Project valuation in the pharmaceutical industry: a comparison of least‐squares Monte Carlo real option valuation and conventional approaches

Least‐squares Monte Carlo simulation (LSM) is a promising new technique for valuing real options that has received little or no attention in the pharmaceutical industry. This study demonstrates that LSM can handle complex valuation situations with multiple uncertainties and compounded American‐type options. The limited application of real option valuation (ROV) in the pharmaceutical industry is remarkable, given the importance of accurate project valuation in an industry that requires large investments in high‐risk projects with long pay‐back periods, which is furthermore suffering from ever‐increasing development costs and shrinking profit margins. The LSM model developed in this study is constructed as an extension of a discounted cash flow model that should be familiar to economists active in the pharmaceutical industry. A number of pharmaceutical projects have been evaluated using LSM ROV, binominal real option valuation and expected net present value techniques. The different results yielded by these methods are explained in terms of differences in risking assumptions and ability to capture the value of flexibility. The analysis provides a framework to introduce the basic concepts of real option pricing to a non‐specialist audience. The LSM model illustrates the potential for real‐life commercial assessment as the versatility of the technique allows for an easy customisation to specific business problems.     

Strategic planning: valuing and managing portfolios of real options

This article presents a value-based strategic planning framework suitable for valuing and managing portfolios of corporate real options. The proposed framework combines insights from strategic management theory with novel quantitative valuation tools from finance. Strategic planning is viewed as a process of actively developing and managing portfolios of corporate real options in the context of competitive interactions. As such, the expanded valuation framework recognizes that future growth opportunity value deriving from the firm's resources and capabilities must explicitly account for uncertainty, adaptability, and competitive responsiveness. The resulting expanded valuation framework is able to capture the value of the adaptive resources and capabilities that enable a firm to adapt and re-deploy assets, develop and exploit synergies, and gain competitive advantage via time-to-market and first- or second-mover advantages. We show how two basic metrics in this value-based framework, current profitability of assets in place and future growth option value, can be obtained from financial market data and how they can be used in active portfolio planning.     

Optimal exploration investments under price and geological‐technical uncertainty: a real options model

This article develops a real options model for valuing natural resource exploration investments (e.g. oil or copper) when there is joint price and geological‐technical uncertainty. After a successful several‐stage exploration phase, there is a development investment and an extraction phase. All phases are optimized contingent on price and geological‐technical uncertainty.
Several real options are considered. There are flexible investment schedules for all exploration stages and a timing option for the development investment. Once the mine is developed, there are closure, opening and abandonment options for the extraction phase. Our model maintains a relatively simple valuation structure by collapsing price and geological‐technical uncertainty into a one‐factor model.
We apply the model to a copper exploration prospect and find that a significant fraction of total project value is due to the operational, development and exploration options available to project managers.     

Toward a behavioral theory of real options: Noisy signals,bias, and learning

Research Summary: We develop a behavioral theory of real options that relaxes the informational and behavioral assumptions underlying applications of financial options theory to real assets. To do so, we augment real option theory's focus on uncertain future asset values (prospective uncertainty) with feedback learning theory that considers uncertain current asset values (contemporaneous uncertainty). This enables us to incorporate behavioral bias in the feedback learning process underlying the option execution/termination decision. The resulting computational model suggests that firms that inappropriately account for contemporaneous uncertainty and are subject to learning biases may experience substantial downside risk in undertaking real options. Moreover, contrary to the standard option result, greater uncertainty may decrease option value, making commitment to an investment path more effective than remaining flexible. Managerial Summary: Executives recognize the need to make uncertain investments to grow their business while mitigating downside risk. The analogy between financial options and real corporate investments provides an appealing method to consider the practical challenge of such investment decisions. Unfortunately, the “real options” analogy seems to break down in practice. We identify how a second form of uncertainty confounds real options intuition, leading managers to overestimate the value of uncertain investments. We present a behavioral real options model that accounts for both forms of uncertainty and suggest how uncertainty interacts with behavioral bias in the option execution/termination decision. Our model facilitates assessment of the conditions under which investments in uncertain opportunities are usefully considered as real options, and provides a means to evaluate their attractiveness.     

Non‐additivity in portfolios of exploration activities: a real options‐based analysis of equity alliances in biotechnology

Firms invest in exploration‐oriented activities to seek competitive advantage and in response to changing environments. Real options formulations represent an emerging strand of thinking on such investments. In this paper we begin with the observation that firms often simultaneously invest in multiple exploration projects. We identify two sources of potential interactions among these real options investments. First, we investigate the effects of correlations between the outcomes in different options. Second, we analyze the effects of investments that are fungible across project options. We show that under different conditions multiple options can be sub‐additive (due to redundancies in outcomes) or super‐additive (due to fungible inputs). We test the implications of our model with data from the biotech industry and find supporting evidence. Our model and results have some interesting implications for the exploration literature and real options lens. Copyright © 2004 John Wiley & Sons, Ltd.     

