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Annual International Conference on Real Options: Theory Meets Practice

3rd Annual Real Options Conference

1999 Leiden
Netherlands Institute for Advanced Studies

Monday: Introductory Workshop/Tutorials | Theoretical Issues in Real Option Valuation | New Product Development, Infrastructure and Firm Valuation | Empirical Evidence | Valuing Product(ion) Flexibility | Real Options and Learning | Valuing Natural Resource Investments
Tuesday: Case Studies in Real Options | Sharing Experiences in Oil Development/Natural Resources and Panel | Competition and Strategy | Sharing Experiences in Pharmaceuticals and Panel Discussion | Real Options, The Environment and Agency Issues
| Keynote Address: Stephen A. Ross

1A. Introductory Workshops/Tutorials

Using Spreadsheets and Real Options Software Tools in the Petroleum Industry
Paper, Spreadsheet

Marc Paulhus and Gordon Sick, University of Calgary

There is a multitude of sources of uncertainty affecting the operations of a petroleum company. This paper sets up a real option analysis approach to valuing a general oil-field development project that integrates several types of risk into a multinomial tree/forest pricing scheme. The approach blends the decision tree model commonly used for binary one-time risks with binomial tree models for the generalized diffusion process(es) followed by the underlying commodity prices. The project specification part of the model has been developed in conjunction with Tuffs, an exploration geologist at Union Pacific Resources. We model the complex inter-dependencies of the cash flows as realistically as possible. Parameters include a finite quantity of reserves, variable rates of production, and cost of production as a function of remaining reserves. A detailed sensitivity analysis is performed with the aim of identifying dependencies of the outcome on the input variables.

The analysis will demonstrate the Real Options Software Engine (ROSE) package.

Using Spreadsheet Add-Ins to Value Managerial Flexibility

Excel Notes, Options Notes

By Wayne Winston, Indiana University

We will discuss how the EXCEL simulation add-in @RISK and the EXCEL simulation/optimization add-in RISKOPTIMIZER can be used to easily and efficiently value many real options. We begin by modeling the value of an underlying asset as a Lognormal random variable and value a European expansion option and contraction option by simulation. Next we will show how to value a European real option when the underlying asset is modeled as a jump diffusion process.

Next we will show how to use RISKOPTIMIZER to value American real options. Our example will be the classic model involving start-up and shutdown of a gold mine. RISKOPTIMIZER uses genetic algorithms to search for a set of changing cells that optimize the mean value of a simulation. These changing cells can correspond to asset prices that trigger a reopening or a shut down of the gold mine.

Finally, we will briefly discuss how RISKOPTIMIZER can be used to value managerial flexibility in classical capital budgeting problems when uncertainty involves factors other than price. Our example will concern the timing of entering a product into a new market. If we enter now we obtain a larger market share, but we do not yet know whether the market is large enough to be profitable. If we wait a while, we will have more information about the size of the market, but if we enter we lose the first-mover advantage and gain a smaller share of the market.

1T. Theoretical Issues in Real Options Valuation

A Recombining Binomial-Tree for Valuing Real Options with Complex Structures

Dan Calistrate, Marc Paulhus, University of Calgary and Gordon Sick, University of Calgary and NIAS

One of the main challenges in pricing complex real option projects is in the choice of the binomial/multinomial numerical scheme for representing the various possible underlying stochastic processes. A computationally simple scheme is desirable. On the other hand, correct modelling of the typical commodity price or interest rate process must incorporate general assumptions on the diffusion parameters such as mean reversion, variable volatility with time, etc. This paper introduces a new binomial tree model which converges in distribution to a general diffusion:

dS = mu(S,t)dt + sigma(S,t)dW.

The model is close in spirit to the work of Nelson & Ramaswamy. However there are advantages over the N&S approach. The discrete volatility fit is precise, allowing for fast convergence to the continuous distribution while retaining computational simplicity through recombination in the tree. Also, no transformation of the original process is necessary - for certain diffusions, the existence of a readily integrable transform (as required in the N&S model) may not be guaranteed. The one-dimensional binomial scheme can be successfully applied to pricing projects contingent on multiple diffusion processes after an appropriate orthogonalization of the factors. The benefits of such an approach are particularly apparent when the correlation parameters vary with time. In most existing models, this prevents the trees from recombining.

Valuing Real Option when Time to Maturity is Uncertain

Tony Berrada, University of Geneva

Recent literature in real options has shown how similar investment opportunities and financial options are. The analogy is clear on the underlying risk as a key variable and the irreversibility of investment, however the relation between the contractual time to maturity of a financial option and the time period over which the opportunity is available is less evident. The assumption often made for investment opportunity is an infinite time to maturity, which simplifies the computation of the option value.

However, when competition is considered in a project for a new market for example, the time to maturity could be the time before a competitor enters the market with a similar or substitute project. Therefore assuming that the time when the competitor will decide (or will be ready) to enter the market is known with certainty is a rather strong assumption. Furthermore the trigger value, i.e. the underlying value at which the project should be undertaken, is an increasing function of the time to maturity (in the simple case of constant risk free rate and investment cost). Therefore, assuming an infinite lifetime for the option overestimates this trigger value. If the time to maturity was not known with certainty the trigger value would be altered, and investment would be undertaken at a different time. In this paper we model the uncertainty over the time to maturity and study its impact under different assumptions for the level of uncertainty. We provide a lower and upper bound for the value of an american contingent claim when the time to maturity is uncertain but the density is known. We also propose an approximation of the value of the american contingent claim using a particular assumption on the form of the exercise boundary. The results obtained confirm the fact that the trigger value (for an investment opportunity, i.e. a call option) is lowered by the uncertainty on the maturity of the option.

