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DAY 1 - THURSDAY, JUNE 23
Welcome & President’s Address
Mergers, Acquisitions, JVs and Strategic Alliances
Real options “in” projects are the latest extension of real options theory into physical systems design. Real options “in” projects are different from real options “on” projects. Real options “on” projects refer to the standard real options treating the physical systems as a “black box”, while real options “in” systems concern design features built into the project or system. This paper defines real options” in” projects, addresses their special issues, and presents possible valuation methods. Although the crux of financial options theory – especially the “no arbitrage” assumption – is hardly valid for real options “in” projects, this paper argues that the definition of options - right not obligation - defines basic unit of flexibility. Options thinking offers important insights into flexibility in physical systems.
This paper treats the issue of flexibility in long term planning decisions. By shedding light on the converging and complementary features of Real Options Valuation (ROV) and Robustness Analysis (ROA), we suggest a new framework for assessing investments decisions under uncertainty. A two-dimensional model is thus provided to measure the feasibility of long-range investments. Five location decision projects are hence analysed for illustration.
This paper presents a real options approach to the valuation of modular projects, focusing in the value of splitting. Building on the Baldwin and Clark (2000) approach to modularity it proposes a more general model which includes the possibility of delaying the option to split, the effct of the correlations between the system and the modules and assumes a multistaged product development. We study the impact of some of the variables which influence the optimal modular strategy showing that modularisation increases value depending on the relative values, costs and risk of each modular configuration.
Thursday 11:15 – 12:30
Mergers, Acquisitions, JVs and Strategic Alliances
Chairperson: B. Lambrecht, Lancaster U., UK
This paper uses a unified treatment of real options and game theory to examine the occurrence of bidding contests within a competitive environment of imperfect information and asymmetric bidders. Competing potential buyers may sequentially perform due diligence and incur costs (option premium) to become informed about their firm-specific target value (underlying value) before making a bid (exercise price). The first player’s bid reveals a signal on its own and the rival’s target value, thereby affecting the value of the rival’s option to bid on the target and the probability of a bidding contest. We find that bidding contests are more likely to take place between moderately correlated buyers, whereas rather diverse or just very similar buyers are less likely to compete.
The main goal of this study is to design practitioners’ friendly methodologies, in a real options framework, when designing joint venture (JV) agreements. Avoiding the general issue of JVs design, we illustrate the application of real options methodology by valuing specific clauses in JVs agreements extracted from usual practice. On the other hand, we have tried to contribute to real options field by designing valuation methodologies of those options embedded in the JVs agreement with certain nonstandard features, which are due to the specific modeling required in order to capture the most interesting nature of JVs clauses (“Compensation Options” and “Options with Uncertain Initial Date”).
This paper reveals an international merger valuation model using stochastic real exchange rate which follows geometric Brownian motion and square root of mean reverting process as an index to investigate how the decision making of international merger when two domestic firms match two foreign firms under two single-channel strategy-alliances in duopolistic market. The proposed model applies game options to evaluate the before and after project values of international merger and analyzes the threshold of international merger which are dealt with the real exchange rate. Under the assumption that the specific profit function of firms is given, the thresholds of real exchange rate are evaluated and the numerical examples of sensitivity analysis are also made. The results of numerical analysis could provide the decision maker to refer either to continue strategy alliance or make international merger decision. The analysis result of this paper finds that with high volatility in real exchange rate, the firm is unlikely to taking an international merger action. The reactions of the leader and the follower are different in many concepts. The follower is more risk aversion than the leader and the leader usually has more advantages than the follower because the earlier wins the more market share. This paper concludes that the investment cost and the return affect the decision of merger. In addition, from the results of analysis using numerical examples, after mergering, a large firm scale gets more benefit than a small firm scale.
Thursday 1:30 – 3:10
Strategy and Competition Games
Chairperson: M. Boyer, Université de Montréal, Canada
This paper investigates an interaction between the managerial flexibility and the competition in a dynamic situation. The value of the flexibility can be valued as a real option while the competition can be analyzed with the game theory. We consider a multi-stage game with two firms under demand uncertainty. In the model, One firm called firm L firstly makes an investment decision, and the other firm called firm F decides secondly after observing firm L’s decision at each stage. The model developed here is an extension of the two-stage investment game of Imai and Watanabe(2005), which fully characterize the equilibrium strategies for the two competitive firms by their investment costs. We show that the project values for both firms can be considered as a special example of switching options, and hence these values can be evaluated by the extended switching option model. We apply a binomial or a trinomial lattice to the underlying demand process. Although the lattice model is discrete it is a well-known fact that the trinomial process can converge e±ciently to the continuoustime process if parameter values of the lattice model are carefully chosen and the number of trading periods tends to infinity. Hence our model can be also considered as an approximation of the continuous-time model. This paper analyzes equilibrium strategies and project values of the two competitive firms quantitatively under more realistic situations. In addition, by comparing our model with the two-stage game we can investigate the e®ects of multiple decision opportunities under a more realistic demand process.
Strategic real options models get more and more attention in the literature these days. In most of these models it is assumed that there are two firms holding the option to invest. From Nielsen (2002) we know that competition leads to earlier investment, i.e. the leader in the duopoly invests earlier than a monopolist. A natural question is what will happen to this result if a third firm is added to the model. In this paper the standard strategic real options model (cf. Dixit and Pindyck (1994, Chapter 9.3) and Nielsen (2002)) is extended to three firms.
It turns out that two cases can be distinguished. In the first case the three firms invest sequentially. In the second case the first and the second investments are made simultaneously. A condition is derived that states which case prevails. The region for sequential investment decreases with uncertainty. Furthermore, we show that the first investment in the three firm case can be either earlier or later than the first investment in duopoly.