EXPLOITING UNCERTAINTY—INVESTMENT OPPORTUNITIES AS REAL OPTIONS: A NEW WAY OF THINKING IN ENGINEERING ECONOMICS

A new trend in corporate planning is to exploit uncertainty by taking investment opportunities as real options. This options approach is to complement the conventional net present value (NPV) criterion in evaluating risky investments. In this paper, we take a broad look at the real options approach to various engineering economic decision problems, laying out how it provides an immediate and important perspective on value creation in an uncertain world. Unlike financial options, real options analysisdeals with investments in real assets, which is one of the primary interest areas in engineering economics. For that reason, we believe that any advancement in the real options decision framework will benefit the field of engineering economics.     

Beyond invention: the additive impact of incubation capabilities to firm value

Incubation is a process whereby the firm nurtures breakthrough discoveries and inventions to test their potential as new business platforms. The recent emergence of organizational roles associated with innovation incubation shows that internal incubation is becoming recognized as an important organizational capability. This development also suggests that firms that invest in discovery for competitive advantage recognize a need to leverage that investment more fully. While case studies describe incubation activities and note their importance, empirical research linking this capability to firm performance is limited. The current study represents an initial attempt at exploring the relationship empirically. Our main finding is that financial markets have difficulty valuing a firm's exploratory discovery investments and that the presence of an incubation capability positively moderates the impact of such investments on firm market valuation. The implication of this result is that investments in certain types of R&D may be suboptimized if there is not a parallel investment in a capability to incubate the opportunities that arise from potentially breakthrough inventions.     

Closed-Form Mortgage Valuation Using Reduced-Form Model

Valuing mortgage-related securities is more complicated than valuing regular defaultable claims due to the borrower's prepayment behavior as well as the possibility of default. Some researchers use a structural-form model to obtain the closed-form formulas for the mortgage value. With this method, however, it is difficult to identify the critical region of early exercise. As an alternative, the reduced-form model developed in this article is able to value the mortgage without setting boundary conditions, and it can thereby accurately handle the multidimensional space of correlated state variables. The purpose of this article is to derive a closed-form solution of the mortgage valuation equation under a general reduced-form model that embeds relevant economic variables. This new approach enables portfolio managers to undertake sophisticated portfolio optimization and hedging analyses. An implementation procedure for the model is also provided to demonstrate how the valuation framework can be utilized in practical applications.     

Oil and Gas Exploration Valuation and the Value of Waiting

The timing flexibility of investments in oil and gas assets can potentially add value. In this article, we examine the value of waiting in exploration projects and propose a real option–based valuation method using least-squares Monte Carlo simulation. We show that the dynamics of the oil and gas prices have a large impact on the value of the option to wait, especially for projects with long lead times and durations. The uncertainty in the forward price curve is modeled using a two-factor stochastic price process. The article also presents the valuation method in the form of MATLAB functions and routines that can be used as an efficient test and analysis platform using the industry-standard input formats.     

Compensation Options in Joint Ventures. A Real Options Approach

This research focuses on a cluster of dynamic reallocation and restatement of ownership clauses contained in joint venture agreements. These clauses, with potentially significant financial implications, govern the transfer of rights between the parties on two key financial issues: the allocation of profits and losses and the ownership interests in the joint venture. The central contribution of this research is to consider these clauses themselves as non-standard real options and to propose a methodology for assessing their values. Determination of such values will be essential throughout the joint venture negotiation process. In addition, we provide valuable information on another key question of managerial importance: estimating the downside risk of a clause so that the affected party can design a hedging strategy. Two actual case studies extracted from recent joint ventures have been used to stress the importance of these concepts and to develop suitable valuation techniques. The theoretical framework is based on real options methodologies. However, the clauses studied involve real options with non-standard features (compensation options and options with uncertain initial date). Therefore, we have developed ad hoc valuation models with user-friendly numerical examples in spreadsheet format.     

Uncertainty and the market valuation of R&D within a real options logic

The aim of this study is to provide new theoretical insights and empirical evidence on the effect of market and technological uncertainty on the market valuation of a firm's R&D capital. A set of hypotheses is developed adopting a real options logic and tested on a panel dataset of 290 manufacturing firms traded in the UK. Consistently with our theoretical model, we show that market and technological uncertainty have distinct effects on the valuation of R&D investments. The results have several important implications for resource allocation to R&D under uncertainty, which we discuss in the concluding section. Copyright © 2008 John Wiley & Sons, Ltd.     

