Optimal investment under operational flexibility, risk aversion, and uncertainty

Traditional real options analysis addresses the problem of investment under uncertainty assuming a risk-neutral decision maker and complete markets. In reality, however, decision makers are often risk averse and markets are incomplete. We confirm that risk aversion lowers the probability of investment and demonstrate how this effect can be mitigated by incorporating operational flexibility in the form of embedded suspension and resumption options. Although such options facilitate investment, we find that the likelihood of investing is still lower compared to the risk-neutral case. Risk aversion also increases the likelihood that the project will be abandoned, although this effect is less pronounced. Finally, we illustrate the impact of risk aversion on the optimal suspension and resumption thresholds and the interaction among risk aversion, volatility, and optimal decision thresholds under complete operational flexibility.     

Duopolistic competition under risk aversion and uncertainty

A monopolist typically defers entry into an industry as both price uncertainty and the level of risk aversion increase. By contrast, the presence of a rival typically hastens entry under risk neutrality. Here, we examine these two opposing effects in a duopoly setting. We demonstrate that the value of a firm and its entry decision behave differently with risk aversion and uncertainty depending on the type of competition. Interestingly, if the leader’s role is defined endogenously, then higher uncertainty makes her relatively better off, whereas with the roles exogenously defined, the impact of uncertainty is ambiguous.     

Project options valuation with net present value and decision tree analysis

Real options analysis (ROA) has been developed to correctly value projects with inherent flexibility, including the possibility to abandon, defer, expand, contract or switch to a different project. ROA allows computing the correct discount rate using the replicating portfolio technique or risk-neutral probability method. We propose an alternative approach for valuing Real Options based on the certainty-equivalent version of the net present value formula, which eliminates the need to identify market-priced twin securities. In addition, our approach can be extended to the case of multinomial trees, a useful tool for modeling uncertainty in projects. We introduce within decision tree analysis (DTA) a method to derive the different discount rates that prevail at different chance nodes. We illustrate the valuation method with an application presented in “A Scenario Approach to Capacity Planning” [Eppen, G.D., Martin, R.K., Schrage, L.E., 1989. A scenario approach to capacity planning. Operations Research, 37 (4)], in which the authors state that for the capacity configuration investment decision studied at General Motors, “… there is no scientific way to determine the appropriate discount rate based on estimated demand.” Our method allows deriving the scientifically correct discount rates. A major result of the analysis is that the discount rates are endogenously derived from the project structure and its behavior in light of prevailing market conditions, instead of being exogenously imposed.     

Return distributions of strategic growth options

In this study, we develop implications of imperfect competition on the return distribution of strategic growth options. We integrate real option theory with a Cournot-Nash framework in which two firms choose output levels endogenously and may have investment-timing differences. Simulations show that traditional option variables are significant determinants for the moments of the return distribution. In addition, uncertain preemption may introduce discontinuities in the payoff of the option that increase skewness and kurtosis. When first-mover advantages are crucial and sustainable, investment-timing differences between competitors can result in bimodal return distributions, where the firm with the first-mover advantage has a high probability of generating high returns. The authors are greatly indebted to the editor, the seminar participants of the Real Option Conference 2003 and the anonymous reviewers for their insightful comments and guidance. All remaining errors are our own.     

Strategic investment under uncertainty: A synthesis

Investment is a central theme in economics, finance, and operational research. Traditionally, the focus of analysis has been either on assessing the value of flexibility (investment under uncertainty) or on describing commitment effects in competitive settings (industrial organization). Research contributions addressing the intersection of investment under uncertainty and industrial organization have become numerous in recent years. In this paper, we provide an overview aimed at categorizing and relating these research streams. We highlight managerial insights concerning the nature of competitive advantage (first- versus second-mover advantage), the manner in which information is revealed, firm heterogeneity, capital increment size, and the number of competing firms.     

The impacts of uncertainties in a real options model under incomplete information

This paper examines the impact with respect to the uncertainty of the underlying state variable, profit uncertainty, on the real options model in a situation of incomplete information. Profit uncertainty has not incorporated into the real options model under incomplete information, in that the underlying state variable is not formulated as the stochastic process (see, e.g., Bernardo, A. E., Chowdhry, E. B., 2002. Resources, real options, and corporate strategy. Journal of Financial Economics, 63, 211–234). We extend the model developed by Bernardo and Chowdhry to formulate the underlying state variable as the stochastic process. We conclude that profit uncertainty has the same type of impact on the real options value and its triggers, both under complete and incomplete information.     

Technology choice under several uncertainty sources

We analyze a model of irreversible investment with two sources of uncertainty. A risk-neutral decision maker has the choice between two mutually exclusive projects under input price and output price uncertainty. We propose a complete study of the shape of the rational investment region and we prove that it is never optimal to invest when the alternative investments generate the same payoff independently of its size. A key feature of this bidimensional degree of uncertainty is thus that the payoff generated by each project is not a sufficient statistic to make a rational investment. In this context, our analysis provides a new motive for waiting to invest: the benefits associated with the dominance of one project over the other. As an illustration, we apply our methodology to power generation under uncertainty.     