We study the development of a duopoly − firm capacities and competitive behavior − in a continuous-time model of capacity investment. We evaluate the investment real options in that context. In the early industry development phase, firms attempt to preempt each other, so that the first industry investment occurs earlier, hence is riskier, than socially optimal. While capacity units are costly, indivisible, durable, and large relative to market size, early entry cannot secure a first-mover advantage and both firms are active beyond some level of market development. Once both firms hold capacity, tacit collusion, taking the form of postponed capacity investment, may occur as a Markov Perfect Equilibrium. Volatility and the expected speed of market development play a crucial role in competitive behavior: we show that a tacit-collusion equilibrium do exist when market growth is highly volatile and/or very rapid.
Empirical examination of certain industries shows heterogeneity on the degree of specificity of the assets employed by different firms. This paper studies why such asymmetries may be observed based on the strategic implications of asset specificity in an uncertain environment. To this end, we present a new class of real options games with a binary entry mode in which exit is allowed. Thus, firms can choose the timing of (dis)investment in an asset whose degree of specificity is selected when entering the market, which affects incentives to wait and see, and hence preemptive incentives. We analyze why ex ante identical firms not only choose to enter and exit at different dates, but usually choose to invest in assets with different redeployment/resale values.
Thursday 3:45 – 5:00
Chairperson: S. Scholtes, U. Cambridge, UK
In this paper we consider partnership deals under uncertainty but with downstream flexibility. We confine ourselves to bilateral deals and focus on the eect of options on the synergy set, the ‘core’, of a partnership deal. We distinguish between cooperative options, which are exercised jointly and in the interest of maximizing the total deal value, and non-cooperative options, which are exercised unilaterally in the interest of one partner's payoff. We provide a simple framework that illustrates options eects in a two-stage model. The model can be readily extended to a binomial lattice. We investigate options eects in the presence of risk-aversion and in the presence of complete markets.
This paper develops a stochastic differential game framework for analyzing strategic exercise of options. We focus on research and development (R&D) competition in information technology (IT) investment projects with technical and market uncertainty. According to the theory of real options and game theory, uncertainty generates an option value of delay which can be diminished by the threat of competition. An important feature of the IT projects is that the firms make investment decision on an ongoing basis before the success of the R&D process. Consequently, repeated strategic interactions may facilitate self-enforcing tacit collusion on R&D. We explore the possibility of defining a collusion (cooperative) equilibrium based on the use of a trigger strategy with an information time lag. When the information time lag is long, a preemptive (noncooperative) equilibrium emerges in which the option values of delay are reduced by competition. When the information time lag is sufficiently short, a collusion equilibrium emerges in which investment is delayed more than the single-firm counterpart. An analysis of the equilibrium exercise policies of firms provides a potential explanation for several otherwise puzzling innovation market phenomenons. We also analyze the role of uncertainty on the likelihood of tacit collusion on R&D and provide implications of strategic effects for antitrust and merger control policies.
This paper investigates how partners (firms or husband and wife) should invest into an uncertain, stock that provides a common good and when to stop investments and when to terminate the partnership. The assumption of lumpy investments leads to a real option problem which is solved for the cooperative and non-cooperative (Nash competition) solution. Yet despite the analytical solution (of the value functions, which are structurally identical for the two cases, Nash competition and cooperation), numerical means are necessary to investigate economic consequences: strong incentives to free ride under competition even turning one of the options - to stop investment at high stock levels - into one of a negative value; in contrast, divorce remains a positively valued option.
Panel Discussion (joint with Managerial Conference)
Valuation, Technology and Corporate Strategy:
Current Status, Challenges and Prospects
Moderator: Dean Paxson, Manchester Business School
James Alleman, U. Colorado and Columbia U.
Arsia Amir Aslani, Real Options Group
Vladimir Antikarov, Monitor Group
Rainer Brosch, Boston Consulting Group
Richard de Neufville, MIT
Gill Eapen, Principal, Decision Options LLC
Onno Lint, European Business School, Germany
Scott Mathews, Boeing Company
DAY 2 – FRIDAY, JUNE 24
Friday 8:30 – 9:45
I. Conceptual Issues
Chairperson: T. O’Leary, U. Manchester, UK, and U. Michigan
It is fundamental to good governance that corporate decision makers be well informed, have the knowledge-base necessary to use the information effectively, and share the same motivations as the owners. Further, managers must provide owners with accurate, timely, and complete disclosure of the company’s positions. Regarding the first part of the problem, value based inc entive systems have been under development in order to aid in resolving conflicts of interest between owners who lack the specific information (or the background knowledge to utilize it) and the managers who act as their agents. Such systems often focus exclusively upon cash flows relative to resource investment; yet, share values are often substantially greater than the amount that could be explained by expected cash flows from existing operations. Indeed, in some firms the majority of share value may de rive from growth opportunities or other real options that add flexibility or reduce risk. So, value basedincentive systems could be improved by explicitly rewarding actions that create or enhance the firm’s real options. Further, satisfactory disclosure requires that accounting reports include adequate information about the firm’s real options, with market-based mechanisms for defining the necessary information and calling it into the appropriate arena.
Perhaps the primary unresolved real options research problem is still how to develop defensible model inputs. In this paper, we address this problem by presenting an analytic theory and related methodology, Knowledge Valuation Analysis (KVA), which provides a new source of raw data for use in real options analysis. Based on complexity theory, KVA functions much like accounting and is easily utilized to resolve the troublesome limitations of current real options approaches. We also present a new area of finance, based on KVA, that we call Sub-Corporate Finance.
This paper develops some results regarding the economic value added and real
options. We use Merton’s (1987) model of capital market equilibrium with incomplete information to introduce information costs in the pricing of real assets. This model allows a new definition of the cost of capital in the presence of information uncertainty. Using the methodology in Bellalah (2001, 2002) for the pricing of real options, we extend the standard models to account for shadow costs of incomplete information.
II. Valuing Natural Resources/Energy Investments
Chairperson: M.A.G. Dias, Petrobras, Brazil
In this paper we analyze the valuation of options stemming from the flexibility in an Integrated Gasification Combined Cycle (IGCC) Power Plant.