2A. New Product Development, Infrastructure, and Firm Valuation

The Option Approach to the New Product Development Process

Onno Lint, Erasmus University Rotterdam, Eindhoven University of Technology and Enrico Pennings, Catholic University of Leuven, Erasmus University Rotterdam

Current phase-review processes for new product development cannot properly capture the economic value of managerial flexibility to continue or abandon a project at different stages of development. Due to this, the discussion whether it is fruitful to skip phases in the development process in order to create time-to-market advantage is left open. By applying insights from the valuation of real options, this article proposes a framework for the assessment of new product development at different stages, derives criteria to speed up the development process or not and introduces the options portfolios, which serve as a basis for assessment and as a tool for choosing an optimal set of business initiatives from a variety of feasible alternatives.

The implementation of the option approach may also entail initial obstacles. In particular the estimation of uncertainty, the key variable in the option approach, will challenge management. Sales predictions from senior managers can be substantially different and, hence, are subject to uncertainty. By a first step in implementing options-based aproaches to NPD at Philips Electronics we found that sales predictions and business events serve well to estimate the uncertainties described. Second, managerial experience can help determining the uncertainty of a project by judging the uncertainty of analogous projects in the past. Finally, at Merck, average stock volatility of companies in the same business as intended for the new product serves as a proxy for project uncertainty.

Reverse Hysteresis: R&D Investment with Stochastic Innovation

Helen Weeds, Fitzwilliam College, University of Cambridge

This paper considers optimal investment behavior when a firm faces both technological and economic uncertainty, in the context of an innovative research project. Specifically, the value of the prize for successful innovation follows a stochastic process, while discovery itself takes place randomly according to a Poisson arrival. The firm's optimal investment strategy, in the form of a pair of trigger points for investment and abandonment, is derived. As in the Dixit (1989) model of product market entry and exit, the investment trigger exceeds the Marshallian entry point given by the sum of variable costs and interest charges on capital costs. However, the abandonment trigger may in some cases exceed the Marshallian exit point, in contrast with the Dixit result, giving rise to reverse hysteresis. Thus, a firm will abandon research projects rapidly as their profitability falls, in some cases despite the existence of positive expected profits.

In addition, the model provides a unified framework encompassing two classic real options models as limiting cases. As the expected rate of innovation becomes large the outcome converges to the investment trigger for the McDonald & Siegel (1986) model of a single irreversible investment opportunity. As discovery becomes slow, on the other hand, the Dixit (1989) entry / exit model is approached.

Real Option Valuation of Strategic Platform Investments

Enrico Perotti and Silvia Rossetto, U. Amsterdam, Netherlands

In this paper we investigate the theme of real option valuation of platform investment in a context of strategic differentiation.

Platform investment has achieved mainstream interest in management science, but to date there are hardly any theoretical analysis. We propose a definition of platform as a market-opening technological innovation that creates a new product market. A classic example is the establishment of operating systems such as DOS or Windows. The innovating firm has the ability to choose the size of the platform, which in itself defines the potential range of product differentiation. The innovating firm must incur the cost of the creation of the platform at a time when there is still large demand uncertainty, while later entrant will be able to operate on the established platform by creating compatible products. On the other hand, the firm controlling the platform has some critical advantage on product and productive processes.

In our model we consider a world characterized by dynamic uncertainty on future consumer demand. In the product market the innovative firm which creates the platform has superior strategic powers. We model first the initial decision on the platform size, which indirectly affects the extend of comparative advantage gained by the innovating firm; we then study the entry decision on specific products within the platform decision of the innovating firm and of a potential entrant. We compute the value of waiting to invest, the point in time when each of the two firms chooses to invest and on which type of product (differentiation). In future research we will consider the choice of investing in a competing platform versus in a platform-compatible product.

The model allows to determine the impact of controlling the platform on ex post competition (as in the case of Microsoft and Windows) and the impact of uncertainty over both the initial platform investment and the extend of later entry. The possibility of waiting to invest is valuable, and increases in value with demand uncertainty. Less obvious is the impact of uncertainty on platform size and ex post entry.

The platform size (which is related to the potential range of differentiated products) is influenced by the hypothesis that the greater is the differentiation, the weaker are the cross-price effects. We show that the firm in charge of the platform may become dominant in some products as later entrants face either higher productive costs or a delay disadvantage relative to the platform-owner, and choose therefore a more limited range of entry among products.

The outcome of this decision process is not trivial, as it depends on product features and expected market demand evolution.

Valuation of a Biotechnology Firm: AnApplication of Real-Options Methodologies

David Kellogg (Sprint USA), John M. Charnes and Riza Demirer (University of Kansas)

Much of the value contained in early stages of pharmaceutical projects is in the promise of developing a blockbuster drug. This is especially apparent for firms in the biotechnology industry. Many biotech firms have significant valuations, yet do not have product revenue because their products are in early stages of development. In the past ten to fifteen years investors have bid up the stock prices of these firms, and their prices have remained high relative to their discounted cash flow valuations.

In this paper we compare the value of a biotechnology firm, Agouron Pharmaceuticals, Inc., to the sum of the values of its drug development projects. Each project's value is found using the decision tree (DT) and binomial-lattice methods. An influence diagram (ID) method is also used and discussed. We compare our computed values of Agouron to actual market values at selected points in time during the development of Viracept¬, a drug used to treat HIV-positive patients.

The approach and results are of interest to stock analysts because it provides a means to value biotechnology companies that have no current revenue. Financial analysts in pharmaceutical companies can use these methods to value projects and compare their relative worth for capital budgeting purposes. Executive management of pharmaceutical firms can use these methods to better understand the values of their projects and convey them to investors. Finally, academic readers can find an interesting case study that demonstrates the use of real-option valuation methodologies.

The decision tree method considers the net present value (NPV) of eleven possible outcomes of each project and calculates an expected NPV by multiplying the NPV by its probability of occurrence. The eleven possible outcomes are failure at each stage of development, and five levels of commercial success.

