# Johnson Controls Inc. Capital Investments

Topics: Monte Carlo methods in finance, Investment, Decision tree Pages: 3 (1186 words) Published: November 13, 2013
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Assignment #2: “Johnson Controls Capital Investments”
ACC 560
December 2, 2012
Professor Linda Chess

Johnson Controls, Inc. follows a carefully an outlined capital budgeting process. There are many methodologies to supplement the traditional methods for evaluating the capital investments of Johnson Controls, Inc. The three traditional valuation methods, transaction, income, replacement cost, are appropriate for nearly all valuation analyses. However, over the past decade or so we have seen the growth of a new family of valuation methods based on future contingent events. This family of methods includes real options, binomial models, and Monte Carlo simulations. They are all based on decision tree models where the conditional events required for the IP to generate value are modeled explicitly. At the core of each of these methods is a two-step process: first, compute the probability of the favorable event occurring that will make the IP valuable, and second, compute the payoff if the favorable event occurs (usually using one of the traditional three methods described above). The real option method is based on the successful Fischer-Black valuation model for pricing options (calls and puts) of financial stocks. The basic premise behind the real option method is that an investment with an asymmetric payoff (i.e., a potentially large payoff and only limited losses) will have an increased value as the level of uncertainty, known as volatility, increases. Consequently, real option methods have been most useful where large capital investments are required with a highly uncertain and far away payoff. Monte Carlo simulations, named for the gambling games popularized at the Mediterranean resort, models a low probability payoff over multiple iterations. The binomial expansion method, or decision tree, is the most intuitive of these methods. In the binomial expansion the required events and decisions are modeled explicitly, each with...

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