First we use as a base case the opportunity to invest in a Natural Gas Combined Cycle (NGCC) Power Plant, deriving the optimal investment rule as a function of fuel prices and the remaining life of the right to invest. Additionally, the analytical solution for a perpetual option is obtained.
Second, the valuation of an operating IGCC Power Plant is studied, with switching costs between states and a choice of the best operation mode. The valuation of this plant serves as a base to obtain the value of the option to delay an investment of this type; it deals with an American option on a series of European nested options.
Finally, we derive the value of an opportunity to invest either in a NGCC or IGCC Power Plant, that is, to choose between an inflexible and a flexible technology, respectively.
Numerical computations involve the use of one- and two-dimensional binomial lattices that support a mean-reverting process for the fuel prices. Basic parameter values refer to an actual IGCC power plant currently in operation.
Keywords: Real options, Power plants, Flexibility, Stochastic Costs.
In the oil and gas industry, producers often happen to own adjacent lands in which they may do production in the future. Should their lands are not next to each other, producers' decision may become very well simple. Their optimal operating strategy can be achieved by following a classical real option approach, which has been addressed by many of the precedential real option papers. However, it is worth noting that there is some difference when these producers are adjacent. The network effect resulting from the reduced toll rate charged by the pipeline company might motivate the leader(who starts investment and production first) to build a larger gas plant so that the leader can use a reasonable leasing rate to induce the follower to start production earlier without building up its own gas plant. This paper will actually discuss the the dynamics of leasing fee and the network effect and the interaction between these two factors and the optimal entry point for both the leader and the follower under some game theory consideration.
Friday 10:20 – 12:00
I. Empirical Evidence
Chairperson: E. Clark, Middlesex U., UK
Despite a large body of literature on the topic, empirical tests of real option models are scarce. The lack of data offers an initial explanation for this. However other intrinsic reasons could well explain why real options are difficult to test on large-scale studies. We show that the use of case studies is a partial solution to this problem since it improves our understanding of management’s behavior but not test the validity of real option models.We support our argument by the analysis of 4 empirical studies traditionally quoted in the real options literature as well as on a real-life case study.
Real option and dynamic asset valuation techniques are becoming established as standard methods for evaluating investment decisions that are subject to quantifiable uncertainty. This has been particularly the case in natural resources industries. In the UK oil industry there is renewed interest in oilfield valuation techniques - the 22nd UK Offshore Licensing Round was held in 2004 with a total of 97 licences offered to 58 companies in 2004, of which 15 were new entrants to the UK Continental Shelf.
Many firms involved in these bid processes now routinely use dynamic modelling and real option valuation to assess oilfield value premiums in differing operating and taxation enviroments.
Literature on PV and real option valuation is clear that models should accommodate tax effects but is unclear about its universal treatment in dynamic models. We examine the impact of the North Sea oil industry’s tax regime on the valuation of shelf real options by using a sample of forty oil fields that for the period 1970 to 2001 had initial estimated reserves greater than 75 million barrels of oil. Our sample uses Wood Mackenzie primary source field data updated quarterly by analysts using bottom up field research.
Our findings are that the tax enviroment of itself will cause asymmetrical movements in both free cash flow models and option values. These results are of interest to both academics and practitioners in that that tax plays an important role in the valuation process of real options in the oil and gas sector. Our results show that North Sea valuation models that treat taxation as a deterministic function systematically overstate DCF valuation results, understate volatility estimates and undervalue real options. Specifically our analysis suggests that failure to incorporate the variable nature of tax into the valuation process leads to an 18 percent over valuation of asset PV and an under valuation of the option price by 19.5 percent.
The increased usage of real option techniques in assessing oil field bids highlights the need for valuation models to incorporate the country specific nature of tax terms. This is especially important for oil fields in the North Sea where field exploration block bidding interest remains high and the legacy of tax changes is long; demanding from financiers a new way of assessing bid values in the face of future cash flow uncertainty.
Drawing from ideas of collusion in option games model with Cournot competition and price competition in a differentiated duopoly, we model, in a binomial framework, the latent collusion opportunity open to a first-follower. The first-follower is faced with investment decision in production capacity under market uncertainty as well as competitive uncertainty. The first-follower has an opportunity to collude with the incumbent in the Bertrand pricing game which will ensue with the first-follower’s entry; on the basis of a non-binding agreement. The investment decision is faced by only one firm – the first follower; unlike other papers where both firms are faced with the same decision albeit with asymmetry in information or cost structure. Focus on collusion in Bertrand game in a differentiated duopoly leads to the insight that for a given degree of collusion (the extent by which Nash Equilibrium payoffs are improved for each of the players), there are two price pairs; which we call the high price point and the low price point. The capacity required to follow the high price point strategy is even lesser than that required to play the low price point strategy. The strategy to go in for low capacity in the initial period and scale up subsequently if need be has costs – variable costs are lower at higher capacity levels, scaling up requires installing appropriate technology and there is a possibility of the first-follower’s capacity constraint becoming binding. We find that under different market demand volatility, elasticity and high/ low price point scenarios, the value of the option to revert to the competitive strategy (the option to scale up capacity) is significant. This insight can aid capacity creation decision of first-follower firms. Existence of low and high price points for collusion follows from an interesting Quartic equation in the price of either of the players.
This paper examines how capital controls affect FDI decisions and how the impact of these restrictive measures varies with different levels of country risk.
We construct a model of firms' FDI decisions, broadly in Dunning's "eclectic theory" framework, using "real options" to emphasize economic uncertainty and country risk. Numerical results of the model take the form of \\\"quality statistics\\\" that uncover the underlying dynamics hidden in the aggregate data that is responsible for the low performance of recent empirical studies.
