The application of real options for valuing infrastructure projects

This section provides the background of real option theory and applies it to value managerial flexibility in a large-scale infrastructure project. Also, this section presents the relevant literature involving the application of real options for valuing projects. The selected literature focuses more on the application of the valuation methodology than its theory.

Infrastructure projects with real options can be modelled using a continuous time model or a discrete time model. A continuous time model can be computed for valuing real options in which the variables behave randomly. Discount cash flow analysis is widely used in

traditional project evaluation. In general, if a project‘s cash flows are stochastic, then they are assumed to follow geometric Brownian motion.

Valuing options in a project requires the mathematics of a partial differential equation (PDE) with boundary conditions. The Black–Scholes model is one of the most famous partial differential equations and was initially used to value financial options. Later, many academic researchers applied the Black–Scholes model to value option flexibility in real assets,

especially for investment projects. Among them were Benaroch and Kauffman (1999), in evaluating information technology project investment; He (2007), in valuing the option to delay a project; and Vandoros and Pantouvakis (2006), in using real options to evaluate a toll road project. Table 3.10 provides the findings of their studies. Although the Black–Scholes model is useful, its limitations have been clearly stated. It provides an industry-standard

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methodology to assess the value of a financial derivative, for which a specific equation of the model may not exist in many realistic situations. Many researchers, i.e., Rose (1998), Lewis et al. (2004), Charles and Liu (2006), and Zhao et al. (2004), have moved to using numerical methods—including the binomial lattice method, the finite difference method and Monte Carlo simulation—for option pricing.

One of the most popular discrete time models is the binomial lattice model, which creates two sets of cash flows: one up and one down. It is generally used to price the value of an option assuming a risk-neutral probability. The main assumption of risk neutrality is that the market is complete, and therefore, a replicating portfolio can be found (Garvin and Cheah, 2004). When a risk-neutral probability outcome is defined, the project‘s cash flows can be

discounted at the risk-free rate. In this research, the binomial lattice method was selected for valuing real options because of its flexibility, matched with the characteristics of the project‘s cash flows.

The assumption of geometric Brownian motion (GBM) with constant volatility is common when valuing real options. If the changes in the value of a project‘s cash flows follow GBM, then the real option can be valued by the traditional option pricing method (Brandao and Dyer, 2005). Then, the binomial lattice method in a risk-neutral world can be applied to the option‘s valuation. However, when the project‘s cash flows are discounted by a risk-adjusted discount rate to value the base NPV, the option payoff is discounted by a risk-free rate, assuming risk-neutral valuation.

Many practitioners including Myers (1987) and Trigeorgis (1993a) have suggested

implementing real options in practise by trying to value the inherent managerial flexibility in an investment project. Trigeorgis (1993a) defined the meaning of managerial flexibility as a set of real options, i.e., the option to defer, abandon, contract or invest in the project. In addition, the managerial flexibility embedded in an investment project traditionally takes the form of the collection of real options, in that the combined values of these operating options can have a large impact on the project‘s value (Trigeorgis, 1993a).

Real options theory has specifically been applied to deal with the uncertainty and flexibility inherit in an investment project (Trigeorgis, 1996). Substantial evidence indicates that the infrastructure projects are key areas for using the application of real options. Many researchers have used real options for valuing infrastructure projects. Blank et al. (2009)

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valued a government‘s options to guarantee minimum and maximum traffic to mitigate the demand risk of a toll road in Brazil using analytical and simulation methods.

Charoenpornpattana et al. (2003) analysed build–operate–transfer (BOT) projects focussing on the real options of minimum traffic guarantee and shadow tolls. Zhao et al (2004)

developed a real option model for the development and operation phase of a highway. The model focussed on three risk types: traffic demand, land prices and highway deterioration. Other authors have applied real options for valuing infrastructure projects, including Chiara et al. (2007), in valuing the multiple exercise of real options in a toll road project; Ford et al. (2002), in measuring the strategic flexibility of a toll road; Ho and Liu (2002), in evaluating the financial viability of privatised infrastructure project; and Rose (1998), in valuing option interactions in a toll road infrastructure project. A detailed analysis of these studies has already been provided in this section.

Typically, real options in a project are more complex, in that the project incorporates a set of multiple real options. When options are combined, their interactions exist and the valuation of those options becomes more complicated. Trigeorgis (1993a) researched the interactions between two options or among more than two options. His study concluded that the combined value of two options in the presence of each other may differ from the sum of the separate value of each option. Literature related to the interaction among options in infrastructure projects is rare. There are Huang and Chou (2006) on the interaction between a minimum revenue guarantee and an abandon option, Rose (1998) on the interaction between

abandonment and deferral options.

Valuing an investment project is difficult due to its substantial uncertainty and complexity, which make it necessary to use sophisticated tools to evaluate opportunities and risks. Real option analysis offers a framework for assessing the risks in a project. Real options are used to capture the managerial flexibility under uncertainty and to simplify complex problems. The real option approach has recently gained growing attention in the project evaluation field. Many authors have illustrated the applicability of the real option methodology for evaluating infrastructure and R&D projects. The next table lists previous works on the application of real options to project evaluation.

Authors Project type Finding on the study

Blank et. al. (2009) Toll road The authors proposed three real options in their study: a minimum traffic guarantee, a

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Authors Project type Finding on the study

maximum traffic ceiling and the abandon option. In the minimum traffic guarantee, the government subsidises demand that is lower than the lower bound level, whereas in a maximum traffic ceiling, the concessionaires pay the government if demand exceeds the upper level. In addition, the implicit abandon option was considered to influence the government‘s decision about the guarantee option.

