A Real Options Model of Patent Litigation
Danmo Lin
University of Warwick
United Kingdom
Du Liu
East China Normal University
China
Elizabeth Whalley
University of Warwick
United Kingdom
We develop a real options model to examine the factors influencing potential outcomes of patent disputes from a corporate finance perspective. By investigating the dynamic strategic interactions between a patent-owning incumbent and an allegedly infringing challenger, we find that intense competition from the challenger's market entry, high product market volatility, and a larger disparity in the two firms' willingness to engage in litigation make settlement less likely. Under the English rule, where the loser pays, the challenger's relative willingness to engage in litigation increases compared to the American rule, where each party bears its own costs. This shift results in lower royalty rates in settlements. Our model offers insights into litigation and settlement rates, the effects of legal rules, and post-dispute market structures, highlighting how these outcomes are shaped by product market characteristics.
A Target Zone Model For Corporate Debt
Massimiliano Marzo
University of Bologna
Italy
Francesco Baldi
University of Bologna
Italy
We study the dynamic corporate structure by considering the role of commitment on firm's side. We show that if the firm can credibly commit to preserve the equity value up to a given threshold, it can afford higher level of debt than those associated to bankruptcy. Our model borrows from a well consolidated literature originated from Leland (1994, 1996), Goldstein,Ju and Leland (2001), Hackbarth, Miao, Morellec (2006), where we model a framework to analyze capital structure and credit risk in a continuous time setting. Our innovative point consists in mixing the existing framework with the Target Zone literature originated by Krugman (1991), Bertola and Caballero (1992), in the exchange rate dynamics context. We extend the traditional capital structure models to a log-normal setting. We identify the upper bound for the debt value associated to bankruptcy by adopting a different strategy based on the 'smooth pasting condition'. This new methodology allows to identify different levels of debt associated to bankruptcy, higher than the corresponding level identified in the current literature. The commitment to keep the bankruptcy value stable within a target zone, allows the firm to issue larger level of debt. If the company can successfully commit to preserve its value, the optimal level of debt can be higher.
Add-On Service Quality and Preemption With Non-Savvy Consumers
Keizo Mizuno
Kwansei Gakuin University
Japan
Kohei Daido
Kwansei Gakuin University
Japan
This paper examines the impact of the presence of non-savvy consumers on firms' entry incentives in durable goods markets. In the durable goods markets, firms provide vertically-differentiated add-on services to consumers. We firstly show that the price of a durable good with high quality add-on services is lower (resp. higher) than that with low quality add-on services when the proportion of non-savvy consumers in the population is high (resp. low). We then show that a firm that supplies a durable good with high quality add-on services enters earlier than that with low quality add-on services, irrespective of the proportion of non-savvy consumers. In addition, when the proportion of non-savvy consumers is high, each firm has a preemptive incentive such that the entry timing of a firm with high quality add-on services into the market becomes earlier than that when savvy consumers are prevalent.
Assessment of Risk Sharing Mechanisms In Ppp Concessions: An Application In Road Infrastructure In Brazil
Naielly Marques
PUC-Rio
Brazil
Katia Rocha
Institute of Applied Economic Research (IPEA).
Brazil
At the end of 2022, Brazil's National Land Transport Agency (ANTT) launched a public hearing on the proposal for a new risk allocation model in road infrastructure concession contracts. This study illustrates, using the real options methodology, how the proposed design modifies the concession's risk-return structures and influences the investment decision in the concession and the expected value of the upside risk sharing mechanism (cap) and downside (floor). Our analysis allows the granting authority to calculate the trade-off between the establishment of cap and floor bands, flexibility of Capex triggers (anticipation of the start of the risk sharing mechanism) and potential tariff discounts. The study shows that there is an optimal frontier of efficient portfolios (bands x triggers) that maintains the same risk-return structure and, consequently, discounts. In this sense, the granting power can allocate itself wherever it most desires depending on the concession object, which can be useful for analyzing regulatory impacts caused by this mechanism. This research contributes to the literature on the applications of real options in infrastructure projects, showing how the clauses governing managerial flexibilities in contracts must be carefully designed to achieve the objectives of the government and the private investor.
Capacity Investment and Market-Driven Price Caps In Electricity Markets
Jacco Thijssen
University of York
United Kingdom
I build a continuous-time model of incremental capacity investment in electricity generation by a representative firm with stochastically evolving electricity prices and time-to-build. The model results in a ``market-driven price cap'' on electricity prices at pledged capacity. This cap is increasing in the cost of investment, time-to-build, volatility of electricity prices, and the market price of electricity price risk. The cap is decreasing the elasticity of demand. It is shown that investment only takes place when demand is elastic and that electricity prices can still increase substantially, even after new capacity has been pledged, due to construction delays. This opens up the possibility of welfare-increasing policy intervention.
