Optimal Investment in Research and Development Under Uncertainty

This paper explores the optimal expenditure rate that a firm should employ to develop a new technology and pursue the registration of the related patent. Our model takes into account an economic environment with indus-trial competition among firms operating in the same sector and in presence of uncertainty in knowledge accumulation. We develop a stochastic optimal control problem with random horizon, and solve it theoretically by adopting a dynamic programming approach. An extensive numerical analysis suggests that the optimal expenditure rate is a decreasing function in time and its sen-sitivity to uncertainty depends on the stage of the race. The odds for the firm to preempt the rivals non-linearly depend on the degree of competition in the market

Investing in Time-to-Build Projects With Uncertain Revenues and Costs: A Real Options Approach

Lagging public-sector investment in infrastructure and the deregulation of many industries mean that the private sector has to make decisions under multiple sources of uncertainty. We analyze such investment decisions by accounting for both multiple sources of uncertainty and the time-to-build aspect. The latter feature arises in the energy and transportation sectors, because investors can decide the rate at which the project is completed. Furthermore, two explicit sources of uncertainty represent the discounted cash inflows and outflows of the completed project. We use a finite-difference scheme to solve numerically the option value and the optimal investment threshold. Somewhat counterintuitively, with a relatively long time to build, a reduction in the growth rate of the discounted operating cost may actually lower the investment threshold. This is contrary to the outcome when the stepwise aspect is ignored in a model with uncertain price and cost. Hence, research and development efforts to enhance emerging technologies may be more relevant for infrastructure projects with long lead times

Computational Support for Technology- Investment Decisions

Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format

Optimal Decision-Making under Uncertainty - Application to Power Transmission Investments

Economists define investment as the act of incurring immediate costs with the expectation of future returns. An investment project, as every asset has a value. For successfully investing in and managing these assets is crucial not only recognizing what the value is but also the sources of this value. Most investment decisions share three characteristics in different degrees. First, investments are partially or totally irreversible. Roughly speaking, the initial investment cost is at least partially sunk; i.e. it is impossible to recover all the expenditures if the decision-maker changes his mind. Second, there is uncertainty in the revenues from the investment, and therefore, risk associated with this. Third, all decision-making has some leeway about the timing of the investment. It is possible to defer the decision making to get more information about the future. These three features interact to determine the optimal decisions of investors on a given investment project. Transmission utilities are faced with investment projects, which hold these three characteristics: irreversibility, uncertainty and the choice of timing. In this context, an efficient decision making process is, therefore, based on managing the uncertainties and understanding the relationships between risks and opportunities in order to achieve a well-timed investment execution. Therefore, strategic flexibility for seizing opportunities and cutting losses contingent upon the market evolution is of huge value. Strategic flexibility is a risk management method that is gaining ongoing research attention as it enables properly managing major uncertainties, which are unsolved at the time of making decisions. Hence, valuing added flexibility in transmission investment portfolios, for instance, by investing in power electronic-based controller meanwhile transmission line projects are deferred, is necessary to make optimal network upgrading. Nevertheless, expressing the value of flexibility in economic terms is not a trivial task and requires new, sophisticated valuing tools, since the traditional investment theory has not recognized the important implications of the interaction between the three aforementioned investment features. Any attempt to quantify investment flexibility almost naturally leads to the concept of Real Options (RO). The RO technique provides a well-founded framework –based on the theory of financial options, and consequently, stochastic dynamic programming- to assess strategic investments under uncertainty. In the first RO applications, valuation was normally confined to the investment options that can be easily assimilated to financial options, for which solutions are well-known and readily available. Nevertheless, an investor confront with a diverse set of opportunities. From this point of view, investment projects can be seen as a portfolio of options, where its value is driven by several stochastic variables. The introduction of multiple interacting options into real options models highly increases the problem complexity, making traditional numerical approaches impracticable. However in the recent years, simulation procedures for solving multiple American options have been successfully proposed. One of the most promising approaches is the Least Square Monte Carlo (LSM) method proposed by Longstaff and Schwartz in 2001. LSM method is based on stochastic chronological simulation and uses least squares linear regression to determine the optimal stopping time (optimal path) in the decision making process. This chapter lays out a general background about key concepts -uncertainty and risk- and the most usual risk management techniques in transmission investment are provided. Then, the concept of strategic flexibility is introduced in order to set its ability for dealing with the uncertainties involved in the investment problem. In addition, new criteria and advantages of ROV approach compared with classical probabilistic choice are presented, by exposing a LSM-based method for decomposing and evaluating the complex real option problem involved in flexible transmission investments under uncertainties. The proposed methodology is applied in a study case which evaluates an interconnection reinforcement on the European interconnected power system, by showing how the valuation of flexibility is a key task for making efficient and well-timed investments in the transmission network. The impact of two network upgrades on the system-wide welfare is analyzed. These upgrades are the development of a new interconnected line and the installation of a power electronic-based controller. Both upgrades represent measures to strengthen the German-Dutch interconnections due to the fact that these are among the most important corridors within the Central Western European (CWE) region. Hence, an interconnection project, which is currently under study, is compared to flexible investment in order to shed some light on the influence of the strategic flexibility on the optimal decision-making process. The research is focused on assessing the impact of different wind power in-feed scenarios in detail as well as the uncertainty of the demand growth, generation cost evolution and the installed wind capacity on the decision-making process. The presented approach might serve as a basis for a decision-making tool for regulatory agencies in order to quantify the necessity for network upgrades.Fil: Blanco, Gerardo. Universidad Nacional de Asunción; ParaguayFil: Olsina, Fernando Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentin

Wind farm layout optimization under uncertainty with landowners\u27 financial and noise concerns

Current wind farm layout research focuses on advancing optimization methods. The research includes the assumption that a continuous piece of land is readily available. In reality, landowners\u27 decisions and concerns play a crucial role in wind projects, and some land parcels are more important to project success than others. During early farm development stages, developers must model many important factors, such as wind resource, land availability, topography, and etc. These factors are associated with great uncertainties. In this dissertation, three system-level optimization models, which include landowners\u27 concerns and optimization-under-uncertainty formulation, are developed progressively. System Model 1 applies a realistic cost model, including landowner remittances, to determine optimal turbine placement under three landowner participation scenarios and two land-plot shapes. The formulation represents landowner participation scenarios as a binary string variable, along with number of turbines. The optimal Cost-of-Energy results are compared to actual Cost-of-Energy data and found to be realistic. System Model 2 advances Model 1 with an optimization-under-uncertainty formulation. A farm layout is optimized under multiple sources of uncertainty including wind shear and farm cost. Landowner participation is represented as uncertain with a novel model of willingness-to-accept compensation. System Model 3 advances Model 2 by modeling landowners\u27 noise concerns and associated compensation. This uncertain model, together with a noise propagation model is then incorporated into the optimization-under-uncertainty system model. Including uncertain parameters and compensation models leads to a total farm cost estimate that is more accurate than the most current publicly-available model used by the National Renewable Energy Laboratory, which requires the addition of an arbitrary term to match industry-reported Cost-of-Energy data. Additionally, the framework presented here can help developers identify land plots that are worth the extra investment during early farm development. It can provide developers with a robust farm design that is not only profitable but also has minimal noise disturbance for landowners. It can also give landowners an idea of where turbines are likely to be placed, and the likely auditory impacts. This improved transparency-of-information can potentially facilitate the negotiation process between developers and landowners during early farm planning and ultimately improve the success rate of projects

Measuring the capacity of a port system : a case study on a Southeast Asian port

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 172-177).As economies develop and trade routes change, investment in port infrastructure is essential to maintain the necessary capacity for an efficiently functioning port system and to meet expected demand for all types of cargo. However, these largescale, expensive investments in long-term infrastructure assets must be made despite a variety of future uncertainties that may potentially influence a port's performance. By using a Southeast Asian multi-purpose port as a case study, this thesis paper enhances the investment decision-making process for port infrastructure through the successful application and modification of two existing methodologies and the development of both an investment tool and a framework for selecting an optimal investment strategy to address capacity constraints within a port system. Applied at the case study port, the research evaluates a modification of an existing methodology for the measurement of port capacity, developed by Lagoudis and Rice, to identify bottlenecks within the port system. The research then examines a modification of an existing methodology, developed by de Neufville and Scholtes, for the evaluation of potential investment strategies under uncertainty. A simulation screening model is developed to forecast expected profitability under uncertainty for potential investment strategies, including strategies with flexible options, and to determine the optimal strategy. The thesis concludes with the presentation of a decision-making process for port infrastructure investment and recommended refinements to the existing methodologies.by Jason Bryan Salminen.M.Eng.in Logistic

Stepwise Green Investment under Policy Uncertainty

We analyse how market price and policy uncertainty, in the form of random provision or retraction of a subsidy, interact to affect the optimal time of investment and the size of a renewable energy (RE) project that can be completed in either a single (lumpy investment) or multiple stages (stepwise investment). The subsidy takes the form of a fixed premium on top of the electricity price, and, therefore, investment is subject to electricity price uncertainty. We show that the risk of a permanent retraction (provision) of a subsidy increases (decreases) the incentive to invest, yet lowers (raises) the amount of installed capacity, and that this result is more pronounced as the size of the subsidy increases. Additionally, we show that increasing the number of policy interventions lowers the expected value of a subsidy and the size of the project. Furthermore, we illustrate that, although an increase in the size of a subsidy lowers the relative value of the stepwise investment strategy, the expected value of a lumpy investment strategy is still lower than that of stepwise investment

The timing of capacity expansion investments in oligopoly under demand uncertainty

Since a flexibility value emerges in waiting to expand capacity, the impact of demand uncertainty in an oligopolistic industry leads to capacity expansion timing. The creation of growth opportunities is then the outcome of expanding capacity at optimal times. However, in our model different capacity size competitors interact not affecting each others, because assessing the impact of demand uncertainty on capacity expansion projects takes them to set up independently their optimal capacity expansion timing schedules. In equilibrium no firm expands capacity more often than any other. Under demand uncertainty simultaneity in capacity expansions is the only possible Markov Perfect Equilibrium

High speed rail transport valuation

The present paper investigates the optimal timing of investment for a high speed rail (HSR) project, in an uncertain environment, using a real options analysis (ROA) framework. It develops a continuous time framework with stochastic demand that allows for the determination of the optimal timing of investment and the value of the option to defer in the overall valuation of the project. The modelling approach used is based on the differential utility provided to railway users by the HSR service.info:eu-repo/semantics/publishedVersio