We find that increasing levels of capital controls reduce the life-span of FDI investments at each level of country risk and foreign investors’ willingness towards risk sharing increases. We reveal a significant interaction between capital control and country risk, resulting in a nonlinear relationship between these and the volatility and volume statistics. We estimate a standard cross-sectional model that provides strong support for our theoretical findings.
II. Valuation Issues
Chairperson: V. Henderson, Princeton U.
The aim of this research work is to explore and apply real options theory and modern capital budgeting techniques to the problem of firm and stock valuation under uncertainty. For that purpose this work applies a simulation approach similar to that proposed by Schwartz and Moon (2001) to the problem of valuing a technology-based dividend-paying company - Portugal Telecom. To get to the firm’s per share value this paper incorporates in the model features aimed at pricing non-stock equity claims, whose value is subtracted from the value of equity. To deal with the problem of valuing convertible securities with early exercise features, like Portugal Telecom convertible bonds, this paper applies the promising Least Squares Monte Carlo method proposed by Longstaff and Schwartz (2001). Results in the literature seem to suggest Monte Carlo simulation as particularly handy at coping with path dependencies, multiple uncertainties and firm-specific complexities and, therefore, a numerical technique especially suited for real options, being used in this paper to solve the discrete time approximation version of the stochastic model.
Moreover, this research introduces in the valuation framework the possibility of dividend distribution, which fits what has been current practice in Portugal Telecom policy. The introduction of dividends in the present work setting brings about challenging implications, not only to the firm valuation process itself but also, and with greater acumen, to the process of pricing American-type contingent claims on discrete dividend-paying underlying assets. Finally, the valuation model is subject to an adequate sensitivity analysis and reveals itself as highly sensitive to starting conditions and precise input parameters, most of which could be estimated from quarterly financial data and analysts projections available at the time of valuation.
Key Words: Real-Options, Capital-Budgeting, Stock Valuation, Least-Squares Monte Carlo, Option Pricing, American Options.
JEL Classification: C15, C63, G12, G13, G31.
We develop a pricing method and derive an optimal equity financing strategy for a unlevered firm with constant production cost, constant production rate, stochastic output price and an option to expand in a non-competitive economy. The effects of taxes, transaction costs and non-liquidity on the share values and the optimal equity financing policy is studied. Shares of common stock in the firm are treated as contingent claims on two underlying instruments: the firm\\\'s retained earnings and the stochastic output price. The paper presents a numerical procedure for computing both the share value and the marginal rate of substitution of retained earnings (MRSRI). It is shown that in the absence of taxes and transaction costs, the MRSRI for a perfectly liquid firm is reduced to the constant a — this is a restatement of the classical Modigliani-Miller proposition in the context of dynamic programming. The study of the MRSRI in an economy with frictions may be viewed as an extension of the Modigliani-Miller theory.
As shown in Williams (1993), the supply of options on real or financial assets can be limited and developers can be less than perfectly competitive. This analysis can be examined in the context of a Merton’s (1987) simple model of capital market equilibrium with incomplete information. For this purpose, we introduce a model in the spirit of Bellalah (1999) and Bellalah (2002). As a by-product of this analysis, we extend also Williams’s result by introducing a quite general exogeneous factor. In this framework, it is possible to account for some specific features of real options and to derive the values of developed and undeveloped assets within incomplete information. Some comparative statistics are proposed to examine the influence of information costs.
“Is there any point to which you would wish to draw my attention?” “To the curious incident of the investment in the market.” “The agent did nothing in the market.” “That was the curious incident.” (with apologies to Sir Arthur Conan-Doyle.)
In this paper we study an optimal timing problem for the sale of a non-traded real asset. We solve this problem for a utility maximizing, risk averse manager under two scenarios: firstly when the manager has access to no other investment opportunities, and secondly when they may also invest in a continuously traded financial asset. We construct the model such that the financial asset is uncorrelated with the real asset, so that it cannot be used for hedging the real asset, and such that the financial asset has zero risk premium. In the absence of the real asset, the manager would not include the financial asset in her optimal portfolio.
Although the problem is designed such that naive intuition would imply that the optimal strategy and value functions are the same irrespective of whether the manager is allowed to invest in the financial asset, we find that curiously, for certain parameter values this is not the case. Our work has implications for modeling of portfolio choice problems since seemingly extraneous assets can impact on optimal behavior.
Keywords and Phrases: Real assets, Perpetual options, Optimal stopping, Incomplete markets, Portfolio
choice, Real options, Portfolio constraints
Friday 12:00 – 1:30
Luncheon Keynote Address by Robert S. Pindyck, MIT Real Options in Antitrust
Friday 1:30 – 3:10
I. Public Policy Options
Chairperson: J. Alleman, U. Colorado and Columbia U.
The introduction of uncertainty can make a significant difference in the valuation of a project. In a regulatory envirormwent, this manifests itself, inter alia, in situations where regulatory constraints can affect the valuations of a firm’s investment which, in turn, has an adverse impact on consumers’ welfare. In particular, the inability of a regulated firm to exercise any or all of the delay, abandon, start/stop, and time-to-build options has an economic and social cost. With this view in mind, we specify and estimate a model where regulatory delay constraints impact the firm’s cash flow and its investment valuation with real options methods.
This paper uses real options analysis to address issues of regulation that have not been adequately quantified. We show that regulatory constraints on cash flow have an impact on investment valuations. Specifically, a model is developed to estimate the cost of regulation by constraining the delay option. We show that the cash flow constraints and the inability to delay has a significant cost. Because some costs are not recognized in a static view of the world, this failure to recognize the operation and implications of nonflexibility by regulators (which can be modelled by real options methods) will lead to a reduction in company valuations which in turn will lead to a reduction in economics welfare.
The impact of regulation changes the variance used in the real options model. For example, the price cap or discounted access charges or other regulatory devices dampen the possibility of a high return contract, thus affecting the variance of returns. We model the regulatory constraint by constraining variance, σ2, in the option model. As intuition would suggest, as the constraint becomes tighter, the probability that the deferred option will pay-off is diminished.