Values for Agouron were also found using a binomial lattice with the addition of a growth option. The growth option was added because the development of an initial new molecular entity (NME) is similar to purchasing a call option on the value of a subsequent NME. Without engaging in development of the initial NME, it is not possible to develop the subsequent NME. Intermediate results from the decision tree method were used to calculate the beginning asset values and volatilities for valuing both the initial NME and the growth option with the binomial lattice method.

We show how a real options approach can be used to value a biotechnology firm. Usage of average assumptions and binomial lattices seems to work better when projects are in earlier stages of development and less is known about the drug. As projects move into later stages, more specific information regarding time to launch, market size and probability of success should be utilized in DT/ID models to reflect the value of the firm more accurately.

2T. Empirical Evidence

Alternative Explanations for Managerial Flexibility: Economic and Sociological Analyses of Mine Closing Decisions

Second Paper

M. Diane Burton, Alberto Moel, and Peter Tufano, Harvard University

Understanding how managers make decisions and react to external stimuli is an important topic that academics in many disciplines study. Economists tend to build normative models of rational behavior, such as real options models, that represent how value-maximizing agents should optimally choose to exercise the options that business presents. Sociologists tend to build positive models of behavior, characterizing how individuals and organizations are likely to respond to the world around them. Far too often, these single-disciplinary research efforts are unconnected.

In our project, we seek to use insights from both economics and sociology to study one particular managerial reaction to the environment: the decision by gold mining firms whether to open or shut mines in response to changes in gold prices. In previous research (Moel and Tufano 1999), we analyzed this decision using the real option framework of Brennan and Schwartz (1985). Using a hand-collected database, we tracked the annual opening and closing decisions of developed North American gold mines in the period 1988-1997. Our analysis provided strong support for the real options approach as a useful model to describe and predict a mine's opening and shutting decisions. In particular ,we found that the decision to open and close demonstrated hysteresis, and was sensitive to both the level and volatility of gold prices as well as to mines' operating costs.

The prior paper took the mine as the unit of observation, and tested if mine and market characteristics affected the decision to close. We used a narrow economic perspective, and tested whether managers behaved "rationally" in response to market and firm conditions. There are, however, entirely different ways of looking at these decisions, where the unit of analysis is not the rational decision manager, but the context within which the manager operates. In particular, the fields of sociology and organizational behavior have developed models of managerial decision-making where the organizational structure and context dictate the boundaries of the manager's decision-making capabilities. Sociologists and organizational theorists have, over the past twenty years, argued that economic transactions are embedded in social relations (Granovetter 1985). These social relations often account for what economists observe to be "non-rational" behavior. In this new paper we propose to explore this line of research and examine the social and organizational factors that influence a firm's decision to close or reopen a mine.

In this current project, we recognize that important decisions such as whether to close a mine are made by managers, who often work in larger organizations (firms), and whose decision-making may reflect more than narrow economic criteria. Drawing upon the literature in sociology which deals with factors that might affect how firms respond to external stimuli, as well as the related behavior finance field, we will seek to understand how the following factors could influence the decision whether or not to close a gold mine. This is work-in progress, and we are unsure how much of this data we can collect:

  • Stakeholder concerns: Whether the location of the decision-maker affects the decision to close a mine and temporarily layoff workers. Related to the number of workers to be laid off, local labor market conditions, and the union status of the workforce.
  • Regulatory costs: Whether the decision to close varies between the US and Canada, where laws and environmental regulations differ.
  • Financial impediments: Whether the existence of prior debt and hedging contracts are related to the decision whether or not to close a mine.
  • Decision maker characteristics: Whether the background of senior executives (mining v. financial background, age, compensation) affects the decision to close.
  • Organization structure: Whether the organizational structure (single line or multidivisional), size and age of the firm affect the decision to close
  • Prior experience: Whether prior experience in closing a mine affects the current decision to close.
  • Overall organization profitability: Whether firm profitability affects the decision to close.

Growth Option Company Acquisitions: In Search Of An Optimal Option Portfolio

Tomi Laamanen, Helsinki University of Technology

Previous work shows that strategic synergy advantages in company acquisitions are often not immediately realized, but rather affect the combined growth options of acquiring and target firms. This paper sets out to explore the stock market responses to changes in the composition of a firmÍs growth option portfolio. It is hypothesized that with a small number of growth options, the growth opportunities are constrained setting a limit to the expected value of the firm. With a large number of growth options, the value-increasing effect of variability gradually levels off and option interactions start to dominate decreasing the expected value of the growth option portfolio. More specifically: (1) The higher the growth expectations, i.e. the higher the market-to-book ratio of a firm, the less positive the stock market reaction to acquisitions of additional growth options. (2) The lower the growth expectations, i.e. the lower the market-to-book ratio of a firm, the more positive the stock market reaction to acquisition of additional growth options. Furthermore, (3) the higher the market-to-book ratio, the more positive the stock market reaction to focus decisions such as divestments and (4) the lower the market-to-book ratio, the less positive the market reaction to divestment decisions.

The hypotheses are tested empirically by studying the abnormal returns from acquisitions and divestments of three major Finnish companies possessing different growth option characteristics. Altogether 188 acquisition and divestment events during a period from 1987 to 1997 are studied. The data would seem to provide support for the hypotheses concerning the relationship between the cumulative abnormal returns in acquisitions and the market-to-book ratio. In connection with divestments, the results are opposite to the hypotheses. Divestments would seem to reduce the book value more than the market value resulting into increasing market-to-book ratios when the initial market-to-book ratios are low. The results also corroborate partly the earlier results concerning the cumulative abnormal returns to shareholders of the acquiring and target firms. As expected, the stock market reactions to divestments and acquisitions differ. The differences are not, however, identical to what has already been documented in the literature. In addition to being dependent on the nature of acquisition or divestment, the stock market reactions to acquisitions and divestments seem to be company specific and time period specific. A signaling explanation is put forward to explain the stock market reactions to divestments.