A BETTER UNDERSTANDING OF WHY NPV UNDERVALUES MANAGERIAL FLEXIBILITY

The Real Options paradigm addresses the valuation of managerial flexibility in capital budgeting. Despite the great strides achieved by researchers in this field, many financial analysts have chosen not to adopt this new paradigm due to a lack of comfort with the approach and the mathematical complexity of the valuation models. This article shows how some projects with real options can be valued using simple and familiar tools-discounting expected cash flows after adjusting the discount rate. Unless the discount rate is adjusted to account for the impact of real options on risk, a traditional net present value (NPV) analysis misses the value of flexibility. By narrowing the gulf between Real Options analysis and more familiar tools, the weighted average discount rate (WADR) approach introduced in this paper may help novices better understand die Real Options paradigm, which subsequently may gain the wider acceptance it deserves. Though the WADR approach is practical only for simple real options, comfort with the approach may encourage analysts to pursue more advanced and robust real option valuation techniques for more complex applications.     

An Options Approach to Valuing Expansion Flexibility in Flexible Manufacturing System Investments

Flexibility in manufacturing processes provides an ability to change or even reverse the decisions made in earlier periods. The traditional economic evaluation methods of investments in flexible manufacturing systems ignore the value of flexibility, which should be one of the key issues in the justification process. Options approach appears as a means of overcoming the limitations of conventional discounted cash flow methods. In this work, a methodology for valuing expansion flexibility of flexible manufacturing systems is presented. Expansion flexibility in a phased manufacturing investment can be valued by viewing an initial investment as being analogous to purchasing an option to exchange one risky asset for another risky asset within a time period from the initial investment. While keeping the option to expand is of value, a thorough analysis requires that the opportunity cost of delaying expansion be taken into account. In this paper, an analytic approximation methodology for valuing sequential American exchange options on dividend paying stocks is employed for valuing expansion flexibility. A comprehensive numerical example is presented to illustrate the approach, and sensitivity analyses are performed.     

Dark Fiber Valuation

Valuation of dark fiber has recently generated controversy, sparked particularly by the large sums booked for swaps of dark fiber between companies. One of the issues raised is valuation: i.e., what is the value of an asset that generates no revenue now and may do so at some unknown point in the future but only after investment, in an uncertain business climate, and where prices are dropping? The picture is further complicated because the result of investing to bring the asset to market (i.e. lighting the fiber) changes the supply and demand conditions of the market itself and hence invalidates price predictions. A realistic and consistent valuation methodology is necessary for increasingly cautious companies, auditors, and investors. In this paper we describe such a valuation methodology for dark fibre based on real options. Publicly available bandwidth price services start to make this practical by providing market price information. For dark fibre valuation the real option to be valued are the lighting decisions. We specifically include the effect on the market of adding new capacity by using the price-elasticity of demand within the stochastic price process itself, conditional on lighting decisions. Prices are generally volatile and decreasing with time. The evolution of lighting costs and maintenance are included in the valuation. The real options technique used here is novel in that it combines economic and market factors explicitly with mathematical finance to arrive at a valuation and optimal decisions. We found that the optimal lighting riming and capacity decisions to depend on many of the factors included in the analysis with no simple triggers: the details really matter.     

Demand Uncertainty,Development Timing and Leasehold Land Valuation: Empirical Testing of Real Options in Residential Real Estate Development

This article develops and tests a long‐dated American call option pricing model for valuing development land under leasehold. We analyze and test option values in ten detailed Hong Kong cases involving purchase, holding, converting and developing land. We also test for optimal exercise of long‐dated American calls using processes based on the optimal trigger ratio feature of the perpetual American call option model. Generally, the empirical results confirm presence of a positive and nontrivial option premium (mean +5.274%) in the cases, and that developers appear to delay exercise to the point predicted by the real options model.     

Valuation and Efficiency in the Market for Creatively Financed Houses

This paper examines two alternative approaches to valuing the impact of creative financing on housing prices. The cash equivalence adjustment which is the generally accepted approach is compared to an approach known as the financed fee valuation adjustment which is argued to be theoretically superior. A sample of 45 matched pairs of condominium sales in which one of the units is creatively financed and the other is conventionally financed is employed to test which model is most effective at explaining the market adjustment for creative financing. The authors are unable to reject the hypothesis that the housing market being examined is efficient and that the financed fee valuation adjustment is a superior model for valuing the impact of creative financing.     

