Michail Chronopoulos

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.

The Value of Capacity Sizing Under Risk Aversion and Operational Flexibility

Risk aversion typically erodes the value of an investment opportunity, often increasing the incentive to delay investment. Although this may be true when the decision maker has discretion only over the timing of investment, any additional discretion over the capacity of a project may lead to different results. In this paper, we extend the traditional real options approach by allowing for discretion over capacity while incorporating risk aversion and operational flexibility in the form of suspension and resumption options. In contrast to a project without scalable capacity, we find that increased risk aversion may actually facilitate investment because it decreases the optimal capacity of the project. Finally, we illustrate how the relative loss in the value of the investment opportunity due to an incorrect capacity choice may become less pronounced with increasing risk aversion and uncertainty.

When is it Better to Wait for a New Version? Optimal Replacement of an Emerging Technology under Uncertainty

Firms that use an emerging technology often face uncertainty in both the arrival of new versions and the revenue that may be earned from their deployment. Via a sequential decision-making framework, we determine the value of the investment opportunity and the optimal replacement rule under three different strategies: compulsive, laggard, and leapfrog. In the first one, a firm invests sequentially in every version that becomes available, whereas in the second and third ones, it first waits for a new version to arrive and then either invests in the older or the newer version, respectively. We show that, under a compulsive strategy, technological uncertainty has a non-monotonic impact on the optimal investment decision. In fact, uncertainty regarding the availability of future versions may actually hasten investment. By comparing the relative values of the three strategies, we find that, under a low output price the compulsive strategy always dominates, whereas, at a high output price, the incentive to wait for a new version and adopt either a leapfrog or a laggard strategy increases as the rate of innovation increases. By contrast, high price uncertainty mitigates this effect, thereby increasing the relative attraction of a compulsive strategy.

Optimal Regime Switching under Risk Aversion and Uncertainty

Technology adoption is key for corporate strategy, often determining the success or failure of a company as a whole. However, risk aversion often raises the reluctance to make a timely technology switch, particularly when this entails the abandonment of an existing market regime and entry in a new one. Consequently, which strategy is most suitable and the optimal timing of regime switch depends not only on market factors, such as the definition of the market regimes, as well as economic and technological uncertainty, but also on attitudes towards risk. Therefore, we develop a utility-based, regime-switching framework for evaluating different technology-adoption strategies under price and technological uncertainty. We assume that a decisionmaker may invest in each technology that becomes available (compulsive) or delay investment until a new technology arrives and then invest in either the older (laggard) or the newer technology (leapfrog). Our results indicate that, if market regimes are asymmetric, then greater risk aversion and price uncertainty in a new regime may accelerate regime switching. In addition, the feasibility of a laggard strategy decreases (increases) as price uncertainty in an existing (new) regime increases. Finally, although risk aversion typically favours a compulsive and a laggard strategy, a leapfrog strategy may be feasible under risk aversion provided that the output price and the rate of innovation are sufficiently high.

Stepwise Investment and Capacity Sizing Under Uncertainty

The relationship between uncertainty and managerial flexibility is particularly crucial in addressing capital projects. We consider a firm that can invest in a project in either a single (lumpy investment) or multiple stages (stepwise investment) under price uncertainty and has discretion over not only the time of investment but also the size of the project. We confirm that if the capacity of a project is fixed and the investment premium associated with stepwise investment is positive, then lumpy investment becomes more valuable than a stepwise investment strategy under high price uncertainty. By contrast, if a firm has discretion over capacity, then we show that the stepwise investment strategy always dominates that of lumpy investment. In addition, we show that the total amount of installed capacity under a stepwise investment strategy is always greater than that under lumpy investment.

Systematic Analysis of the Evolution of Electricity and Carbon Markets Under Deep Decarbonisation

The decarbonisation of electricity generation presents policy-makers in many countries with the delicate task of balancing initiatives for technological change whilst maintaining a commitment to market liberalisation. Despite the theoretical attractions, it has become debatable whether carbon markets by themselves can offer a complete solution. We address this through a modelling framework, stylised for the GB power market within the EU ETS, which includes three distinct components: (a) a long-term least-cost capacity planning model, similar in functionality to many used in policy analysis, but innovative in providing the endogenous calculation of carbon prices; (b) a short-term price risk model producing hourly dispatch and pricing outputs, which are used to test the annual financial performance risks implied by the longer-term investments; (c) an agent-based model which uses a computational learning algorithm to derive pricing behaviour in imperfect markets. The results indicate that the risk/return profile of electricity markets deteriorates substantially as a result of decarbonisation, reducing the propensity of companies to invest in the absence of increased government support. Markets may adjust, if allowed, by deferring investment until conditions improve, or by consolidating to increase market power, or by operating in a tighter market with reduced spare capacity. To the extent that each of these ‘market-led’ solutions may be politically unpalatable, policy design will need to sustain a delicate regulatory regime, moderating the increasing market power of companies whilst maintaining low-carbon subsidies for longer than expected.

Real options valuation applied to transmission expansion planning

Transmission expansion planning (TEP) is a complex problem where building a new line involves a long permitting process of around 10 years. Therefore, transmission expansion must anticipate the evolution of uncertainties, particularly those derived from changes in the capacity and location of new generating facilities. As it is not possible to request permits for all possible lines, priorities must be established. We develop a formulation to use real options valuation to evaluate the potential benefit of candidate lines and thereby identify priority projects. We present a feasible representation of optionality in TEP projects and propose a tractable evaluation of option value. The proposed technique identifies the candidate transmission lines with the highest potential, as well as their main value drivers. This is implemented in a realistic large-scale case study based on the Spanish system.

Strategic Technology Switching under Risk Aversion and Uncertainty

Sequential investment opportunities or the presence of a rival typically hasten investment under risk neutrality. By contrast, greater price uncertainty or risk aversion increase the incentive to postpone investment in the absence of competition. We analyse how price and technological uncertainty, reflected in the random arrival of innovations, interact with attitudes towards risk to impact both the optimal technology adoption strategy and the optimal investment policy within each strategy, under a proprietary and a non-proprietary duopoly. Results indicate that technological uncertainty increases the followers investment incentive and delays the entry of the non-proprietary leader, yet it does not affect the proprietary leaders optimal investment policy. Additionally, we show that technological uncertainty decreases the relative loss in the value of the leader due to the followers entry, while the corresponding impact of risk aversion is ambiguous. Interestingly, we also find that a higher first-mover advantage with respect to a new technology does not affect the leaders entry, and that technological uncertainty may turn a pre-emption game into a war of attrition, where the second-mover gets the higher payoff.