Real Options and Preemption under Incomplete Information

Bart Lambrecht, University of Cambridge and William Perraudin, Birkbeck College, London and CEPR

This paper introduces incomplete information and strategic behaviour into an equilibrium model of firms holding real options.

The main contributions of our study are, first, to provide a practically useful and yet consistent way of combining real option values and threats of preemption with incomplete information in a capital budgeting framework. Incorporating incomplete information is important as it is otherwise hard to see what prevents firms from colluding and splitting the surplus efficiently. Given some basic data about a firm's investment costs, revenue potential after investment, and conjectures about the distribution of costs faced by competitors, our techniques permit one to derive an optimal investment strategy in a simple fashion.

Second, we explore the implications of our analysis for equity returns. Our model allows one to decompose equity volatility into price changes reflecting changes in publicly observable profit variables and price changes caused by the resolution of uncertainty about competitors. Parametrizing our model so that in simulations it yields second and higher moments that resemble those of US biotech stocks, we show that 'competitor risk' may comprise a substantial fraction of these firms' total volatility especially close to the firms' initial listing dates. As we show, the degree to which the threat of preemption may accelerate investment according to our estimates is comparable to the firm facing an expected time to ruin on its individual real options of approximately half a year.

Third, we show that incomplete information and competitive pressure interact in a way that crucially affects real option values. For firms of a similar type, if information is complete, preemption will lead to the total destruction of option value. Under incomplete information, these firms will be better off. On average, if one integrates across firms of all different types, incomplete information leads to a reduction in firm value, however.

3A. Valuing Product(ion) Flexibility

The Value of Manufacturing Flexibility: Real Options in Practice

J. Bengtsson, LIT, Sweden

Managers in the manufacturing industry of today ask the question how to justify the higher costs often associated with a flexible manufacturing system. Even though they are aware of all the advantages of a flexible manufacturing system they face a problem since the traditional capital budgeting approaches undervalue the potential of a flexible system. Using the traditional approach might in the worst case result in rejection of a profitable project, wherefore other methods should be used to evaluate projects with embedded flexibility.

This paper considers applications of real option thinking and valuation of manufacturing flexibility using option-pricing theory and will present results and experiences from research carried out with industry. Three Swedish midsize companies constitute the empirical base. A case description of each of the three companies will also be presented in the paper. The descriptions will show how the companies view flexibility today and how this can be looked at from an option-theoretic point of view. Also, the different kinds of external and internal uncertainties that the companies are, or could be, affected by will be described as well as the means to achieve the desired flexibility.

The companies are producing totally different products; electrical motors, casting reels and industrial robots, to industry and consumer customers. While all industrial robots produced are customer specific and require a flexible production process, the electrical motors and casting reels have a big proportion of itÍs annual volume in standardised products. For the two latter products it might thereby be an alternative to separate standardised product and customer-specific and produce these in different line where the line producing the customer-specific products has a flexible process. Different production set-ups can be evaluated using option pricing to find an optimal set-up, which maximise NPV.

The paper will focus on flexibility in the assembly part of production. Assembly is a central operation to the companies that are studied and flexibility of the whole production line is often constrained by the flexibility in the assembly stations. All three companies strive to achieve the same types of flexibility, volume and product-mix, to cope with uncertainties in demand. However, the ways to achieve these types of flexibility differ between the companies due to differences in products and ways to produce these. For example, one company is solely carrying out manual assembly while another uses automatic machines. Thus different kinds of options have to be identified and different kinds of exercise patterns may be shown. We will highlight some practical problems associated with the different steps from identifying options, finding sources of uncertainty, gathering appropriate data from the financial markets, etc.

The Options View of Products: Flexibility, Modularity, and Systemic Effects

Jussi Keppo, Columbia University and Sampsa Samila, Columbia University

This paper aims to lay a theoretical foundation on how individuals value durable products. In this paper we emphasize ownership and analyze why customers want to own products and the value they give to ownership. Specifically, we argue that the ownership of a product represents a bundle of options. At any given point in time, the owner of a product has the option to choose whether she wants to use the product or not. In addition, this paper extends the current literature on product value by taking explicitly into account several important characteristics of modern products, namely modularity, and systemic as well as network effects. This approach has the significant benefit that it allows consideration of uncertainty about the future use of the product. The model shows that the value of a product is sensitive to the changes in uncertainty, especially when the variable costs are high compared to the utility. This uncertainty about future utility depends on the uncertainty about future needs and wants, about the quality of the product, and about the availability and quality of future upgrades. However, the value is also dependent on the uncertainty about the future variable costs.

3T. Real Options and Learning

Valuation and Information Acquisition Policy for Claims Written on Imperfectly Observed Real Assets

Paul D. Childs, Steven Ott, University of Kentucky and Timothy J. Riddiough, Massachusetts Institute of Technology

Unlike the assets that underlie exchange-traded claims, many real assets are infrequently traded so that asset values cannot be continuously and precisely observed. If the exact value of the asset that underlies the contingent claim is not known with certainty, both the valuation and any exercise decision must be made with an imperfect estimate of real asset value. In this setting, the claimholder has an incentive to more precisely determine asset value by acquiring additional information about the underlying asset value.

The framework for this paper is that the value of underlying assets for some contingent claims is partially obscured by noise. We determine distributional parameters for the conditional expected asset value where the noise and the underlying asset value dynamics follow normal, lognormal and mean-reverting processes. We also examine the effects of two types of noise: an initial level of noise present when the underlying asset value is originally observed or estimated, and a dynamic process that accumulates noise after the initial observation. When a costly information acquisition technology does not exist, the initial level of noise volatility does not affect option value or exercise policy, while noise that accumulates always results in lower option values.