The analytical approach and the Monte Carlo simulation approach were proposed to evaluate the real options for the toll project. Their study showed that the government‘s guarantee option had two benefits: i) the guarantee could reduce the probability of project‘s default and ii) the government could design a level of guarantee to minimise the probability of abandonment from the concessionaires. It can be argued that adopting the abandon option in a project should be carefully reviewed, as doing so may create unfavourable consequences, such as social and political problems, for governments. This research agrees with the authors that three objectives should be carefully considered: the concession scheme should be attractive to private capital; the probability of abandonment should be limited; and the overall risks of the project should be minimised.

Charles and Liu (2006)

Infrastructure and

transportation

The authors used a Monte Carlo simulation of cash flow to value the government‘s support and the repayment option in an infrastructure

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Authors Project type Finding on the study

project project. The case study of the Malaysia–

Singapore Second Crossing project was used in their study. The simulation showed that the value of the government support, in the form of subsidy payments, may be substantial, relative to the base net present value. In addition, a repayment option can be designed to set a limit on the concessionaire‘s return. The value of a government guarantee may be significant and create significant government expenses. Hence, the appropriate level of government guarantee should be determined.

Vandoros and Pantouvakis (2006)

PPP Project (toll road project)

The author evaluated ―the option to abandon‖ a hypothetical toll road project. The hypothetical toll road project was used to evaluate and compare both traditional NPV and real option analysis using the Black and Scholes method.

The authors concluded that real options incorporate managerial flexibility in decision making for evaluating projects at the appraisal stage. The study is limited to a hypothetical project, in that the use of a case study could provide more realistic results. The authors argued that the advantage of real option

analysis over NPV is its flexibility to deal with uncertainty in the decision making process. The authors did not analyse the limitations of the Black–Scholes model.

Lewis et. al (2004) Research and development project

The authors presented a method for evaluating research and development projects. The authors determined the value of a deferral option and defined five variables that would impact the

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Authors Project type Finding on the study

option‘s value: -Future cash flow -The investment cost -The interest rate -Time

-The volatility of the future cash flows The authors used the binomial lattice and Black–Scholes models to price an option‘s value. The authors defined the deferral option as the call option. The dividend payment was considered to be the cost of deferral.

The study showed that the deferral option provided the value of managerial flexibility. In a sensitivity analysis of the independent variables, the present values of the future cash flows and their volatilities were the most sensitive factors in the option‘s value and should be forecasted with great care. It can be argued that the cost of the deferral option should be considered, as it may have significant impacts on the deferral option‘s value. The lender in the project can apply the deferral option, as the lender may have the option to delay long-term funding and may wish to see the progress of the construction.

Zhao et. al (2004) Highway project The authors presented a real option model for decision making in highway development. The study focusses on three real options: land acquiring, expansion and rehabilitation. The model focusses on three risk types: traffic demand, land prices and highway deterioration. The uncertainties were simulated using Monte

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Authors Project type Finding on the study

Carlo simulation. The authors proposed optimal decision making for highway expansion and rehabilitation. However, they did not address the limitations of applying Monte Carlo simulation, especially in valuing American options.

Charoenpornpattana et. al (2003)

BOT highway project

The authors presented the role of government support in BOT projects. The authors focussed on two types of government support: the

minimum traffic guarantee and the shadow toll.

The project‘s cash flows were divided into two parts to evaluate the value of the government support: the cash flow without support and the support component. The support component could be valued by the real option approach, with the support component composed of a set of multiple options. To evaluate the real options, the authors used the binomial lattice with a risk-neutral approach. The case study of the M2 toll road project in Australia was selected for illustration. The level of the minimum traffic guarantee and the level of toll rates were determined using the binomial model. However, the minimum traffic

guarantee may not be the best strategic choice for governments, as it may create significant future liabilities for governments.

This research can be extended to investigate the other types of government support. The study did not conclude which types of support the government should incorporate into the project.

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Authors Project type Finding on the study

Pichayapan et al (2003)

Expressway project

The authors evaluated an expressway project with the option to delay an investment decision. The paper showed that as long as the project could be delayed without any additional cost, the longer delaying time provided higher NPV. The value of delay options is more valuable for financially unfeasible projects with low

volatility. However, economic NPV should be analysed for public transportation projects for which a delay decision is worthless.

The authors suggested that a social loss due to delaying the project should be included into the calculation of an option‘s value; otherwise, the option‘s value will seem to be overestimated. Table 3.10: Previous literature associated with using real options in project evaluation

The approach in this research differs from that of Charoenpornpattana (2003), Blank (2009) and Charles and Liu (2006), in that their studies focus on the government‘s options in the development of infrastructure projects. This research extends the application of real options to a project‘s other main stakeholders, not only the government but also financial institutions and private companies. In addition, this study proposes a real option interaction model among the government, the financial institution and the private company. This research begins with the financial institution‘s options in infrastructure development (Chapter 4) and then defines and determines the government‘s options in infrastructure projects (Chapter 5). Next, the options for the private company in the project are valued (Chapter 5). Lastly, this study will determine the value of the option interactions among the government, the private company and the financial institution (Chapter 6).

3.8 The options for governments, private companies and financial institutions in