Optimal exercise of jointly held real options: A Nash bargaining approach with value diversion

This paper provides a two-stage decision framework in which two or more parties exercise a jointly held real option. We show that a single party’s timing decision is always socially efficient if it precedes bargaining on the terms of sharing. However, if the sharing rule is agreed before the exercise timing decision is made, then socially optimal timing is attained only if there is a cash payment element in the division of surplus. If the party that chooses the exercise timing can divert value from the project, then the first-best outcome may not be possible at all and the second-best outcome may be implemented using a contract that is generally not optimal in the former cases. Our framework contributes to the understanding of a range of empirical regularities in corporate and entrepreneurial finance.     

Arithmetic Brownian motion and real options

We treat real option value when the underlying process is arithmetic Brownian motion (ABM). In contrast to the more common assumption of geometric Brownian motion (GBM) and multiplicative diffusion, with ABM the underlying project value is expressed as an additive process. Its variance remains constant over time rather than rising or falling along with the project’s value, even admitting the possibility of negative values. This is a more compelling paradigm for projects that are managed as a component of overall firm value. After outlining the case for ABM, we derive analytical formulas for European calls and puts on dividend-paying assets as well as a numerical algorithm for American-style and other more complex options based on ABM. We also provide examples of their use.     

The impact of investment lags on investment decision

This paper suggests a valuation framework for an investment project through the concept of real options. Generally, in real asset world, decision time and its payment time are not identical. This so-called investment lag problem should be considered when valuing real assets. When investment lags exist, firms’ accommodation capacities play important roles. In this paper, the real effect of investment lag on investment value is tested upon various conditions. We show the valuation process of real assets under the risk-neutral world. The closed-form formula is also provided for valuing real assets, including R&D project.     

Technology selection and capacity investment under uncertainty

We analyze the problem of technology selection and capacity investment for electricity generation in a competitive environment under uncertainty. Adopting a Nash-Cournot competition model, we consider the marginal cost as the uncertain parameter, although the results can be easily generalized to other sources of uncertainty such as a load curve. In the model, firms make three different decisions: (i) the portfolio of technologies, (ii) each technology’s capacity and (iii) the technology’s production level for every scenario. The decisions related to the portfolio and capacity are ex-ante and the production level is ex-post to the realization of uncertainty. We discuss open and closed-loop models, with the aim to understand the relationship between different technologies’ cost structures and the portfolio of generation technologies adopted by firms in equilibrium. For a competitive setting, to the best of our knowledge, this paper is the first not only to explicitly discuss the relation between costs and generation portfolio but also to allow firms to choose a portfolio of technologies. We show that portfolio diversification arises even with risk-neutral firms and technologies with different cost expectations. We also investigate conditions on the probability and cost under which different equilibria of the game arise.     

Investment and the dynamic cost of income uncertainty: The case of diminishing expectations in agriculture

This paper studies optimal investment and the dynamic cost of income uncertainty, applying a stochastic programming approach. The motivation is given by a case study in Finnish agriculture. The investment decision of a representative farm is modelled as a Markov decision process, extended to account for risk. A numerical framework for studying the dynamic uncertainty cost is presented, modifying the classical expected value of perfect information to a dynamic setting. The uncertainty cost depends on the volatility of income: e.g. with stationary income, the dynamic uncertainty cost corresponds to a dynamic option value of postponing investment. The model can be applied to agricultural policy planning. In the case study, the investment decision is sensitive to risk.     

Real options valuation of forest plantation investments in Brazil

In this paper, we consider investments in eucalyptus plantations in Brazil. For such projects, we discuss real options valuation in the place conventional methods such as IRR or NPV, possibly with CAPM. Traditionally, real options valuation assumes complete markets and neglects market imperfections. Yet, market frictions, such as transaction costs, interest rate spreads, and restricted short positions, can play an important role. We extend real options valuation to allow incomplete and imperfect markets. The value is obtained as a competitive price, given markets of competing investment opportunities, such as real and financial assets. Under perfect and complete markets, such valuation method is consistent with conventional real options theory. Stochastic programming and standard software is used for valuation of eucalyptus plantations. We estimate the underlying interdependent diffusion processes of stock market, interest rates, exchange rates and pulpwood price, and derive novel expressions of stochastic integrals to be employed in scenario generation for discrete time stochastic programming.     

Renewable energy investments under different support schemes: A real options approach

This paper adopts a real options approach to analyze investment timing and capacity choice for renewable energy projects under different support schemes. The main purpose is to examine investment behavior under the most extensively employed support schemes, namely, feed-in tariffs and renewable energy certificate trading. We consider both multiple sources of uncertainty under each support scheme and uncertainty with respect to any change of support scheme, and we obtain both analytical (when possible) and numerical solutions. In a Nordic case study based on wind power, we find that the feed-in tariff encourages earlier investment. Nevertheless, as investment has been undertaken, renewable energy certificate trading creates incentives for larger projects. In our baseline scenario and taking the fixed feed-in tariff as a base, the revenue required to trigger investments is 61% higher with renewable certificates. At the same time, investment capacity is 61% higher.     