To study information acquisition policy, we examine the case of a borrower who holds the default (put) option inherent in a risky discount debt contract. Costly information acquisition technology will be used to reduce potential errors in exercise policy at the debt payoff date if the technology is sufficiently inexpensive and the conditional expected asset value is sufficiently close to the face value of the debt. Comparative static results reveal that when asset volatility is greater than the accumulating noise volatility, the optimal level of information acquisition is most sensitive to noise volatility. Initial noise volatility has the greatest impact for short-lived claims while accumulating noise volatility has the greatest impact for longer-lived claims.

We provide solutions for the value of the debt given that market participants anticipate acquisition of information. Under the more general setting where there are multiple opportunities to gather information, it is optimal to acquire information in smaller increments to reduce the potential of ex-post overinvestment and underinvestment in information acquisition. Nevertheless, the cumulative level of information acquisition is often higher relative to the case when information can only be gathered once.

Real Options with Random Controls and the Value of Learning

Spiros Martzoukos, U. Cyprus

In this paper we propose a conceptual framework for valuation of real options in the presence of controls with random outcome (learning) in continuous time. The controls affect the value of the underlying asset, and are incurred at some cost. They represent optional efforts by management to add value to the underlying real investment over which it has monopoly power, albeit with uncertain results. A special case of this framework captures costly learning, like in R&D projects. A solution methodology is demonstrated and the impact of such uncertain actions is seen to be relatively more significant in the case of less profitable investment options.

4. Valuing Natural Resource Investments

Real Options in Offshore Oil Field Development Projects

Morten W. Lund, Natural Gas Marketing & Supply, Statoil, Norway

The Norwegian offshore activity has evolved rapidly and Norway is today the 7th largest oil producer in the world. As a consequence the oil and gas industry has become a very important element of the Norwegian economy, and the focus on improved development strategies has strengthened over the last 10-15 years, putting emphasis on the need for so-called flexible development strategies. A number of contributions have addressed the subject of investment under uncertainty in the oil industry. Especially the development of contingent claims analysis and its applications to real investments have provided increased insight into this topic. However, most of the published examples greatly simplify the project description, both regarding the number of stochastic variables and the operator's decision making freedom. Due to the simplifications it is hard to discern the benefit of real options in a realistic oil field development project from contributions reported in the literature.

The model described in this paper seeks to provide a more complete and realistic description of an oil field development project by capturing the main types of options present in the projects. Compared to related models the presented framework represents a significantly extended approach. Both the degree of decision making freedom and the number of stochastic variables are increased, implying a much more computationally demanding model.

The model is a finite horizon Markov decision process and includes three stochastic variables; the oil price, the well rate, and the reservoir volume. These variables are of major importance to the production profile and the cash flow of the field. The size of the model, measured by its state space, the number of alternative decisions and the number of stages, depends on the field development project being addressed as well as e.g., the choice of stochastic process for the oil price. Nevertheless, reported solution times for runs made on a PC and on a Unix machine are considered acceptable for practical decision making situations.

To illustrate the qualities of the developed framework the model has been implemented for a small oil field about to be developed on the Norwegian continental shelf. Project data are, however, somewhat modified in order not to reveal any restricted information.

The case study reveal several interesting consequences of going from a deterministic to a stochastic evaluation of the oil field development project, and clearly illustrate the importance of giving due attention to flexibility in future oil field development projects. The value of flexibility for the addressed project is substantial, both in relative and absolute terms.

The model outlined in this paper represents a first approach to provide a comprehensive decision support model for oil field development projects. It should be conceived of as a prototype, and the possibilities for refinement and expansion are thus abundant. Such improvements are not considered in this context.

Petroleum Concessions with Extendible Options: Investment Timing and Value Using Mean Reversion With Jumps To Model Oil Prices

Marco Antonio G. Dias (Petrobras, Brasil) and Katia Maria C. Rocha (IPEA, Brasil)

Petroleum firms acting in exploration and production (E&P) routinely need to evaluate concessions and to decide the investment timing for its project portfolio. In some countries, the exploration concession has features such as the possibility of extension of the exploratory period. The holder of a petroleum exploration concession has an investment option until the expiration date fixed by the governmental agency, and these rights can be extended by additional cost. The additional costs can be some fee (extra-tax) to governmental agency and/or additional exploratory/appraisal investment.

The value of these rights and the optimal investment timing thresholds are calculated by solving a stochastic optimal control problem of an American call option with extendible maturities, using the dynamic programming framework. The thresholds for both the optimal extension of the option and the immediate development investment are presented and discussed.

The uncertainty of the oil prices is modeled as a mix jump-diffusion process. Normal information generates continuous mean-reverting process for oil prices, whereas random abnormal information generates discrete jumps of random size. We adapt the Merton (1976) jump-diffusion idea to the oil prices case. Normal information means both marginal interaction between production and demand (inventory levels is an indicator) and depletion versus new reserves discoveries (the ratio of reserves/production is anindicator).

Abnormal information means very important news, causing in a short time interval, a large variation (jumps) in the prices. These jumps, which has been observed sometimes in oil prices history, are modelled with a Poisson process.

The paper's new contributions are two: the framework of options with extendible maturities for real assets and the utilization of a mixed stochastic process (mean-reversion with jumps) to model the petroleum prices which, despite of its economic logic, has not been used before in petroleum economic literature. Comparisons are performed with the popular geometric Brownian process for both the concession option value and the optimal investment timing policy. The role of the convenience yield is also discussed for both stochastic process, which has an important impact in the optimal development investment threshold. Analysis of alternative timing policies for the petroleum sector is presented, and also the comparative statics for the main parameters of the model.

Optimal Exploration Investments under Price and Geological Uncertainty: A Real Options Model

Gonzalo Cortazar, P. Universidad Católica de Chile, Eduardo S. Schwartz, University of California Los Angeles, and Jaime Casassus, P. Universidad Católica de Chile

We present a real options model for valuing natural resource exploration investments when there is joint price and geological uncertainty. Price uncertainty is modeled by a brownian motion, while geological risk is on reserves, development investments and cost structure, with uncertainty declining as exploration investments are undertaken. The model considers that in case of finding an economically feasible mine, there may be a development investment, to be followed by an extraction phase. All phases are optimized contingent on price and geological uncertainty.