Keywords: Real Options, Decision, Investment, Economic Methodology; Statistical Decision Theory, Criteria for Decision-Making under Risk and Uncertainty, Regulatory Distortions
JEL Classification: B41, C44, D81, G13
The recent applications of real options theory in environmental policy issues have illustrated the importance of explicitly modeling uncertainty and irreversibility in this type of problems. Within this framework, this paper explores the optimal timing of environmental policies when either the stock of pollutant or future economic costs caused by climate changes, are subject to normal as well as irregular changes. We assume that the stochastic evolution of these state variables is well described by a jump diffusion process and we examine alterations in optimal policies induced by the presence of discontinuities.
This paper examines the eﬀect of open access policy on competition in network industries under uncertainty. Comparing a competition under an open access policy with a facility-based competition, we confirm that allowing access to an essential facility makes the timing of a follower’s entry earlier than that in a facility-based competition, irrespective of the level of access charge. Furthermore, a leader’s (i.e., an incumbent’s) incentive for network investment under open access policy can be larger than without open access, depending on the relative magnitude between the level of access charge and positive network externality generated by an additional network facility.
Keywords: Real options, Open access policy, Facility-based competition.
When choosing among employment options, employees must consider the impact of their choice on total compensation: current and future salary earnings and retirement plan benefits. Employers offering retirement plans must decide whether to offer the employee the ability to participate in an employer sponsored defined contribution (DC) or defined benefit (DB) plan, or in some cases, both. The employer's decision on type of plan(s) and plan design will affect not only the salary needed to attract an employee, but also the expected tenure of the employee. In turn, employee tenure affects the level of employer hiring costs incurred to replace employees as they exercise of their option to switch employers. To address these interrelated issues, we solve the problems of optimal employee and employer plan choice in two stages. First, using a real options framework, we construct a dynamic programming model that determines the expected present value of the employee's lifetime earnings and plan benefits under varied current and competitive employer plan offerings. To take into account the employee's option to switch employers in the future, we use correlated diffusion processes to model the employee's current salary and an alternative employer's salary that can be earned by the employee exercising their option to switch. The optimal exercise of the employment switching option is affected by salary, retirement plan and years of service and is endogenously determined within the model. In the second stage modeling, we use the endogenous employee switch boundary determined from the first stage in a simulation to determine the employer's expected salary, benefit and hiring costs under either a DB or DC plan with varied plan design characteristics and competitive employer plan offerings. In our model, employers with DB plans have to offer employees higher salaries to compensate them for decreased value of the switching option. This higher compensation value tends to dominate the hiring cost savings that DB plans afford by helping retain employees. Numerical comparative statics are completed to show how retirement plan type, plan design, and employee characteristics affect the optimal plan choice by both employees and employers. In the majority of circumstances, DC plans are superior for both the employer and the employee which is consistent with the increased preference and prevalence of DC plans observed in practice.
II. New Product Development
Chairperson: D. Paxson, Manchester Business School, U
Investment decisions in new aircraft development programs are difficult because of large capital expenditures, long lead times, and many technical and market uncertainties. A flexible strategy that takes advantage of the ability of managers to incorporate information as uncertainties are resolved is suggested as a means to manage risk. In this paper, the use of real options analysis to evaluate and guide new aircraft development programs is illustrated through a case study of a real-world aircraft program. The analysis provides clear evidence that investors can use the numerical results of the real options analysis to determine how much they should spend on an aircraft program, that managers can use the same results to restructure the program to improve the financial feasibility of the project, and that both investors and managers can use the output of derivative analyses to define minimum requirements (in terms of aircraft orders) to ensure program success.
The analysis is based on a generalized real options methodology in which the underlying asset and the strike price may be described by any probability distribution. Thus, there is no need to approximate the distribution of the stock price or assume that exercise costs are fixed.
We introduce a general framework to value pilot project investments under the presence of both, market and technical uncertainty. The model generalizes different settings introduced previously in the literature. By distinguishing between the pilot and the commercial stages of the project we are able to frame the problem as a compound perpetual Bermudan option. We work on an incomplete market setting where market uncertainty is spanned by tradable assets and technical uncertainty is idiosyncratic to the firm. The value of these investment opportunities as well as the optimal exercise problem are solved by approximate dynamic programming techniques. We prove the convergence of our algorithm and derive a theoretical bound on how the errors compound as the number of stages of the compound option is increased. Furthermore, we show some numerical results and provide an economic interpretation of the model dynamics.
Clinical R&D is a highly uncertain venture where experiments achieve successful outcomes on an extraordinarily rare basis. Just one successful product could change the future of a company; the stage to discovery can often be an invaluable or disastrous experience. Developers should balance probability analysis against the potential profits that may result. With that objective, we propose extreme-value theory (EVT) as an extension to the standard perpetual American call option.
We develop an R&D option model when discoveries follow extreme-value distributions. We examine the optimal trigger that justifies an investment, the effect of frequency in discoveries on real option values, the roles of tail-shape parameters of discovery distributions, and compare values to invest with models governed by other distributions. We find that effective premiums for options based on extreme-distributions should be lower (and triggers for optimal investment higher) than those governed by normally distributed underlying values, with otherwise similar parameters. The sensitivities of option values and triggers to changes in the shape parameter of the extreme distributions are simulated, and show interesting, perhaps counter-intuitive results.
Keywords: R&D, real options, extreme value theory, probability density functions.
We study a novel issue in the real-options-based technology innovation literature by means of double barrier contingent claims analysis. We show how much a firm with the monopoly over a project is willing to spend in investment technology innovation that softens the irreversible cost of accessing the project before its irreversible demise. The answer depends on the project's characteristics and on the e®ectiveness demanded from technology innovation.