Comparing Simulation-Based Methods: Case Applications In Finland
Santeri Liukkonen
LUT Business School
Finland
Mariia Kozlova
LUT Business School
Finland
Roman Stepanov
LUT Business School
Finland
Julian Scott Yeomans
Schulich School of Business
Canada
At the core of real options theory is the recognition of uncertainty surrounding investment projects and a desire to derive value out of that uncertainty. The uncertainty can be captured in multiple ways; one of the most used is Monte Carlo simulation with a follow-up representation of the Net Present Value (NPV) probability distribution. In this research, we focus on two Monte Carlo simulation-based methods. The Datar-Mathews (DM) real options method and the global sensitivity analysis Simulation Decomposition (SimDec) approach are compared in terms of value added for decision support.
Our research contrasts the visual analytical insights that the simulation-based methods can provide to decision-makers by applying the two methods to three very different real-world innovative business case scenarios taking place in Finland. The first case is a standard use-case for real options in R&D. The second case uses real options to estimate the value of flexibility “in” a complex pumped hydroelectric storage system. The third business case explores using real options to help value and negotiate a contractual clause for a multi-party joint venture.
The results of this research demonstrate that the Datar-Mathews method possesses relatively limited informativeness, providing only a single real option value and a plain histogram. The decision support can be greatly improved by quantifying and showing which scenarios and input parameters have the greatest impact on the investments’ success, as SimDec does. Thus, SimDec is able to answer the prescriptive analytics question “how to achieve the desired outcome?”, providing actionable information to the decision-makers.
Competitive Real Option Portfolio Risk In A Duopoly
Dean Paxson
University of Manchester
United Kingdom
Roger Adkins
University of Manchester
United Kingdom
Alcino Azevedo
University of Aston
United Kingdom
We evaluate the risk aspects of a simple portfolio of real options to invest for a duopoly. After summarizing the basic model, covering three sequences, two thresholds, and three strategic and rival options, we look at five risk elements: delta, vega, rho (the conventional option Greeks) along with epsilon (drift) and alpha (market share). The value function of both the leader and follower is most sensitive to revenue (delta), interest rate (rho), drift (epsilon) and market share (alpha) variations, which we view in terms of sensitivities (to percentage changes), partial derivatives (analytical confirmed by numerical) and to a range of each of the input variables. Naturally, delta and rho hedging are plausible and appropriate risk avoidance actions. Maintaining final stage market share is particularly important for the follower.
Energy Transition Policy Options
Frank Heinz
RWTH Aachen University
Germany
Reinhard Madlener
RWTH Aachen University
Germany
The next step in the ongoing energy transition is investment in storage and electrolyzer capacity on an industrial scale. From an investors' perspective, these assets are particularly difficult to evaluate because on the one hand, their business model requires large electricity price fluctuations, while on the other hand, exactly these fluctuations increase uncertainty, against the background of transitioning from conventional power generation to a decarbonized state. We present a generalized setup for an optimal stopping problem which manages these uncertainties in a realistic setting and solve the trade-off between investment encouraging versus deferring effects. We get there in four steps: first, a stochastic model of the electricity market, based on its underlying drivers of supply and demand with their periodic trends, is developed. Second, with the help of studies on energy transition, realistic target states are defined in the form of several scenarios. Third, the resulting multi-dimensional optimal stopping problem is formulated in a generic way and adapted appropriately. Fourth, the numerical analysis of the dynamic programming problem is mastered. We can show that under a wide range of assumptions, although we find an even increasing volatility in the electricity price, the investment encouraging effect of price fluctuations largely keeps the upper hand over the investment-deferring effect of volatility. The consequence for energy policy making is that the investments can be stimulated mostly with the day-ahead market for electricity and do not, or to a lesser extent, require rigid, costly and competition distorting subsidy schemes.
Evolution and Trends of Real Options Under Incomplete Markets: A Bibliometric Review
Rafael Gomez-Gomez
Universidad de Manizales - EGADE Business School
Colombia
Eliana Morales Zuluaga
Universidad de Manizales
Colombia
Contribution: This bibliometric study contributes to the theory of real options under incomplete markets by identifying the journals who document the transition of the study of real options from finance to management, four thematic nodes, three articles whose impact makes them pillar, and three lines of evolution that allow the identification of emerging categories for new research.
Purpose: This paper aims to analyze how research and the use of real options under incomplete markets has evolved.
Gap: So far, bibliometric studies in real options have focused on the application to specific fields such as natural resources, commodities, and fields such as medicine. Despite the relevance of the problem of completeness, most articles have addressed the problem from the literature review and there are no bibliometric studies that focus on methodological aspects.
Relevance: The evidence suggests deepening in the evolution of real options in incomplete markets, showing a path towards a better understanding and adoption of advanced techniques of prospective and decision analysis.
Impact: This study contributes significantly to the area of finance and financial management by showing the evolutionary process of real options in incomplete markets as well as by identifying the scientific web that has supported their evolution.
Methodology: As bibliometric studies are increasingly the focus of literature reviews in economics, management and finance, a bibliometric approach was applied to a series of articles studying the valuation of real options in incomplete markets.