Several real options are considered in the model. The exploration investment schedule is considered flexible and may be stopped and/or resumed at any moment depending on cash flow expectations, which in turn depend on current commodity price and geological expectations. The model allows for several exploration phases, each one with its own investment schedule and probabilities of success. In the event of an exploration success the model considers a timing option for the development investment, and closure, opening and abandonment options for the extraction phase.

The model has the virtue of maintaining a relatively simple structure by collapsing price and geological uncertainty into a one-factor model for expected value. The model was applied to value some real exploration prospects for a major copper company. Results for a case are presented.

1. Case Studies in Real Options

Schering Plough Case: Valuing Pharmaceutical Development and Expansion Options

Alberto Micalizzi, Bocconi University

This case is taken from Schering Plough in the pharmaceutical sector, a sector in which the concept of value creation is currently under significant reconsideration. Enabling technologies and optimization of stop-go decisions must be seen as a means through which managers can improve the R&D efficiency. It follows that more and more attention is being devoted to:

  • Increasing market opportunities for each product
  • Selecting the best candidates to develop
  • Boosting the customer satisfaction

The fact that the fixed cost investments are focused increasingly on the late stage of clinical trials gives more importance to the product launch as an irreversible investment decision. In particular, the costs of the last phase of clinical trials necessary to bring new products to market are typically undertaken three to five years before product launch. These resource-intensive trials can significantly impact the total value of the project.

The firm is faced with an irreversible decision of whether or not (and when) to invest in the third stage of clinical trials of a new anti-asthma product, Newprox. The potential worldwide market for Newprox is approximately one billion dollars.

The case is enriched by the fact that the firm plans the launch of a product, Minprox, designed to treat nasal congestion caused by allergies. This product uses the same molecule in Newprox but the market for Minprox could be significantly small, which would result in a negative NPV.

There are two important aspects worth considering about the Minprox project and its link to Newprox. First, the launch of Minprox would underline the continuity of investments in company image and would represent a bridge between the anti-allergy segment (where Schering Plough has been present for over ten years) and the anti-asthma segment (where Schering Plough is a newcomer ). Second, Minprox represents an important source of information that allows SP to postpone and condition the launch of Newprox. As a matter of fact, SP bases the decision to invest in the last stage of clinical trials of Newprox on the potential success of Minprox.

Airbus: Valuing Options in the Airline Industry

John Stonier, Airbus Industrie and Alexander Triantis, University of Maryland

Real options may arise naturally in the course of business, such as the option to wait to invest. Alternatively, they may be granted or purchased in the form of contractual options. This paper presents the authors' experience with the valuation and use of contractual aircraft delivery options in the aircraft manufacturing and airline industries. The relative value of a contractual option compared to an airline's natural option to wait to invest is captured using a contingent claims model. Some of the interesting issues that arise in the analysis include mean reversion, the estimation of underlying present values and volatilities, and the appropriate specification of stochastic exercise prices and queue lengths for delivery. In addition to a standard delivery option, we also examine conversion rights - options to take delivery when there is a choice of aircraft type (i.e., options on the maximum). The use of contractual delivery options raises many interesting strategic issues from the perspective of both the aircraft manufacturers as well as the airlines. We explore implications for risk management, value creation through flexibility, competitive strategy, and optimal contract design.

2A. Sharing Experiences in Oil Development/ Natural Resources & Panel

Real Options Application: From Successes in Asset Valuation to Challenges in Portfolio Optimization

Soussan Faiz, Texaco Inc., USA

The Real Options methodology is emerging as the state-of-the-art technique for asset valuation among practitioners. The increased collection of comprehensible literature on real-life applications is paving the way for using "option-pricing" methods, customary on Wall Street, in situations within firms of all sizes on Main Street.

Separately, the concept of "efficient frontier" is also making headway for applications in strategic diversification. Various products within the marketplace now enable a portfolio manager to optimize an asset (or business) mix under different risk and return trade-offs, short- and long-term objectives, and key operational and fiscal constraints.

There is, however, a large gap in the literature and in practice on combining Real Options with Portfolio Optimization. Often a portfolio contains opportunities that are dependent on common macroeconomics (e.g., oil price), have possible other interplays, and include various embedded options through their lifecycles. The ability to dynamically optimize asset combinations and determine the percentage stake and staging of each opportunity is of critical interest to senior executives.

This presentation conveys some insights from a Real Options application and, separately, from a Portfolio Optimization case study. In the absence of established guidelines to link the two techniques, however, it invites the Real Options community to focus its attention on closing this important gap and providing a seamless solution to a portfolio manager.

Roadblocks, Sleeping Policemen and Real Options

Peter H.L. Monkhouse, Rio Tinto plc, UK

This presentation outlines the experiences of Rio Tinto plc in applying the real options framework to the valuation of mining properties. It sets out our successes, the difficulties we have encountered, and one major problem that is currently halting the quantitative implementation of the real options approach within Rio Tinto.

As a company we have been using the real options approach for about 10 years. We began by treating the project value as the stochastic variable. This approach has two major deficiencies. It is difficult to parameterise the stochastic process and it is poorly suited to valuing multiple real options, which is a characteristic of almost all mining projects.

In an effort to overcome these difficulties we moved to treating the commodity price as the stochastic variable. This allows us to use futures data to parameterise the stochastic process, and coupled with the concept of switching between modes, allows the valuation of multiple American real options. Using this approach we have constructed a lattice-type model within Excel. The model uses a two-factor price process and can value three American real options simultaneously. In a mining sense, the model also allows for finite reserves, and for ore grades and production rates to vary with cumulative production.