The objective of this paper is to explore the potential of the real options approach for analyzing farmers’ choice to switch from conventional to organic farming. Understanding the determinants of this decision is relevant in particular for agricultural policy makers when predicting the response of farmers to supporting programs. An econometric model is applied to aggregated data of conventional and organic farms in Germany and Austria. The empirical analysis confirms the reluctance to adopt organic farming due to option-like effects. We conclude that the incentives for an adoption of organic farming have to be increased if a higher share of this production type is desired.
Key words: organic farming, real options, switching regression, hysteresis
Animal epidemics can bring severe damage to the livestock sector as well as the whole society. In controlling animal epidemic, the selection of suboptimal control strategies may lead to unnecessary costs which should be avoided. This paper argues that uncertainties about the state of the epidemic, irreversible actions like culling and vaccination of animals, and the possibility of learning during the epidemic requires control strategies to be flexible and the value of flexibility should be considered when evaluating control strategies. Based on Markov decision process (MDP) and dynamic programming, a decision support framework is developed to determine the optimal control strategy which accounts for uncertainties as well as flexibility in the dynamic decision making process. A numerical example illustrates our approach to quantify the value of flexibility.
Keywords: Value of °exibility; Decision-making under uncertainty; Control strategy; Contagious Animal Disease.
In this paper, we study the problem of investing in sustainable transport to relieve air pollution. In such a case, the growth of the city population is the major source of uncertainty, as a high population density increases pollution and, on the other hand, makes a big transportation project necessary. Using the real options\\\' method, we show how to maximize inter-generational utility when the population grows stochastically. We obtain explicit closed form expression for the threshold on population above which it is optimal to invest. Our numerical results show that we must wait a longer time before investing when the uncertainty is high, and that our approach allows us to invest in some cases where classical approaches does not.
Most investors and real estate developers consider brownfield redevelopment projects risky and, to compensate for the additional environmental risk, demand higher returns on the investment needed to cleanup and redevelop a contaminated property. The perception of risk is aggravated by the fact that, depending upon the remediation technique adopted, remediation of a contaminated site takes time during which, the real estate market conditions may change significantly.
To estimate the value of brownfields considering the environmental and market risks associated with property clean up and redevelopment, both technical and market risks are integrated. A closed-form solution derived for a perpetual American call option was modified to calculate the optimal sequential investment that accounts for the required time to undertake the investment (i.e., implement the proposed remediation for a contaminated land). The proposed solution can be used to evaluate the value of a brownfield if the owner/developer has the option to delay remediation indefinitely waiting for optimal conditions to start. The results of the proposed approximation are compared to the results obtained using numerical techniques to solve partial differential equations.
II. Innovation and Learning
Chairperson: J. Sadowsky, Stanford U.
In this paper we use a real options approach to value pilot project investments that help reduce idiosyncratic uncertainty with respect to the final costs of a project. We develop a general one period investment model and, using standard financial engineering techniques, are able to find the value of these investment opportunities and the corresponding optimal investment level. In our setting, both tradable market uncertainty and idiosyncratic technical uncertainty affect the value of the project, with the latter being driven by the amount invested in the pilot stage. Learning is modeled using a proportionality assumption between investment in the development stage and resolution of technical uncertainty.
The coefficient that governs this proportionality relation will play a key role in our model, as it defines whether there are decreasing or increasing marginal returns to investment in the development stage and to what extent. Interesting economic implications concerning the effects of this learning coefficient and other parameters of interest in the optimal investment decision are obtained. The robustness of our results is also analyzed. Finally, applications of our framework to investment decisions in various industries and across the supply chain of firms are discussed.
This paper considers the optimal entry strategy in a new product market. Some firms enter new markets by committing the sunk cost up-front and immediately investing at full scale. Other companies start out more cautiously by undertaking market research first (e.g. by launching a pilot project). In the latter case, the idea is to gain information on the demand of consumers for this product. One of the indirect costs of such a strategy is that it can disclose the true demand curve to the firm\\\'s competitor(s). We investigate the value of conducting the market research for different levels of uncertainty and of the sunk cost that has to be incurred to enter the new market. We show that the value of market research is non-monotonic in the level of the sunk cost and the shape of this relationship critically depends on the level of market uncertainty. Furthermore, we show that due to strategic interaction, higher uncertainty does not necessarily increase the firm\\\'s willingness to carry out the market study.
This paper studies financial properties of venture-capital backed start-ups through a continuous-time real-options patent-race model. Numerical analysis shows that patent races, relative to a joint monopoly, cause over-investment, value-dissipation, a higher CAPM beta, a higher return volatility and more negative return correlation when firms intensively compete. A firm’s CAPM beta is a complicated non-linear function of its position relative to its competitor. The magnitude of annualized return volatilities of start-ups can be in excess of 100%. This high level of return volatility is mainly attributed to technological risks and is consistent with empirical findings by Cochrane .
This paper proposes a theory for technical uncertainty with main focus on learning real options and real option games applications. It discusses information revelation as processes of reduction of uncertainty and proposes the expected percentage of variance reduction as learning metric to simplify the complex analysis of investment decisions under uncertainty in which the technical uncertainty about a real asset is relevant. This learning measure has a direct link with the distribution of conditional expectations of a variable of interest, where the conditioning is the set of new information that can be revealed by a cost (learning option) or by waiting as free rider (option game application). In addition, it is shown that this learning measure has many favorable mathematical and practical properties. A set of axioms for (probabilistic) learning measures is presented. This paper also analyzes with some detail the simplest revelation process, namely the sequential bivariate Bernoulli process, including the analysis of Fréchet-Hoeffding limits and interchangeable bivariate Bernoulli process. Examples in exploration of petroleum and in portfolio of real assets, illustrate this methodology.
Keywords: value of information, real options, learning measures, information revelation processes, exploratory process, bivariate Bernoulli process, correlation ratio, investment under uncertainty.