Flexibility In Bidding Strategies Among Consortia In Brazil
Gláucia Fernandes Vasconcelos
UFRJ
Brazil
Alexandre Scarcioffolo
Denison University
United States
Carlos Bastian-Pinto
PUC-Rio
Brazil
In the contemporary economic and social scenario in Brazil, consortia have emerged, playing a crucial role in financing goods and services while offering an alternative to conventional acquisition methods. This article aims to apply the real options method to the analysis of consortia. The literature review highlights gaps in traditional consortium analysis methodologies, emphasizing the dynamics and uncertainty present in this collaborative environment. Real options theory is examined within credit contexts, substantiating the innovation of this approach in the consortium scenario. The proposed methodology incorporates principles of real options theory in consortium analysis, considering the flexibility of bidding strategies. Case study and simulations are employed to illustrate the application of this approach to managing uncertainty and adapting to changes in market conditions and participant preferences. The results highlight the pressing need for more sophisticated tools to analyze dynamic strategies in collaborative financial decision-making for a clear definition of the returns and risks involved in this financial structure and to guide the decisions involved with these investment alternatives.
Flexible Use of Green Hydrogen: An Application of The Option To Switch Between Hydrogen and Ammonia In Brazil's Renewable Energy
Antonio Intini
Politecnico di Bari
Italy
Sidnei Oliveira-Cardoso
PUC-Rio
Brazil
Carlos Bastian-Pinto
PUC-Rio
Brazil
Roberta Pellegrino
Politecnico di Bari
Italy
Air pollution and global warming pose urgent challenges that require the decarbonization of key sectors of the economy. Brazil, a leader in electricity production from renewable sources, can use part of this energy to produce green hydrogen, offering an innovative solution to environmental problems. This study uses a real option approach to evaluate a hypothetical investment in an electrolyser and an ammonia synthesis plant to exploit the flexibility of hydrogen in being able to be used in different ways by different sectors. In particular, the analysis considers a switch option which gives to the investor the possibility to choose, period by period, when to produce green hydrogen and to which sector to sell it, and when to convert it into green ammonia, with the aim of maximizing the final cash flows. The value of the option is calculated comparing the net present value of the investment with the base case of selling electricity on the free market, subject to high price volatility and therefore high probability of loss. Preliminary results, obtained with a simplified model, indicate that the switch option increases return of the investment, allowing to choose what to produce and sell based on market conditions.
How do Suppliers' Market Power Changes Affect A Buyer's Investment Decisions?
Benoit Chevalier-Roignant
Emlyon Business School
France
Stéphane Villeneuve
Toulouse School of Economics
France
Supply chain tensions have become an issue often talked about. Our paper develops a set of stylized models studying the effect of an increase in suppliers' market power on a buyer's investment decisions. First, we study the case where the buyer regularly goes to the input market to source from a known set of oligopolistic suppliers and determine the buyer's optimal investment policy. We then study the conditions under which the buyer is better off committing at the time of investment on a production schedule signing with the set of suppliers a framework agreement regulating the input price. Finally, we endogenize the size of the pool of suppliers the buyer can source from by considering a supplier's decision to exit a market if the economic circumstances are not satisfactory. The degree of competition in the input market is a key driver of a buyer's investment decision. While supply contracts favor suppliers, they lead to a delayed investment by the buyer. Cost asymmetry among suppliers may lead the buyer to delay its investment as a tradeoff between waiting for clarity about the supplier base or securing better terms with a larger pool, which is less likely to sustain.
Incorporating Charitable Endowment In Financing Sustainable Infrastructure Ppp Projects: The Case of Islamic Bonds In The Economic Development of Emerging Countries
Wahyu Jatmiko
Southampton University
United Kingdom
Rafal Wojakowski
Surrey University
United Kingdom
M. Shahid Ebrahim
Durham University
United Kingdom
Novriana Sumarti
Institute of Technology Bandung
Indonesia
The economic development of emerging countries necessitates an efficient funding mechanism. This paper models
the cultural perspectives of blended infrastructure financing in developing Muslim economies by examining Islamic bonds (sukuk). We identify the structural imperfections of this value-based instrument and offer a novel solution to remediate opacity and agency costs of debt. Relying on a mix of Participating and Continuous Workout financing, we model a financially engineered sukuk for impact financing by incorporating charitable endowment (waqf) into the public-private partnership (PPP).This allows to develop a fragile-free blended finance facility to overcome the impact of financialization and inequality in infrastructure development.
Integrating Generative Artificial Intelligence and Humans Under Uncertainty
Du Liu
East China Normal University
China
This study explores how uncertainty in Generative Artificial Intelligence (Gen-AI) performance and market conditions affects strategic decision-making in AI-human collaboration using a real options framework. Four strategies are modelled: human only, AI-exclusive use, task distribution between humans and AI, and the Human-in-the-loop approach. The research shows that higher chances of AI success encourage earlier adoption of AI-inclusive strategies, while greater market uncertainty delays transitions to more AI-driven approaches and highlights the need for human involvement. The findings suggest that fully relying on AI is suboptimal, with the Human-in-the-loop strategy offering the most benefits. This study provides a dynamic AI adoption model and offers valuable managerial insights for optimizing AI-human collaboration under uncertainty.
