Evaluation of a mining project under the joint effect of commodity price and exchange rate uncertainties using real options valuation

Cash flows generated by mining projects tend to be volatile and are extensively influenced by exogenous variables, notably commodity prices and exchange rates. The traditional discounted cash flow (DCF) method, which is normally used for economic feasibility studies and mining project evaluations, presents inconsistencies because the method fails to adequately address uncertainties and operational flexibilities and often ignores certain specific market conditions. Numerous studies have been carried out for mining project evaluations using the real options valuation (ROV) technique for assessing commodity price uncertainty, but there is no research on the combined effects of price and exchange rate uncertainties. Therefore, in order to assess the economic viability of a mining project more accurately, the commodity price and its inherent volatility, the exchange rate and its inherent volatility, and the correlation parameters between them have been incorporated into the model and used in the evaluation process. One of the interesting findings revealed in the study is that project values are overestimated if only commodity price uncertainty is considered in evaluating the project value instead of the joint effect of commodity price and exchange rate uncertainties. This new ROV technique will explore the opportunity to utilize an alternative methodology for approximating project values and to identify valuation opportunities to enhance economic gains or to mitigate economic losses, where the DCF valuation method does not.     

生物制药项目价值评估方法研究

本文研究通过比较传统的净现值法、风险调整的净现值法以及实物期权法,研究在生物制药业项目开发阶段的价值评估的方法,说明风险调整的净现值法以及实物期权法是较好的研究生物制药项目价值评估的方法。     

Valuing Real Capital Investments Using The Least-Squares Monte Carlo Method

The recently developed least-squares Monte Carlo (LSM) method provides a simple and efficient technique for valuing American-type options. The proposed method is applicable to the cases of compound real options, like the other numerical techniques such as finite difference and lattice methods, with the additional advantage to handle easily the cases of multiple uncertain state variables with different and complex stochastic processes. With this advantage, the LSM method is not only efficient for valuing multi-factor American options, but it can also be extended for valuing complex real investments having many embedded real options and involving multiple uncertain state variables. This article examines the applicability of the LSM method in valuing real capital investments. Two valuation examples have been provided to test the efficiency of the proposed method in both the valuation and the decision-making processes.     

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.     

Real Options—An Introduction and an Application to R&D Valuation

In this short paper, we summarize the real options approach and show how it can be used to introduce flexibility into the capital budgeting process. We then go on to show an application of real option evaluation to research and development valuation in the pharmaceutical industry. Our calculations and illustrations are in Excel and can be easily replicated.     

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.     

R&D as an option on market introduction

Discounted cash flow methods for making R&D investment decisions cannot properly capture the option value in R&D. Since market and technology uncertainties change expectations about the viability of many new products, the value of projects is frequently adjusted during the R&D stages. Capturing the adjustment in expectations has an option value that may significantly differ from the Net Present Value of R&D projects. However, there are no historic time series for estimating the uncertainty of the value of R&D projects. As a result, the standard Black and Scholes model for financial option valuation needs to be adjusted. The aim of this paper is to report the application of a particular option pricing model for setting the budget of R&D projects. The option value of the model captures jumps or business shifts in market or technology conditions. The approach originates from applying current insight into the valuation of R&D projects to the field of multimedia research at Philips Corporate Research. This way, the gap between real option theory and R&D practice is further diminished.     

Valuation of Learning Options in Software Development Under Private and Market Risk

Commercial software development is an inherently uncertain activity. Private risk is high, schedule and cost overruns are common, and market success is elusive. Such circumstances call for a disciplined project evaluation approach. This paper addresses the use of market and earned value management data in assessing the economic value of commercial software development projects that are simultaneously subject to schedule, development cost, and market risk. The assessment is based on real options analysis, a financial valuation technique that can tackle dynamic investment decisions under uncertainty. The paper demonstrates the application of real options analysis to a development scenario that consists of two consecutive stages: a mandatory prototyping stage and an optional full-development stage. The full-development stage is undertaken only if the prototype is successful and the market outlook is sufficiently positive at the end of the prototyping stage, thus giving the full-development stage the flavor of an option. The project's staged design increases its value. Real options analyses capture the extra value due to optionality.     

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.     