DAY 3 – SATURDAY, JUNE 25
Saturday 8:30 – 10:10
I. Methodology/Computational Issues
Chairperson: G. Cortazar, Catholic U. of Chile
We examine the influence of market uncertainty on incremental capacity investment in a symmetric oligopoly. In order to capture the case of negative profits we assume an arithmetic Brownian motion representation of uncertainty. In a such set-up we derive a closed-form solution for the equilibrium in myopic strategies in a strategic real-option game based on Grenadier (2002, Review of Financial Studies). Surprisingly, we found that uncertainty does not influence a welfare, yielding the same equilibrium value of unity of investment as in the base-case model. Also the option premium turns out to be not only independent on uncertainty but also on uncertainty process being arithmetic Brownian motion or geometric Brownian motion. Analogous to the geometric Brownian motion case, increasing competition results in investments undertaken at a threshold very near to the simple net present value threshold. Despite this similarity, we prove that possible occurrence of negative profits makes investment significantly less attractive relative to the case with the same value of uncertainty and nonnegative profits.
In this paper we show how a multidimensional American real option may be solved using a computer-based simulation procedure. We implement an approach originally proposed for a financial option and show how it can be used in a much more complex setting. We extend a well-known natural resource real option model, originally solved using finite difference methods, to include a more realistic 3 factor stochastic process for commodity prices, more in line with current research. We show how complexity may be reduced by adequately choosing the implementation variables. Numerical results show that the procedure may be successfully used for multidimensional models, notably expanding the applicability of the real options approach.
One of the central tasks of Finance Theory is achieving the value of both financial and real assets. In general, these problems are approached through continuous time. In this context, the analysis and definition of stochastic processes are central. One of the most important is commodity prices process, usually employed for pricing futures contracts and valuation of projects. In general, commodities are traded in futures markets and spot prices can not be observed. These are estimated on the basis of futures prices. The literature on the topic employs the Kalman filter as a methodology to this end. Kalman filter requires linearity and Gaussian conditions. This is limiting because many financial models do not have these properties. The present article uses the particle filter, which does not require the conditions above. We analyse the filtering process of both methodologies. We use Schwartz and Smith (2000) two factor model to carry on the analysis. Excellent results have been obtained.
The American option evaluation is a relatively complex and expensive process due to commonly used methodologies as Finite Differences, Dynamic Programming, Monte Carlo Simulation, etc. needs high computational performance. Besides that, the complexity needed to calculate the option value and the optimal threshold increases when the price of underlying asset follows the Mean Reversion Stochastic Process. By this way, is interesting to achieve an analytical approximation in order to make easier to obtain the optimal threshold and the option value.
There are many analytical approximations mentioned in bibliography respecting to American Options about asset prices following a Geometric Brownian Motion  , but none about it follows Mean Reversion Processes.
This work proposes a model based on Symbolic Regression by Genetic Programming to obtain an analytical approximation for the optimal threshold respecting to an American option which its asset follows a Mean Reversion Process.
The Optimal Threshold that separates during the option life-cycle the decision to exercise the option, is later employed to evaluate the option. The result achieved by the proposed model (Threshold Analytical Function) seemed to be satisfactory.
II. Financing/Agency Issues
Chairperson: G. Sick, U. Calgary, Canada
This paper presents a theory of capital investment and debt and equity financing in a real-options model of a public corporation. The model assumes that managersmaximize the present value of their future compensation (managerial rents), subject to constraints imposed by outside shareholders' property rights to the firm's assets. We derive an optimal debt policy that generates e±cient investment and disinvestment decisions by managers. The optimal policy sets debt at the liquidation value of the firm's assets; optimal debt is therefore default-risk free. The optimal policy may not be followed if managers are wealth-constrained, however. Wealth constraints can justify additional risky debt if necessary to fund positive-NPV investments. Changes in cash flow can cause changes in investment by tightening or loosening the constraints.
In this paper, we explore the impact of debt financing on the timing of an irreversible investment and the value of waiting to invest. As a benchmark, we consider the case where the market for loans is perfectly competitive. Alternatively, a small firm has limited access to financial markets and must bargain with its bank to get financing. The debt contract is a Consol and as soon as the firm cannot meet the required coupon payment, liquidation takes place. In the competitive case, when default occurs, the higher the debt level, the higher the coupon, the lower the investment trigger which dampens the option value. Under imperfect competition, the higher the bargaining power of the lender, the higher the coupon charged, the higher the investment trigger but the lower the value of waiting to invest.
This article develops a contingent-claims model in which both the volatility and the return of the firm cash-flows are altered by the equityholders decisions. Our results contrast with those previously based on a reduction of the asset substitution problem to a pure risk-shifting problem. We find larger agency costs and lower optimal leverages. Moreover we show that covenants that restrict equityholders from adopting a project with high volatility and low return are not necessarily value enhancing. Our model highlights the tradeoff between ex-post inefficient behaviour of equityholders and inefficient covenant restrictions.
Keywords: Asset substitution, capital structure, covenants, agency costs.
The availability of consumption insurance may alter an agent’s risk appetite. This paper examines bankruptcy exemptions which allow agents with extremely adverse income realizations a consumption floor at the level of the exemption. In particular, a real options model is constructed to examine whether the improved insurance inherent in higher bankruptcy exemptions induces agents to increase the share of risky assets within their financial portfolios. The evidence from US micro level data indicates that exemptions induce agents to weight their portfolios more in favor of risky assets. Moreover, the results are consistent with the conjecture that specific exemption changes will affect the risky asset weighting of agents with asset levels closer to the exemption level more than those of agents with more remote asset levels.
Saturday 10:45 – 12.25
I. Theoretical Issues
Chairperson: C. Carlsson, IAMSR/Åbo Akademi U., Finland
The real options literature has provided new insights on how to manage irreversible capital investments whose payoffs are always uncertain. Two of the most important predictions from such theory are: (i) greater risk delays a firm’s investment timing, and (ii) greater risk increases the option value of waiting. This paper challenges such conclusions in a setting in which the relevant random variable is the arrival time of an unfavorable event. In addition, we avoid using stochastic calculus by introducing a novel framework in which a firm updates its beliefs about the profitability of an investment opportunity by waiting to invest.