Interaction of Dividend Policy and Merger Dynamics
Paulo J. Pereira
University of Porto
Portugal
Artur Rodrigues
University of Minho
Portugal
This paper explores the interaction between dividend policy and mergers and acquisitions (M&A) in a dynamic setting. It examines the decisions faced by two firms regarding their dividend payout policy in the presence of a potential merger between them, under the risk of liquidation. The payout strategy (barrier or band) will depend on the level merger costs. One key finding of the paper shows that, unlike previous literature on merger cooperative games, firms' bargaining power becomes endogenous in leading to merger agreement.
Investment and Financing Decisions Under Constrained Demand In Infrastructure Projects
Paulo J. Pereira
University of Porto
Portugal
Artur Rodrigues
University of Minho
Portugal
This paper examines the effects of an output cap and an upper reflecting barrier on demand. The output cap arises from the finite output capacity of the firm, leading to a portion of the potential demand remaining unsatisfied. Simultaneously, the reflecting barrier captures the realistic scenario in which part of the unsatisfied demand opts for alternative consumption choices. This model is particularly relevant in the context of infrastructure projects, such as airports. The main findings reveal that an upper reflecting barrier significantly affects leverage decisions, while its impact on investment timing decisions is less pronounced. The effects become more prominent under higher uncertainty. When the option to expand exists, eliminating both the cap and the barrier, initial investment accelerates and leverage ratios and credit spreads decrease.
Investment In Circular-Economy Additive Manufacturing: An Application To Furniture Smes
Antonio Piepoli
Politecnico di Bari
Italy
Roberta Pellegrino
Politecnico di Bari
Italy
Pierpaolo Pontrandolfo
Politecnico di Bari
Italy
Small and medium-sized enterprises (SMEs) in the furniture industry face challenges due to fluctuating demand and the trend towards sustainable and customized products. However, SMEs may struggle to adopt innovative digital technologies due to high initial costs. Additionally, fluctuating demand for metal structures and components can significantly affect the supply of SMEs. Nonetheless, certain critical metals carry a high global supply risk, which can expose furniture SMEs to disruption. In this context, implementing Industry 4.0 (I4.0) technologies can increase a company's productivity and flexibility in response to sources of uncertainty, while enabling the achievement of circular economy (CE) principles. The aim of this research is to analyze investments in Additive Manufacturing (AM) for the furniture industry by using the Real Option Valuation method to model the internal flexibility mechanism of manufacturing options. The research will specifically consider the choice between externalization to third-party suppliers or internalization through the implementation of AM technologies for metal structures and component manufacture in the furniture industry. Moreover, this study examines the potential of manufacturing options to enable CE practices in order to mitigate various sources of uncertainty, including production capacity constraints, price volatility and product reliability. The results confirm that the integration of AM technologies can enhance the capabilities of furniture SMEs, leading to increased customer satisfaction, improved supply security of metal structures and components, enhanced product sustainability, and greater competitiveness in the marketplace. Finally, the study concludes by discussing the implications of each option for enabling CE practices.
Irreversibility, Uncertainty, and The Optimal Finance of Public Goods
Yishay Maoz
The Open University
Israel
This article analyzes the case where a government finances the supply of a public good via a tax on a private good which is produced and traded in a market where demand is stochastic, production requires an initial irreversible investment, and firms can choose optimally when to invest. The government problem is to find the tax rate that maximizes overall welfare, which is a composite of the welfare generated by the production of each of the two goods. The analysis reveals this optimal tax rate and enables characterizing it, as well as characterizing the equilibrium dynamics under the optimal tax rate. Of particular interest is the result that the higher the uncertainty regarding the demand for the private good the higher the optimal tax rate.
Learning, Uncertainty Reduction and Optimizing The Location of Delimitation Wells In Hydrocarbon E&p
Wellington Nascimento
PUC-Rio and Petrobras
Brazil
Marco Pacheco
PUC-Rio
Brazil
Marco Dias
PUC-Rio
Brazil
Carlos Bastian-Pinto
PUC-Rio
Brazil
Luiz Brandão
PUC-Rio and University of Texas at Austin
United States
The phases associated with the search for, and production of hydrocarbon reservoirs are known as Exploration and Production (E&P). The five main phases are: exploration, evaluation, development, production, and abandonment. As each step depends on the previous one, a combination of successful exploration, optimized assessment and commercial extraction is required to ensure a successful E&P cycle. Determining the number of appraisal wells is a problem widely discussed in the literature, however, studies are limited in determining the number and location of wells to obtain maximum profitability. There is no systematic approach. In this work we will use uncertainty reduction to optimize the location of wells. A quantity known as a learning measure will be used to measure the reduction of uncertainty in obtaining information. We use Geostatistics to obtain the spatial correlations of the delimitation wells. The study will complement the analysis of the value of information in the context of reducing uncertainty via evaluation wells. We will also analyze the value of flexibility quantified through real options theory which emphasizes the value of information. The use of real options will take place through the problem of delimiting the volume of oil, considering that there is already a discovery. This option is called a learning option because our objective is to resolve doubts in the delimitation stage and subsequently decide whether or not to develop the discovered field. This decision is strongly influenced by the economic context, known in the literature as market uncertainty.