In using this model to value mining projects we came across a number of disappointing and problematic issues. The first issue was that many of the commonly quoted options often have limited value. The second issue was just how difficult it was to reconcile our real option values with our conventional values that use a risk-adjusted discount rate. Disconcertingly, this analysis highlighted the possible importance of interest-rate risk. Allowing for both stochastic interest rates and stochastic commodity prices has received only limited attention in the literature. As such, it is difficult to know if the usual assumption of constant interest rates is reasonable, thereby detracting from the confidence we have in our calculated real option values. The third issue was the treatment of corporate debt and investor-level taxes within the real option framework. Again this is an area that seems to have received only limited attention in the literature, but is of importance if we are to have confidence in our calculated real option values. Finally an issue we have identified but not addressed is the reconciliation of real option values to quoted share prices.

In attempting to value real options, the most significant problem is estimating a long-term forward curve. While we are endeavouring to parameterise the two-factor price process by Kalman filtering futures price data, we are currently unable to get the filter to converge to a stable solution, even after scaling the variables. We believe that unless we can estimate a stable and plausible forward curve, the real options approach will have limited quantitative application within Rio Tinto.

2T. Competition and Strategy

Strategic Delay In A Real Options Model Of R&D Competition

Helen Weeds, Fitzwilliam CollegeUniversity of Cambridge

When an irreversible decision is taken under uncertainty, real options theory tells us that there is an option value of delay. From the game theoretic analysis of situations in which a small number of agents compete for the same prize, where there is an advantage to the first-mover, it is well-known that the fear of pre-emption causes agents to move sooner than would otherwise be the case. Thus, it is generally presumed that in imperfectly competitive settings the fear of pre-emption undermines option values and the predictions of the real options approach will no longer have any relevance.

In this paper, we present a real options model of R&D competition in which two firms have the opportunity to invest in competing research projects with uncertain returns. Depending on parameter values two distinct types of equilibria may arise. One is a leader-follower equilibrium in which one firm invests strictly earlier than its rival and option values are reduced by competition. In the other case, however, the outcome is a symmetric equilibrium in which both firms delay investment to a greater extent than in the corresponding model where a single firm has the opportunity to invest, in contrast with the expected outcome.

Does Waiting Matter? An Equilibrium Model With Firm-Specific Demand

Sigbjorn Sodal, Agder College, Norway

Products like pharmaceutical drugs, cars, aircraft, and computers normally require two quite different investments: R&D and production. In one sense or another, the first investment will represent a patent, while the second one implies to activate the patent. Technically, the first investment can be thought of as an option investment, and the second one as exercising the option.

Since demand or cost variables may change, it is not always optimal to undertake wide-scale investment in production right after the patent has been acquired. Such changes imply, more generally, the possibility of an increasing wedge between the net present value (in terms of sales) and the cost of production, thereby also gains from holding on to the patent instead of exploiting it massively right away. There will, however, also be a cost of this kind of waiting, since the obtained revenue must be discounted more heavily the longer production is postponed. We discuss whether the gains from waiting exceed the costs, using a stylistic one-sector model, and deriving a criterion for whether waiting is optimal. Typically, waiting is optimal if demand is highly expected to increase or if it is highly volatile, if the discount rate is small, and if the patent cost is small relative to the production cost.

Crude Oil Industry Dynamics: A Stackelberg Leader/Follower Game between the OPEC Cartel and Non-OPEC Producers

J. Tvedt (Den norske Bank, Norway)

This paper studies the dynamics in the crude oil industry. The basic model derives the price dynamics of an industry where fixed capital is produces by another industry with costs of structural changes. Due to the cost of increasing and decreasing capacity in the capital producing industry, output prices in the industry that apply the capital will follow a long run mean-reverting pattern. A stochastic partial differential equation for this price process is derived.

At any point of time the equilibrium in the oil market is model as a Stackelberg leader/follower model. The leader, OPEC, has the lowest marginal costs whereas the marginal costs of the non-OPEC producers, the followers, depend on future and present investments. Present investments are restricted by the size of the investment goods producing industry. To increase or reduce the capacity of this industry entails costs. The dynamic equilibrium in the investment goods industry is, therefore, modelled as a stochastic optimal control problem. Hence, uncertainty in the demand for oil, via the demand for oil industry investments, implies hysterisis effects in the adjustment of the capacity of the investment goods industry.

The main theoretical contribution of this paper is the effect the cartel exercises on the investments of the non-cartel producers. In a perfectly competitive market changes in investments are solely triggered by the current oil price, where the oil price is determined by current demand and production capital. However, the cartel members know that they influence the oil price by their production strategy. Hence, when choosing the optimal production path the cartel takes into account the effect this path may have on the investment decision of the non-cartel producers. Hence, the cartel production strategy is a trade-off between high oil prices and the risk of triggering non-cartel oil production investments.

The industry level model indicates that the oil price process in the crude oil market will be mean reverting. Hence, when valuing the option to invest in an oil field development, the market power of the efficient OPEC oil producers should be taken into account. Uncertainty is not only due to shifts in demand and technological shocks, but also due to strategic changes in OPEC production policy.

3A. Sharing Experiences in Pharmaceuticals & Panel Discussion

3T. Real Options, the Environment and Agency Issues

Pollution Reduction, Environmental Uncertainty, And The Irreversibility Effect

Jean-Daniel M. Saphores, Université Laval and Peter Carr, NationsBanc Montgomery Securities

This paper analyses the decision to make an investment to reduce the emissions of a stock pollutant under environmental uncertainty, which is introduced through stochastic variations in the stock of a pollutant. Two types of irreversibility are present here: the first one is environmental, because society has to live for a long time with a slowly decaying stock of pollutant; the second is economic because the investment needed to reduce the emissions of the pollutant are sunk. We use a continuous time formulation and concepts from the theory of real options to formulate and solve a social planning problem. We consider two classes of stochastic processes and obtain analytic expressions for the option value terms and the optimal stopping rules. Most of the previous work on this topic (e.g., Kolstad, 1996, and Ulph and Ulph, 1997) has been done using discrete time, two-period models that cannot fully handle the dynamics of the problem.