Key words: Investment under Uncertainty, Option Value, Entry Timing, Bad News Principle, Hazard Rate and Bayesian Updating.
Most Real Options authors have been assuming that the only critical variable in the investment decision analysis is price. The success of an investment depends not only on the price of a product but also on other variables like the quantity of production. The number of units sold is a variable with different characteristics than price. It can be in some applications a discrete variable, and its drift and volatility can be affected by different factors.
We present a model in which a monopoly investor has the option to invest in a new market, in which the number of units sold follows a stochastic birth and death process. We present a numerical solution for the value of the option to invest and for the trigger level for investment. Also we study the sensitivity of the option value to changes in the number of units sold and also the sensitivity of the trigger level to changes in volatility. The model suggests, that the classical assumption of Geometric Brownian motion, as the stochastic process of the underlying variable can overestimate the option value to invest.
Most decision making research in real options focuses on revenue uncertainty assuming discount rates remain constant. However for many decisions, revenue or cost streams are relatively static and investment is driven by interest rate uncertainty, for example the decision to invest in durable machinery and equipment. Using interest rate models from Cox et al. (1985b), we generalize the work of Ingersoll and Ross (1992) in two ways. Firstly we include real options on perpetuities (in addition to "zero coupon" cash flows). Secondly we incorporate abandonment or disinvestment as well as investment options and thus model interest rate hysteresis (parallel to revenue uncertainty, Dixit (1989a)). Under stochastic interest rates, economic hysteresis is found to be significant, even for small sunk costs.
Key Words: real options, interest rate uncertainty, perpetuities, investment hysteresis.
Giga-investments are very large projects with long life cycles, which make them both risk investments and decision problems built on imprecise and uncertain assumptions. They nicely fulfil the classic in-sight, which motivates the use of fuzzy set theory: there is a trade-off between precision and relevance. That is, if we increase precision we will start losing relevance at some point, and if we increase rele-vance we will have to give up on precision at some point. We used this insight as a basis and motiva-tion to introduce the fuzzy real option valuations (FROV) as a remedy for coping with the undue preci-sion introduced with the NPV methods. The key issue is that future uncertainty cannot be dealt with as a stochastic phenomenon when we work with decisions on giga-investments. Possibility theory is an alternative way to handle future uncertainty where we do not have to rely on historical time series or try to make estimates from variation patterns.
The reality of national sovereignty makes sovereign credit risk a function of the government’s “willingness to pay”. The current structural and reduced form models of credit risk are based on the principle of the ability to pay and, therefore, do not capture the effects of the “willingness to pay”. In this paper we model the “willingness to pay” as an American style call option and show how it can be implemented to estimate default probabilities and the distance to default.
This paper examines the valuation and exercise incentives for real options under various exogenously given debt policies that the firm may have, when interest tax shields have positive or negative value. We focus on debt policies that are linear in the value of the firm. These policies include the fixed debt policy that underlies the APV models of Myers and the proportional debt policies that underly WACC models and the Miles-Ezzell model. The american investment option value is approximated as a difference from the european investment option by an extension of the quadratic approximation first used by MacMillan and made popular by Barone-Adesi and Whaley.
We examine these in the contexts of default-free debt and debt that defaults at an exogenous (non-strategic) hurdle.
We review and extend recent contingent claims models of capital structure. We focus on two models with analytic formulas in perpetual horizon- Leland (1994) and Mauer and Sarkar (2004). We implement the investment option in both models in finite horizon with a numerical lattice while maintaining the analytic structure for the capital structure decisions in the second stage by maintaining the perpetual horizon for debt. Incorporation of the investment option itself essentially extends and generalizes Leland’s model. Using this framework we investigate two issues: the effect of capital financing constraints on both debt and new equity and the effect of managerial (equity-financed) options to enhance the value of the firm by R&D, advertising or marketing research efforts before the major investment decision takes place. In this general framework we are able to analyze when equity holders should invest to improve the investment option (control option), simply delay for more uncertainty resolution or invest early in a project that can be both equity and debt financed and may face constraints in the level of financing. Financing constraints may arise due to asymmetric information or moral hazard, affecting both optimal first stage control decisions and optimal financing, and in turn, the values of equity and debt.
This paper estimates costs of external finance, applying indirect inference to a dynamic structural model where the corporation endogenously chooses investment, distributions, leverage and default. The corporation faces double taxation, costly state verification in debt markets, and linear-quadratic costs of external equity. Consistent with direct evidence on underwriter fee schedules, behavior is best explained by rising marginal costs of external equity, starting at 3.9%. Contrary to the notion that corporations are debt conservative, leverage is consistent with small (12.2%) bankruptcy costs. Investment-cash flow sensitivities are not a sufficient statistic for financing costs. The cash flow coefficient decreases in external equity costs and increases in bankruptcy costs. When the model is simulated using our parameter estimates, the cash flow coeffient across Fazzari, Hubbard, and Petersen’s dividend classes is U-shaped. The diﬀerence between cash flow coeﬃcients across dividend classes actually decreases as costs are increased.
Saturday 12:30 – 1:30
Panel Discussion: Current State, Challenges and Future Prospects
Moderator: Gordon Sick, U. Calgary
Mondher Bellalah, AMFAM, U. Cergy and EDC, France Marcel Boyer, U. Montréal, Canada Ephraim Clark, Middlesex U., UK John Kensinger, U. North Texas Bart Lambrecht, Lancaster U., UK Ted O’Leary, U. Manchester, UK, and U. Michigan Robert S. Pindyck, MIT Lenos Trigeorgis, U. Cyprus and ROG
Closing Remarks (L. Trigeorgis, ROG, and C. Bouy, EDC)