Market Vs Consensus Negotiation Mechanisms For The Adoption of Industry Compatibility Standards
Laura Delaney
Kings College London
United Kingdom
Tarik Driouchi
Kings College London
United Kingdom
We apply a game-theoretic real options approach to analyse two mechanisms for the adoption of industry compatibility standards in situations of conflict. Conflicts arise if the players agree that adoption by the industry of one particular standard is best for all, but they each have a vested interest in their own preferred standard being the industry choice. We analyse the two main mechanisms for standard adoption: one mechanism focuses on achieving consensus via negotiation and the other is via the market in which one player unilaterally adopts and expects her competitors to follow suit. A key question in the field is which mechanism performs better. Another is when should a participant take the lead and unilaterally adopt a particular standard.
We address these questions in our paper by deriving equilibrium strategies for both mechanisms. In particular, we show that by considering the problem from the unique perspective as a real option timing game, a comparison of the mechanisms to help inform the industries which performs best cannot provide a definitive answer because it depends on each of the participants' expected payoffs from unilateral adoption and concession at any given time. Furthermore, the equilibrium expected payoffs in each of the mechanisms are equivalent.
Minimum-Revenue Guarantee Levels In Ppp Projects: An Application To Transportation Infrastructure
Glaucia Fernandes
COPPEAD/UFRJ
Brazil
Naielly Marques
IAG/PUC-Rio
Brazil
Jim Dyer
University of Texas at Austin
Brazil
Luiz Brandao
IAG/PUC-Rio
Brazil
There is a growing reliance on private capital for funding infrastructure projects globally, particularly through Public-Private Partnerships (PPPs). However, private investors may perceive certain projects as excessively risky, potentially leaving governments without viable bidders. To incentivize private investment, governments often provide risk mitigating mechanisms such as subsidies, incentives, revenue guarantees or even term extensions. Yet, most of these mechanisms involve upfront costs or future liabilities for taxpayers. The Minimum Revenue Guarantee (MRG) is a common risk mitigating mechanism in PPPs, but the optimal procedure to determine its optimal design remains unclear. Building on existing literature, this paper proposes the use of the cap and floor model, widely used in European electricity markets, to mitigate risks in infrastructure projects in transportation. Unlike revenue-based approaches, the model's cost-based cutoff values offer simplicity and transparency. The floor guarantees minimum revenues to cover project costs, while the cap restricts excessive returns. Although successfully applied in electricity markets, its application to transportation infrastructure remains underexplored. The paper contributes to the literature by showing how this approach can be successfully applied to infrastructure financing. We model the cap and floor regime under the real options approach and apply this model to a numerical example. Our results suggest that this model is effective in assisting policy makers determine the optimal cap and floor levels while minimizing the cost to the government and taxpayers.
Mitigation of Demand Risk In Ppp With Funding Via Risk Sharing: The Case of Rio Airport In Brazil
Liliana Dennis Mejia Sanchez
PUC-Rio
Brazil
Luiz Brandão
PUC-Rio and University of Texas at Austin
United States
Carlos Bastian-Pinto
PUC-Rio
Brazil
Concession contracts often include clauses for sharing; mainly, demand and exchange rate risk. The modeling of concession contracts has evolved over the years. An interesting innovation is the implementation of a bank account mechanism. The mechanism aims to ensure the economic-financial sustainability of the concession. Most academic studies on risk-sharing mechanisms are focused on calculating their value and effect. However, there is little attention to how to fund the results of risk-sharing mechanisms. This paper aims to propose a strategy to mitigate demand risk through risk sharing, but without generating liabilities for the granting authority. This model combines the Minimum Revenue Guarantee (MRG) with the Accounts Mechanism. The MRG is used to mitigate demand risk, and the Account Mechanism is used to generate funds to compensate the MRG. This model is called Minimum Revenue Guarantee with Guaranteed Liabilities Mechanism (MRG/GL). The real options approach is used to calculate the value of the mechanism proposed (MRG/GL). To illustrate the functioning of the model, we use the International Airport of Rio de Janeiro-Galeão as a case study. Furthermore, the MRG/GL mechanism is simulated using two different auction criteria. The MRG/GL is analyzed as a sequence of European Options (Put), with annual maturity. Finally, the Monte Carlo Simulation is used to compare the variations in airport revenue and calculate the put value.
Navigating Dual Disruptions: The Impact of Brexit and Covid-19 On Uk Sme Investment and Growth
Karolis Matikonis
University College Dublin
Ireland
Byron Graham
Queen's University Belfast
United Kingdom
Although economies experienced substantial turbulence from Covid-19, the United Kingdom Government rejected the possibility of a transitional period extension after the withdrawal from the European Union. This study uses microdata to unpack the impact of reduced investment due to the increased uncertainty attributable to Brexit and Covid-19 on SME growth.