Earnouts in mergers and acquisitions: A game-theoretic option pricing approach

This paper presents a valuation approach for merger and acquisition (M&A) deals employing contingent earnouts. It is argued that these transactions have option-like features, and the paper uses a game-theoretic option approach to model the value of such claims. More specifically, the paper examines the impact of uncertainty on the optimal timing of M&A using earnouts, and it also investigates the impact of uncertainty on the terms of the earnout. Optimal earnout and initial payment combinations are endogenously derived from the model, and testable hypotheses are developed. The theoretical contribution of this paper is a dynamic decision-making model of the invest-to-learn option generated upon investment in an acquisition. The paper also offers practical implications for the design of acquisitions employing earnouts.     

Flexible waste management under uncertainty

In this paper, we use stochastic dynamic programming to model the choice of a municipality which has to design an optimal waste management program under uncertainty about the price of recyclables in the secondary market. The municipality can, by undertaking an irreversible investment, adopt a flexible program which integrates the existing landfill strategy with recycling, keeping the option to switch back to landfilling, if profitable. We determine the optimal share of waste to be recycled and the optimal timing for the investment in such a flexible program. We find that adopting a flexible program rather than a non-flexible one, the municipality: (i) invests in recycling capacity under circumstances where it would not do so otherwise; (ii) invests earlier; and (iii) benefits from a higher expected net present value.     

Controlling for supplier switching in the presence of real options and asymmetric information

Applying a real option approach, this paper examines how asymmetric information alters key variables of a firm’s supplier switching process, such as the timing of contracting (hurried versus delayed contracting), transfer payments, set-up, switching, and abandonment decisions. In a symmetric information setting, delayed contracting is unambiguously beneficial. Abandoning the once established relation with the entrant supplier is never an issue. In contrast, under asymmetric information hurried contracting with potentially abandoning the relation can be beneficial. Consistent with adverse selection models, we find that under delayed contracting, in equilibrium, the firm switches less frequently to the entrant supplier (switching inertia). Surprisingly, we also find that under hurried contracting the firm switches more frequently to the entrant supplier (switching acceleration) and may abandon the relation. Finally, we study how these key variables of the supplier switching process change when also the incumbent supplier has private information (two-sided asymmetric information case).     

Fixed versus flexible production systems: A real options analysis

In this work, we address investment decisions in production systems by using real options. As is standard in literature, the stochastic variable is assumed to be normally distributed and then approximated by a binomial distribution, resulting in a binomial lattice. The methodology establishes a discrete-valued lattice of possible future values of the underlying stochastic variable (demand in our case) and then, computes the project value. We have developed and implemented stochastic dynamic programming models both for fixed and flexible capacity systems. In the former case, we consider three standard options: the option to postpone investment, the option to abandon investment, and the option to temporarily shut-down production. For the latter case, we introduce the option of corrective action, in terms of production capacity, that the management can take during the project by considering the existence of one of the following: (i) a capacity expansion option; (ii) a capacity contraction option; or (iii) an option considering both expansion and contraction. The full flexible capacity model, where both the contraction and expansion options exist, leads, as expected, to a better project predicted value and thus, investment policy. However, we have also found that the capacity strategy obtained from the flexible capacity model, when applied to specific demand data series, often does not lead to a better investment decision. This might seem surprising, at first, but it can be explained by the inaccuracy of the binomial model. The binomial model tends to undervalue future decreases in the stochastic variable (demand), while at the same time tending to overvalue an increase in future demand values.     

A real options approach to labour shifts planning under different service level targets

Firms that experience uncertainty in demand as well as challenging service levels face, among other things, the problem of managing employee shift numbers. Decisions regarding shift numbers often involve significant expansions or reductions in capacity, in response to changes in demand. In this paper, we quantify the impact of treating shifts in workforce expansion as investments, while considering required service level improvements. The decision to increase shifts, whether by employing temporary workers or hiring permanent employees, is one that involves significant risks. Traditional theories typically consider reversible investments, and thus do not capture the idiosyncrasies involved in shift management, in which costs are not fully reversible. In our study, by using real options theory, we quantify managers’ ability to consider this irreversibility, aiming to enable them to make shift decisions under conditions of uncertainty with the maximum level of flexibility. Our model aims to help managers make more accurate decisions with regard to shift expansion under service level targets, and to defer commitment until future uncertainties can be at least partially resolved. Overall, our investigation contributes to studies on the time required to introduce labour shift changes, while keeping the value of service level improvements in mind.     

Game options with gradual exercise and cancellation under proportional transaction costs

ABSTRACT

Game (Israeli) options in a multi-asset market model with proportional transaction costs are studied in the case when the buyer is allowed to exercise the option and the seller has the right to cancel the option gradually at a mixed (or randomized) stopping time, rather than instantly at an ordinary stopping time. Allowing gradual exercise and cancellation leads to increased flexibility in hedging, and hence tighter bounds on the option price as compared to the case of instantaneous exercise and cancellation. Algorithmic constructions for the bid and ask prices, and the associated superhedging strategies and optimal mixed stopping times for both exercise and cancellation are developed and illustrated. Probabilistic dual representations for bid and ask prices are also established.