Pricing real growth options when the underlying assets have jump diffusion processes: the case of R&D investments

Numerous previous studies have demonstrated that research and development (R&D) investments can be evaluated by a real growth options approach. However, few studies have constructed evaluating models which consider the important R&D characteristics, including uncertainty regarding the project value, investment cost, and jump diffusion processes. The contribution of this study is not only to derive a model for evaluating R&D investments to conform to these key characteristics of R&D activities but also to build a real option pricing method that is more general than comparative important models, such as the theoretical papers of Black and Scholes (1973), Merton (1976), and Fischer (1978), and the application paper of Brach and Paxson (2001). This study also presents sensitivity analyses which illustrate the dynamic relationship between the real growth option value and the project value, investment cost, and main jump parameters. Hopefully, the results of this study can provide a useful reference for managers, and help them make better evaluations of R&D investments.     

CEO career horizon,corporate governance,and real options: The role of economic short‐termism

Research Summary: Combining studies on real options theory and economic short‐termism, we propose that, depending on CEOs’ career horizons, CEOs have heterogeneous interests in strategic flexibility, and thus, have different incentives to make real options investments. We argue that compared to CEOs with longer career horizons, CEOs with shorter career horizons will be less inclined to make real options investments because they may not fully reap the rewards during their tenure. In addition, we argue that long‐term incentives and institutional ownership will mitigate the relationship between CEOs’ career horizons and real options investments. U.S. public firms as an empirical setting produced consistent evidence for our predictions. Our study is the first to theoretically explain and empirically show that a CEO's self‐seeking behavior will impact real options investments. Managerial Summary: This article helps to explain how a CEO's self seeking‐behavior may shape a firm's real option investment, which could result in different level of strategic flexibility. We argue that CEOs with short career horizons have less time to exercise their firms’ real options, which should lower the investments in the firms’ real options portfolios relative to CEOs with long career horizons. We study a sample of U.S. public firms and find strong evidence that a CEO's expected tenure in the firm is positively related to the real options investments at the firm level. We find that this agency issue can be mitigated by adopting appropriate corporate governance mechanisms such as long‐term incentives and institutional investors.     

A REAL OPTIONS DESIGN FOR PRODUCT OUTSOURCING

Product outsourcing is recognized as a way to gain flexibility for competitive advantage. We formulate the outsourcing problem using real options. We develop a financial model to assess the option value of product outsourcing. Specifically, we consider a three state-variable problem and use Monte Carlo simulation to estimate the value of the option. This valuation gives decision makers a way to choose the appropriate outsourcing strategy based on an integrated view of the market dynamics. A case example from the apparel manufacturing industry is used to demonstrate the application of real options to value outsourcing flexibility. We show that the inability of classical net present value methods to address dynamics in the market condition leads to an undervaluing of the outsourcing strategy. Numerical results and sensitivity analysis show how the real options approach can be used to give a better view of the long-term value of outsourcing.     

Making real options work for practitioners: a generic model for valuing R&D projects

We propose a generic valuation framework for the appraisal of R&D projects based on real option theory. The added value of this approach is the presentation of a model that was implemented in a manner that allows corporate decision makers to use real options in an intuitive and standardized way. The project valuation procedure is separated into three main phases: project modeling, data and input collection, and result generation and analysis. The project model represents the structure of the real world R&D project with its investments, expected results, and decisions that need to be taken conditionally on the outcomes of research activities. The project model is represented in the form of a decision tree, where different research results or taken decisions lead to new branches. In this way, every possible situation the project can pass through can be represented. Uncertainties are separated into market uncertainties (e.g., market prices) and project specific, private uncertainties (e.g. uncertainty of research results). For both uncertainties, event trees are constructed which are then combined and merged with the above mentioned decision tree in order to represent the value evolution of the R&D project under given decisions and uncertainties. For every possible state of the project the real option value is calculated. By creating multidimensional trees, a multitude of decision steps and various kinds of real options (e.g., continue, expansion, switch, abandonment) can be modeled. The calculation complexity for the decision trees is given. From the tree structure we can calculate the real option value of starting an R&D project, i.e., the value of undertaking the first investment and thus acquiring the subsequent decision opportunities given by the completion of the first research effort. Furthermore, the optimal exercise strategy is derived from the decision tree. The exercise strategy gives the manager the possibility to have an a priori overview of where an R&D project may lead to, which decisions need to be taken in which circumstances, and when the project needs to be stopped in order not to generate losses. In an in‐depth case study we use an illustrative R&D project to set up and discuss the three phases of project modeling in the real options framework: building the multidimensional decision tree, input generation, and calculation of the real option value as well as the optimal strategy for the R&D project.