Optimal Entry Deterrence By An Incumbent Under Uncertainty
Richard F. Hartl
University of Vienna
Austria
Peter Kort
Tilburg University
Netherlands
Stefan Wrzaczek
IIASA, Laxenburg
Austria
The objective of this paper is to study an incumbent-entrant model under uncertainty. The entrant knows the realization of the random variable(s) before it makes its decision on entry and eventual capacity choice. So all the uncertainty is on the incumbent's side. The sources of uncertainty include the characteristics of the entrant's product and the entry cost the entrant needs to incur before becoming active. We know from the literature that the incumbent-entrant setup could result in three different outcomes: blockaded entry, i.e., the incumbent behaves like a monopolist and the entrant does not enter, deterred entry, i.e., the incumbent overinvests to make the market unprofitable for the entrant, and accommodated entry. The main result from our work is that under uncertainty there can be four outcomes: apart from blockaded entry and accommodated entry, it can be either 100% entry deterrence or entry deterrence with a certain probability.
Optimal Strategies For Information Updating, Learning and Investment Under Knightian Uncertainty
Junichi Imai
Keio University
Japan
Motoh Tsujimura
Doshisha University
Japan
In this paper, we investigate the value of learning options under the Knightian uncertainty. A theoretical framework is presented for determining optimal strategies for information updating, real investment strategies based on the updated information, and evaluating the information to resolve Knightian uncertainty. To this end, we formulate the problem of determining optimal real investment strategies under Knightian uncertainty using the real options framework. The formulation is notable for its inclusion of proactive information gathering. An analytical examination is conducted using a simplified model. Numerical demonstrations are used to complement this examination and determine optimal strategies, as well as to quantify the value of learning options across a range of scenarios.
Optimal Timing and Scale of Green Technology With Demand Preferences For Greener Production
Nicos Koussis
Frederick University
Cyprus
Florina Silaghi
Universitat Autònoma de Barcelona
Spain
We study firms’ decisions concerning the timing of installing green technology in production and the optimal mix between brown and green technologies. Firms’ decisions are driven by uncertain demand, where consumers are environmentally sensitive and either reward products with more green technologies or penalize those that do not meet environmental targets. Capital allocation is also influenced by the relative costs of installing brown versus green technologies, as well as their efficiency in production. High regulatory targets for a green energy mix in production, such as those set within EU countries, help accelerate investment in green technologies. Firms aim to avoid higher penalties by investing earlier; however, this may result in a lower scale of green technology adoption. Factors such as higher volatility and growth levels of demand, less efficient green technologies, or high existing capacity may delay investment in the green transition. We explore the effect of an uncertain regime shift toward more environmentally sensitive consumers, demonstrating how this uncertainty impacts firms’ initial and subsequent choices between green and brown capital. We finally consider the social planner’s maximization problem which includes firm’s generated profits and the benefit for the society in the form of a consumer surplus as well as the negative externalities on the environment.
Optimal Timing and Scale of Investment In Hydrogen Infrastructure: Is The Hydrogen Fuel Cell Truck A Better Option?
Oana Ionescu
Grenoble INP/GAEL
France
Alain Kibangou
UGA/Gipsa Lab
France
The transformation of current production and consumption patterns and energy supply to reduce greenhouse gas (GHG) emissions are priority sectors. In particular, the production of electricity can be decarbonized by using energy sources with low or no GHG emissions. Cleaner mobility by 2050 based on hydrogen technology takes on its full strategic value when political decision-makers and consumers anticipate a reversal in the evolution of the various parameters, upsetting the pre-established order in terms of economic performance. To describe this phenomenon, it is necessary to obtain information on the evolution of the prices of electricity, hydrogen, fuels used and long-term demand. Therefore, a more comprehensive analytical framework should simultaneously incorporate the short-term uncertainties associated with the operation of hydrogen and fuel cell technology, storage and the necessary infrastructure, and the associated long-term uncertainties such as market developments, investment in low-carbon assets and financing costs. In our paper, we use a real options approach and we assess the regulatory uncertainty in terms of subsidy and the speed of adoption of fuel cell trucks in France. With a continuous-time model and dynamic programming method we determine the optimal timing and scale of investments in hydrogen infrastructure, influenced by dynamic subsidy policies and adoption rates of fuel cell hydrogen trucks.
Public Infrastructure and Applications In North America and The Eu
Yuri Lawryshyn
University of Toronto
Canada
In this presentation we present recent trends related to the use of real options in public infrastructure investment in North America and the European Union.
