Investment decisions with two-factor uncertainty

This paper considers investment problems in real options with non-homogeneous two-factor uncertainty. We derive some analytical properties of the resulting optimal stopping problem and present a finite difference algorithm to approximate the firm’s value function and optimal exercise boundary. An important message in our paper is that the frequently applied quasi-analytical approach underestimates the impact of uncertainty. This is caused by the fact that the quasi-analytical solution does not satisfy the partial differential equation that governs the value function. As a result, the quasi-analytical approach may wrongly advise to invest in a substantial part of the state space

CO2 storage or utilization? A real options analysis under market and technological uncertainty

Carbon Capture and Storage (CCS) and Carbon Capture and Utilization (CCU) are considered essential solutions to reduce greenhouse gas (GHG) emissions worldwide. A crucial difference between the two is that CCS is already a mature technology, while CCU is still in the R&D phase. Hence, firms are confronted with a dilemma, where they have to choose between either the mature CCS, the emerging CCU, or the installation of both in a Carbon Capture Utilization and Storage (CCUS) system. In this study, we analyze different strategies that the firm can pursue and determine the optimal investment timing. In doing so, we take into account both technological uncertainty, i.e. the unknown time-to-market of CCU, and market uncertainty, i.e. the CO2 price. Three different CCUS value chains in the cement industry are analyzed. We find that the anticipated arrival of profitable CCU technologies in the future does not delay investments in CCS in the current period. Investments in CCS and CCU can be accelerated by reducing the volatility of the CO2 price, or by increasing the growth rate of the CO2 price. Finally, we find that a higher fraction of CO2 emissions that can be used in CCU, results in sooner adoption of CCS today

Strategic Technology Switching under Risk Aversion and Uncertainty

Firms devising green investment strategies within a deregulated environment must take into account not only economic and technological uncertainty, but also strategic interactions due to competition. Also, further complicating green investment decisions is the fact that firms are likely to exhibit risk aversion, since alternative energy technologies entail risk that cannot be diversified. Therefore, we develop a utility-based, real options framework for pre-emptive and non-pre-emptive competition in order to analyse how economic and technological uncertainty interact with risk aversion to impact the adoption of an existing technology in the light of uncertainty over the arrival of an improved version. We confirm that greater risk aversion delays investment and show that technological uncertainty accelerates the follower’s entry, delays the entry of the pre-emptive leader, and, intriguingly, does not affect the non-pre-emptive leader’s investment decision. Also, we show how the relative loss in the leader’s value due to the follower’s entry is affected by economic and technological uncertainty as well as risk aversion, and how the risk of pre-emption under increasing economic uncertainty raises the value of direct investment in the new technology relative to stepwise investment

Strategic real options: Entry deterrence and exit inducement

The focus of this thesis is the analysis of the strategic behavior of the firms undertaking an irreversible investment decision in an uncertain environment. In particular, this thesis contains three studies, in which we develop continuous-time investment models under uncertainty with lumpy investment. The first two studies analyze firms’ competitive strategies in a setting where they decide not only upon the optimal timing of the investment, but also upon the scale of its installment. In Chapter 2, we examine how hidden competition affects the capacity investment decisions in a duopoly. Chapter 3 extends the strategic investment model with capacity choice by incorporating the exit option. Chapter 4 presents a stochastic dynamic model of predatory pricing under firm-specific uncertainty

Stock markets during COVID-19

Author's accepted version (postprint).This is an Accepted Manuscript of an article published by Universitetsforlaget in "Beta” on 21/06/2022.Available online: https://www.idunn.no/doi/10.18261/beta.36.1.3acceptedVersio

Transmission Investment under Uncertainty: Reconciling Private and Public Incentives

Private companies (PCs) in restructured electricity industries determine facility investment timing and sizing. Such decisions maximize the PC’s expected profit (rather than social welfare) under uncertainty. By anticipating the PC’s incentives, a welfare-maximizing transmission system operator (TSO) shapes the network to align public and private objectives. Via an option-based approach, we first quantify welfare losses from the PC’s and TSO’s conflicting objectives. We show that by anticipating the optimal timing and capacity decisions of the profit-maximizing PC, the TSO is able to reduce, though not eliminate, welfare loss. Next, we exploit the dependence of the PC’s capacity on the TSO’s infrastructure design to devise a proactive transmission-investment strategy. Hence, we mitigate welfare losses arising from misaligned incentives even in relatively uncertain markets.Peer reviewe

Optimal harvesting of farmed salmon during harmful algal blooms

This paper studies the optimal harvesting decisions of a salmon farmer that faces the risk of harmful algal bloom as well as market uncertainty. The salmon farmer seeks to maximize the financial value of the fish farm by determining the optimal course of actions during the algal bloom, and the optimal time to harvest after the bloom. Specifically, we compare the options to perform an early harvest and to wait in order to learn about the true algal risk. We extend this framework by taking into account the option to move the salmon to an algal free location. To illustrate the results and investigate the robustness of our model, we present two case studies with realistic industry parameters from Norway and Chile. We find that there is a significant value associated with the ability of salmon farmers to actively learn about the true risk of losing the biomass. This value is strongly affected by the availability of frequent and reliable information about the algal risk emphasizing the importance of communication between industry actors, as well as facilitation of effective information flow by policy makers and research organizations

Discounted optimal stopping problems for maxima of geometric Brownian motions with switching payoffs

We present closed-form solutions to some discounted optimal stopping problems for the running maximum of a geometric Brownian motion with payoffs switching according to the dynamics of a continuous-time Markov chain with two states. The proof is based on the reduction of the original problems to the equivalent free-boundary problems and the solution of the latter problems by means of the smooth-fit and normal-reflection conditions. We show that the optimal stopping boundaries are determined as the maximal solutions of the associated two-dimensional systems of first-order nonlinear ordinary differential equations. The obtained results are related to the valuation of real switching lookback options with fixed and floating sunk costs in the Black–Merton–Scholes model