Optimizing Investment Decisions Using DCF, Decision Tree Analysis, and Real Options Analysis: The Case of Hotel Expansions

Optimizing Investment Decisions Using DCF, Decision Tree Analysis, and Real Options Analysis: The Case of Hotel Expansions

Ramya Rajajagadeesan Aroul (Ecole Hôtelière de Lausanne, HES-SO – University of Applied Sciences Western Switzerland, Switzerland)
DOI: 10.4018/978-1-5225-1054-3.ch004
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Large scale infrastructure expansions in hotels are exposed to uncertainty. Since the costs involved in these expansion projects are high and often irreversible, hotels would benefit from analyses that incorporate uncertainty along with traditional valuation techniques like the discounted cash flow (DCF) method. Decision tree analysis (DTA) and real options analysis (ROA) have been in use for the past couple of decades to handle uncertainties and optimize investment decisions. DTA provides a distinct approach to strategic investments that quantitatively takes into account the uncertainties involved in the investments. Under uncertainty, the decision about whether to expand is analogous to the decision about whether to exercise an American call option. By using ROA to the hotel expansion scenario, managers can incorporate and quantify, flexibility and timing in their analysis. The objective of this chapter is to detail the DCF, DTA and ROA methodologies and their applications specific to hotel expansion investments.
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The discounted cash flow (DCF) technique is the most widely used valuation technique in practice. In this technique, a project is valued by discounting its expected cash flows at its cost of capital. The cost of capital, usually the weighted average cost of capital (WACC) is used to estimate the worth of future cash flows today. This process of estimating how much these future cash flows are worth today is called discounting and hence the name for the technique. The net present value (NPV) of the project is then calculated as the difference between the total of all discounted future cash flows and the initial investment. A project is valuable to be undertaken if the NPV is not negative. Accepting projects with NPV less than zero decrease the value of the firm. Also, the higher the NPV of the project is, the higher it contributes to the overall value of the firm.

However, DCF works best when the certainty of future cash flows is high. But valuation using DCF is shaky when it's difficult to predict and estimate future cash flows with much confidence. Also, this analysis does not take into account the flexibility inherent in the investment decision. Also, past real estate studies suggest that DCF may be insufficient for evaluating real estate investment projects (Hayes & Abernathy 1980; Hodder & Riggs, 1985; Sirmans, 1997).

The complexity of the investment process is that the firm can take dynamic decisions which is not accounted for by DCF. When there is a lot of complex information that needs to be accounted for, decision trees (Gertner & Rosenfield, 1999) are often used as techniques for investment decision making. They provide an effective configuration in which different decisions and the consequences of taking those decisions are portrayed in a diagram and evaluated. Eventually they help to picture an accurate and balanced opinion of the risks and rewards that evolve from making a specific investment choice. In this regard, decision tree analysis is superior to the DCF analyses in the context of inclusion of uncertainty in the investment decision process. Although decision-tree analysis tends to pay a lot of attention to the cash flow uncertainties, it rarely considers dynamic decision making.

In 1970s, stochastic calculus was introduced in the finance literature leading to theories and models in pricing financial options. Many studies then applied these financial option-pricing models to investment projects. This new area of ‘real option’ analysis received a lot of attention in several areas especially in real estate valuation (Quigg 1993, 1995; Buetow & Albert 1998; Hendershott & Ward 2000; Holland et al. 2000). Real options analysis (ROA) has been in use for the past couple of decades to handle uncertainties and optimize investment decisions. It provides a distinct approach to strategic investments that quantitatively takes into account the risks and uncertainties. Similar to DCF, ROA also focuses on the goal of value maximization. However, ROA acknowledges that managers use available information to make decisions while DCF makes managers to choose years in advance and does not accommodate the changes that may happen in the future. ROA uses the “backward induction” approach like the decision tree analysis and combines this with a valuation model.

In the following sections, we evaluate a hypothetical hotel expansion project using DCF, decision tree analysis and real options analysis and explain the fundamental differences among these techniques. This chapter is divided into the following distinct sections. The first section provides the background of literature. Section 2 discusses the motivation for the book chapter. Section 3 discusses the DCF valuation framework, the basic decision tree valuation approach that is used in both single period and multi-period cash flow scenarios and introduces the ROA analysis. This section also discusses the advantages and disadvantages of each valuation technique. Section 4 introduces the case’s basic framework and applies all three valuation techniques on this mini case. The chapter also provides ROA application to the hypothetical case study with illustrations of the real options optimization technique step by step in Excel.

Key Terms in this Chapter

Valuation: The process of determining the present value of all potential future cash flows of an asset.

Real Option: A real option provides the manager the right not an obligation to undertake certain business initiatives like expansion, abandonment, deferment, etc.

DCF: Discounted Cash Flow (DCF) analysis estimates the value of an asset based on its expected future cash flows, by discounting them to the present using an appropriate discount rate.

Call Option: A call option provides a buyer the right not an obligation to buy a security (stock, bond, commodity etc.) at a specified price during a specified time.

Decision Tree: A decision tree is a tool that uses a tree like graph to model decisions and consequences to help managers incorporate uncertainty in valuations.

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