Public Infrastructure: Overview and Applications
Luiz Brandao
PUC-Rio Brazil and University of Texas at Austin
United States
Infrastructure opening presentation for the Thursday panel of the Managerial session
Reactivating Idled Resources: The Case of Oil & Gas Drilling Rigs In Texas
Toby Li
Texas A&M
United States
Jan-Michael Ross
Imperial College London
United Kingdom
Jeffrey J. Reuer
Purdue University
United States
real options theory, resource-based perspectives, capabilities, resource reactivation, demand uncertainty
Real Options: Added Returns Versus Added Risk
Arkadiy Sakhartov
University of Illinois at Urbana-Champaign
United States
Risk in a firm is not just the variance of its accumulated net cash-flow with the unchanged allocation of that firm’s resources to its business. Multiple resource reallocation strategies, or real options, not only change a firm’s return but also alter that firm’s risk. This study has used formal models to explore how four popular real options (redeployment/switching, idling/shutting down, divestiture/abandonment, and growth/acquisition) change risk in a firm and has come to the following tentative conclusions. First, the presence of real options generally entails the tendency for a positive risk-return relationship in firms. Second, despite this general tendency, at least some options allow firms to receive high returns and low risk at once. Third, some option determinants have oppositely directed effects on risk and on return. Finally, some real options can reduce a firm’s risk, whereas other real options always increase that risk.
Real-Time Information Systems For Dynamic Management
Mikael Collan
LUT University
Finland
Jyrki Savolainen
LUT University
Finland
Investment management systems are information systems designed for tracking the development of the value of financial investments or financial investment portfolios. The information these systems use and contain is updated even on real-time basis. Interestingly, similar systems are not common for planned or operational real-investments / portfolios of real-investments. In this paper, we discuss management systems for real-investments including the management of real options. Aspects that have to do with data-availability, automated data-gathering and data-input, different types of real option valuation models that can be utilized in the systems and their data-needs, information and results presentation, and the benefits of collecting time series of the development of results, such as trend information.
Safety Risk Mitigation In Oil & Gas: An Application To An Oil Refinery
Marcelo Guedes Pecly
PUC-Rio
Brazil
Carlos Bastian-Pinto
PUC-Rio
Brazil
Leonardo Lima Gomes
PUC-Rio
Brazil
This paper researches the academic and market literature relative to financial assessment of risks in Operational Risk Mitigation in Oil & Gas Industry. Decision-making must take into account flexibilities and potential for future learning. Modelling Safety Processes using a Real Options approach allows the valuation of these risks. This enables quantification of projects and assets within an uncertain environment, particularly in cases involving low-frequency but high-impact events such as accidents or equipment breakdowns, which result in significant harm and financial losses. The research seeks to apply the methodology with integrated dynamic risk simulation to quantify the probabilities of financial expenditure in the occurrence of operational risks (or deviations). Utilizing a refinery as a case study and accounting for typical fatality patterns within this sector, the study maps out the costs associated with deviations. By extrapolating these estimates, the research provides insights into potential investments in Research and Development (R&D) for operational safety, elucidating their incremental impact on underlying assets.
Subsidies and Sustainable Tourism: Balancing Demand Guarantees With Environmental Damage From Tourism
Luciana Barbosa
ISCTE - Instituto Universitário de Lisboa and Business Research Unit (BRU-IUL)
Portugal
José Carlos Dias
ISCTE - Instituto Universitário de Lisboa and Business Research Unit (BRU-IUL)
Portugal
Margarida Marques
ISCTE - Instituto Universitário de Lisboa
Portugal
This paper considers the problem of taking a managerial decision associated to an investment project in a trail designed for tourist activities. Our real options models study the existence of alternative temporary minimum demand guarantee policies aiming to encourage new private investments, but without neglecting the potential environmental damages when the number of tourists is too excessive. We provide an elegant analytical characterization for both the value function of the active project and for the infinite-horizon optimal stopping problem.
Sustainable Agriculture Balancing Build-To-Suit Contract and Carbon Prices: An Application To "Green Cattle" and Farming In Brazil
Marina Lins de Carvalho
UFRJ
Brazil
Gláucia Fernandes Vasconcelos
UFRJ
Brazil
This paper demonstrates the effectiveness of utilizing the real options approach in analyzing investments in "green cattle". The primary objectives include discussing real options theory and illustrating its application in modeling uncertainty and managerial flexibility in a collaborative relationship between a small farmer and a high-emission industry company aiming to reduce emissions through a build-to-suit contract of the land and trading carbon credits produced in the land. Additionally, the paper demonstrates the calculation of specific options, focusing on this contractual arrangement. The analysis explores two management options: expanding business activity and delaying investment. Considering the stochastic nature of future cattle and carbon credit market prices, the Monte Carlo simulations unveil a notable inherent risk, contrasting with conventional analyses that may imply profitability. The real options approach indicates a significant value when an option is exercised, with the level of uncertainty in the expanded model dropping 71%, demonstrating that the option holds substantial value. Sensitivity analysis for input option parameters further emphasizes the limitations of the traditional model to adequately address management's ability to adapt to economic shocks, risks, and uncertainties in investments involving build-to-suit, carbon credit, and green cattle.
The Option To (re)develop Or Abandon A Mature Depreciating Oil Field
Maher Al-Sharea
Heriot-Watt University
United Kingdom
Towards the end of the life of mature fields, the decline in production leads to diminishing cash flows. At this stage, the operator faces the crucial decision of either continuing, abandoning, or reaching for remaining, but harder-to-access reserves. The timing of this decision has economic consequences, particularly with uncertain prices and technical challenges.