This paper makes two contributions. First, it shows that there is no simple irreversibility effect for the management of a stock pollutant. The irreversibility effect was introduced by Arrow and Fisher (1974) when they showed that a standard (i.e. static and deterministic) cost-benefit analysis for the development of a natural area was biased against the environment. We show that the decision to invest to reduce the emissions of a stock pollutant depends both on the type and level of uncertainty. Indeed, when uncertainty is small, it may be optimal to delay or advance this decision compared to the deterministic case, depending on the value of the parameters (mainly pollutant decay rate, social rate of discount, and cost of reducing emissions). This results from the tension between environmental irreversibility (the stock of pollutant causes costly long-term social damages), and investment irreversibility (pollution abatement investments are sunk). Moreover, when uncertainty is large enough, we find that pollutant emissions should be curbed immediately. This is to be contrasted with Pindyck's results (1994): he found that an increase in the uncertainty over the valuation of pollutant damage leads to postpone a sunk investment to reduce the emissions of a pollutant. These results have implications for global warming.

The second contribution of this paper is a clarification of the notion of option value in the environmental literature. Work on quasi-option value (Arrow and Fisher, 1974) had tried to link it with the value of information, but Hanemann (1989) showed that this interpretation does not hold when some of the basic assumptions of the Arrow-Fisher model are relaxed. By using the same formulation for both the static and the deterministic case, we show that option value (in a real options framework) can be seen as the value of the flexibility to change a decision with irreversible consequences, with or without uncertainty.

Water Management In France: Delegation And Irreversibility

Ephraim Clark, Middlesex University Business School and Gérard Mondello, LATAPSES

The problem that we address in this paper stems from the trend to delegation in the water management field. It refers to the municipality's negotiating disadvantage in the face of cartelized water management firms that makes delegation, once undertaken, virtually irreversible. We show why the characterisitics of the delegation auction render it useless as a tool for collective welfare maximization. We also show that the remaining tool for achieving collective welfare maximization, i.e. the municipality's right to revoke delegation and return to direct management, is also ineffective due to a lack of credibility that is essentially financial in nature. Thus, if the credibility of revocation could be restored, the municipality's bargaining power could also be restored. Using standard methods of stochastic calculus, we model the municipality's right of revocation as a call option held by the municipality. We show that the key variable for the value of this option, and thus for the municipality's position, is the exercise price, which is partly determined by objective economic criteria and partly by legal and institutional conventions. We show that community welfare maximisation occurs at the point where the exercise price is determined exclusively by objective economic criteria. Since the delegated firm as a simple agent has the right to abrogate the contract if delegation becomes unprofitable, we then model this right as a put option held by the firm. Its value also depends to a large extent on the exercise price, which is partly determined by objective economic criteria and partly by legal and institutional conventions. Combining the exercise points of the two options enables us to determine the price-profit interval over which delegation will be acceptable to both parties. We conclude that the optimal interval will be the one where the exercise prices are determined entirely by objective economic criteria.

Valuation of Irreversible Investments and Agency Problems

Joril Maeland (NHH-Bergen, Norway)

This article examines dynamic investment decisions when there is an agency problem. A principal delegates the decision of an investment strategy of a project to an agent. The agent has private information about the investment cost, whereas the principal only knows the probability distribution of the cost. The principal's problem is how to compensate the agent in order to optimize the value of the principal's investment opportunity.

One reason for an owner of an investment possibility to delegate the management of a project to an agent, may be that the management requires expertise that the principal does not possess, or that is too costly for him to obtain. In other cases it may be impossible for the principal to make the decisions himself, but it may be possible for him to commit to a delegation contract.

The information asymmetry creates a situation where adverse selection may occur. The agent is compensated according to a contract. The principal observes the outcome from the investment project, and the contracted compensation is a function of this variable. Owing to the asymmetric information about the investment cost, it may be optimal for the principal to leave the agent some "information rent".

The model applies to situations where the production from the project is sold in perfect markets, whereas there are imperfections due to the costs of projects.

An application of the model is the case where a government owns some natural resources. Production of natural resources involves large and (partly) irreversible investments, and uncertainty due to future output prices. A feature of production of natural resources is that uncertainty in output prices usually is common knowledge, whereas investment and production costs may be private information for those investing in and operating such projects. To exploit the resources, the government delegates the production of the resources to companies. The companies may have incentives to signal higher cost than the true cost in order to obtain a larger profit within the companies. The model presented in this paper gives the government a method of how to find the most efficient contract between the government and the companies to which it gives the right to invest in production of natural resources. The contract can be in the form where the companies are paid a compensation for the management of the resources, or it can be in the form of a taxation system.

Keynote Address

Dr. Stephen A. Ross, Massachusetts Institute of Technology

Professor Ross is the Franco Modigliani Professor of Finance and Economics at MIT and Co-chairman of Roll and Ross Asset Management Co. He previously taught at Yale University and at the Wharton School of the University of Pennsylvania. He received his Ph.D. in economics from Harvard in 1970. A Fellow of the Econometric Society and a member of the American Academy of Arts and Sciences, he currently serves as an Associate Editor of several economics and finance journals and was President of the American Finance Association.

Professor Ross is the author of more than 75 articles on a variety of topics in economics and finance (and is the coauthor of a leading introductory textbook in finance). He is best known for having invented the Arbitrage Pricing Theory and the Theory of Agency, and co-developing the risk-neutral valuation and the binomial model that enabled the practical valuation of both financial and real options. Such models are now standards for valuation in major securities trading firms and other corporations. Professor Ross' other contributions to real options specifically include the recognition that interest rate uncertainty also creates a valuable option to wait, which he will discuss in his keynote address.

Professor Ross has been a consultant to a number of investment banks and major corporations, has served as an expert advisor and advisor to various government departments, and serves on the board of major international organizations.


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