledge that I gained in college (along with statistics, by the way). It has been applicable to both my job and my personal finances.

The fundamental task in capital budgeting is to predict future cash flows from an investment. Surprisingly, capital budgeting the way we know it, using discounted cash flows, has been a practice in most companies only since the 1960s. Certainly, the rise of computers had something to do with the practice gaining popularity. Computers allowed rapid calculation of discount factors for each year and facilitated the analysis of multiple cases. Personal computers and the introduction of spreadsheet software (first Visicalc, then Lotus 1-2-3, and then Microsoft Excel) brought user-friendliness to the task and made it accessible to most professionals.

Practitioners of capital budgeting observed fairly early that point estimates of all factors used in calculating cash flows, a deterministic analysis, left much to be desired in terms of presenting the real risk of an investment, given the speculative nature of future cash flows. Consequently, about the same time that discounted cash flow became standard practice, some analysts began to apply the techniques of stochastic modeling to their calculations (see Hertz). Once again, the rise of personal computers and spreadsheets, and the introduction of spreadsheet add-ins such as @Risk, Crystal Ball, and Risk Detective made stochastic analysis accessible to most professionals.

Fundamentally, stochastic analysis is the representation of input variables as statistical distributions rather than as point estimates to project not a single outcome from a model but a statistical distribution of outcomes. Because capital budgeting depends on projecting future cash flows, and the future generally can only be discussed in terms of probabilities of events (except perhaps for events like the rising and setting of the sun) rather than as absolute outcomes, stochastic analysis is naturally extended to capital budgeting.

My goal in the material I present to you is to start you off right, so to speak, thinking of capital budgeting in all cases as a stochastic analysis rather than as a deterministic analysis. Indeed, you should learn that deterministic analyses can be dangerously misleading.

If I teach this material well, at the end of the lecture, you might actually wonder what the big deal is. Even in my own company, however, the techniques were not used until about 1997. Consequently, while I hope that you will indeed adopt a stochastic view of capital budgeting, do not underestimate the possibility that your co-workers or managers might not. Your ability to sell your investment ideas to these colleagues could depend as much on your ability to explain the concepts behind stochastic modeling as it does on being able to support your analysis. If you will take the time to learn this material and practice it through homework, I think you will be well-served in your future careers.

Updated: Sunday, March 7, 2010