The optimal decision of redevelopment or abandonment depends on the level of prices and the chance of success in accessing added reserves. We use an integrated real options framework through an illustrative example to discuss solutions and sensitivities to this multi-dimensional problem.
The Timing and Terms of Mergers For Organically Growing Firms
Riccardo Calcagno
Polytechnic University of Turin
Italy
Richard Ruble
Emlyon Business School
France
We study how competitive firms accumulate capital and undertake a productivityraising merger. We derive optimal investment and acquisition policies for standalone
firms and with a merger option. Industry development generally involves an initial phase of catch-up growth to reach a long-run expansion path. On the long-run path
highly capitalized firms wait to merge their current assets before pursuing further growth, whereas undercapitalized firms grow their assets first and merge at a higher
threshold. If decisions are decentralized and firms commit to future deal terms, relative productivity-based shares induce efficient investment and merger decisions.
Use of Real Options In Practice: The Legal Case of International Arbitration Over The Loss of A Mining Project
Graham Davis
Colorado School of Mines
United States
In 2019 an international arbitration proceeding based its financial award on a real options model of mine project value. This impetus for the arbitration's selection of a real options model over other valuation techniques was noted to be the evolution of the approach within the industry. In this paper one of the valuation experts involved in the proceeding reviews the arbitration and the decisions reached by the tribunal to award Claimant over $4 billion in damages for the loss of a mining project. Of note, the publicly available award documentation lays bare the tribunal's consideration of the real options valuation technique and its acceptance of the technique despite its relatively new application in arbitration.
Use of Sensitivity Analysis In Real Options Studies
Abid Nahiyan Alam
Queen's University
Canada
Mariia Kozlova
LUT University
Finland
Julian Scott Yeomans
York University
Canada
The ability to incorporate flexible strategic decision making under risk and uncertainty have made real options (RO) models a popular approach for project/investment valuation. For such models to be effective in providing reliable decision support, as with any model, it is crucial to understand how model responses vary with the input variables, model parameters, and any underlying assumptions. The scientific field, which is responsible for it, is sensitivity analysis (SA). One at-a-time (OAT) SA often leads to misrepresentations due to its inherent inability to detect underlying model complexities and confounding factors. Consequently, the more sophisticated Global SA methods tend to prove more appropriate for application in the wide variety of complex models employed in such fields as engineering and finance. In this research we study the use of SA in RO literature along both the extensive (degree of adoption) and intensive (quality of adoption) margins. We do so by first identifying all relevant studies in the SCOPUS database, and then performing a systematic review of the identified body of work. Our preliminary findings suggest that the adoption rate of SA in the RO literature is poor at best. Furthermore, even when adopted, adequate methods are frequently overlooked in favor of sub-optimal methods. Specifically, only 3% of the studies consider SA and fewer than 1% of them employ global SA methods.
Using Reinforcement Learning To Value Multi-Factor Option Mining Projects
Yuri Lawryshyn
University of Toronto
Canada
Reilly Pickard
University of Toronto
Canada
In this study, we consider both one-factor and two-factor real options mining valuation problems. In the one-factor case, we further explore the use of RL to solve the build / abaondon problem we presented in \citeN{Lawryshyn23}. In the two-factor model we introduce a second process where the quantity (or quality) of the mined mineral is uncertain and, as mining proceeds, more is learned about the quantity available allowing for staged investment. We attempted to solve the two-factor "learn-as-you-go" (LAYG) problem using the EBF method previously with partial success. Our objective is to explore the opportunity to use RL for valuing realistic, computationally difficult real options problems. We note that this study is a work in progress.
Valuation of Co2 Storage Buffer In Hydrocarbon Well Recovery Projects
Ibrahim Kadafur
Heriot-Watt University
United Kingdom
Using Carbon Capture Utilization and Storage (CCUS) is crucial for achieving greenhouse emission reduction goals. While most studies have discussed the technical aspects, few focused on the economic valuation of such projects. This interdisciplinary work provides insights into the link between CCUS technology and the economics of projects. We study the economic feasibility of storing CO2 in a saline aquifer serving as a buffer to an oil reservoir for the expected needs of emission reduction and CO2 Enhanced Oil Recovery. Will such use of buffer storage lead to an economic advantage over the common methods of sourcing CO2 from external sources? How much of the CO2 stored in the Aquifer is recoverable? Which well architecture, production, and injection constraints favour the process? We utilize an integral economic model along with reservoir models for our analysis and valuations of the decision alternatives.
Valuing Pay-For-Success Contracts In Social and Financial Innovation: A Put Spread Formula
Andreas Andrikopoulos
University of Piraeus
Greece
Andrianos Tsekrekos
Athens University of Economics and Business
Greece
Pay-for-success contracts are social and financial innovations in social policy and capital markets, respectively. This paper argues that they exhibit option-like payoffs and implements standard option-pricing arguments in assessing the value of investing in pay-for-success contracts. Sensitivities vis-à-vis contract specifications are reflected in the valuation formula and help reach investment and social policy decisions.