A REAL OPTIONS DESIGN FOR QUALITY CONTROL CHARTS

We develop a financial model for a manufacturing process where quality can be affected by an assignable cause. We value the real options associated with applying a statistical process control chart using the Black-Scholes equation, binomial and pentanomial lattices, and Monte Carlo simulation methods. This valuation gives decision makers a way to choose the appropriate quality control strategy based on an integrated view of the market dynamics with the manufacturing operational aspects. An industry case is used to demonstrate the application of real options to value control chart decisions. Web based programs are given to value the alternatives in the case study, making the valuation task accessible to other users.     

Real options valuation: the new frontier in R&D project evaluation?

The real options approach has recently received growing attention in R&D and Technology Management research. Recent empirical findings by Ellis (1997) and Busby and Pitts (1997) also report growing attention and use in practical investment decisions. However, there is a certain concern about the applicability to a wide range of R&D related problems. The theoretical base behind options valuation is derived from the capital markets and thus assumes market conditions that are closer to the theoretical construct of 'perfect competition' than most other settings. Even under these conditions, several assumptions made and difficulties left are subject to controversial discussions. Of course these problems even gain importance when the R&D environment with its discontinuities and lack of regulation or institutionalized trade is assumed. This paper describes some basic properties of the real options approach and sheds light on existing problems for the application in R&D project evaluation. On the other hand, roads to application of the method are shown using the Geske model of option evaluation. One main goal of the paper is to broaden and deepen the discussion on real option models in R&D and Technology Management, which has in some cases been limited to stressing the advantages of the method rather than reflecting on applicability and concrete way of application of the method.     

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.     

ECONOMIC ANALYSIS IN THE MAINTENANCE,REPAIR, AND OVERHAUL INDUSTRY: AN OPTIONS APPROACH

This paper presents a practical case application of the real options framework to a multi-stage investment in the aerospace maintenance, repair, and overhaul (MRO) industry. With the deregulated commercial airline industry and military procurement reform, the $44 billion MRO sector must implement tools to remain strategically poised. In this case study, the MRO participant values a multi-stage irreversible expenditure in maintenance equipment and processes under air travel demand uncertainty using a real options analysis. The investment scenario is viewed from a delay, growth, and compound options framework, and an appropriate sensitivity analysis is performed. The main contribution of this paper is the detailed real option framing, valuation, and discussion that may be used as an illustration for industry practitioners or classroom instruction.     

The Impact of Volatility on Firms Holding Growth Options

“Abuses of real option valuation were partly behind the ramping and subsequent deramping of the 2000 internet techno bubble. No one ever got to eat the free lunch these real option 'theorists' promised. No one ever will; no one ever could.” (Mayor 2001, 53) Growth options contribute to over 95% of the market value of Internet stocks such as Amazon.com, America Online, and eBay. Finance theory often promotes market volatility as being desirable for investors holding financial options. Is volatility also desirable for firms holding growth options? While many argue that it is, this paper presents a simple example illustrating that increasing volatility can destroy growth option value, especially for firms holding “quality” growth options.     

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.     

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.     

Valuation of R&D real American sequential exchange options

Valuation of R&D real American sequential exchange options requires specifying the pattern of R&D expenditures and the stochastic process of the eventual R&D project. We model the stages of R&D expense and then the ultimate discovery (and the development cost for the discovery) using real sequential (compound) exchange option models. We study E_Commerce R&D, so the timing is relatively short‐term, with initial R&D, a second phase of R&D, and a final development phase, when the project values are realized. We use proxies from the financial markets for expected project value and cost volatilities (and correlation). Then the real option valuation is based on an approximate American sequential exchange option.     

Integrating Real Options with Managerial Cash Flow Estimates

This article presents a real options model that fits managerial cash flow estimates (optimistic, likely, and pessimistic projections) to a continuous geometric Brownian motion (GBM) cash flow process with changing growth and volatility parameters. The cash flows and the value of a project are correlated to a traded asset, so the real option is priced under the risk-neutral measure with a closed-form solution. The analysis is extended to a sequential compound call option for investments over multiple periods. If the project is correlated to the market, then some of the risk may be mitigated by a delta-hedging strategy. A numerical example shows that the effect of the correlated asset on the real option value is significant, and the relationship between the volatility of the project and the real option value is not analogous to the typical relationship found in financial option pricing. Integrating the expertise and industry knowledge of management, this approach makes possible a more rigorous estimation of model inputs for real option pricing.     

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.