Real options have been widely applied to analyze investment planning and asset valuation under uncertainty in many industries, especially energy markets. Because of their close analogy to financial options, real options can be valued using the classical financial option pricing theories and their extensions. However, as real options valuation often involves complex payoff structures and operational constraints of the underlying real assets or projects, accurate and flexible methods for solving the valuation problem are essential. This thesis investigates three different approaches to real options valuation and contributes to aspects of modeling realism and computational efficiency. The contributions are illustrated through two important applications of real options in energy markets: natural gas storage and power plant valuation. Because spread options are commonly used in basic real options valuation techniques, the first part of the thesis addresses the problems of spread option pricing and hedging. We develop a new closed-form approximation method for pricing two-asset spread options. Numerical analysis shows that our method is more accurate than existing analytical approximations. Our method is also extremely fast, with computing time more than two orders of magnitude shorter than one-dimensional numerical integration. Closed-form approximations for the Greeks of spread options are also developed. In addition, we analyze the price sensitivities of spread options and provide lower and upper bounds for digital spread options. We then further generalize the above results to multi-asset spread options on an arbitrary number of assets. We provide two new closed-form approximation methods for pricing spread options on a basket of risky assets: the extended Kirk approximation and the second-order boundary approximation. Numerical analysis shows that both methods are extremely fast and accurate, with the latter method more accurate than the former. Closed-form approximations for important Greeks are also derived. Because our approximation methods enable the accurate pricing of a bulk volume of spread options on two or more assets in real time, it offers traders a potential edge in a dynamic market environment. In the third part of this thesis, we propose a market-based valuation framework for valuing natural gas storage facility with realistic operational characteristics. The operational process is modeled as a multi-stage stochastic optimization problem. We develop a Gaussian quadrature scheme to solve for the dynamically optimal spot trading strategy and show that the computational efficiency of this method exceeds existing approaches in about two orders of magnitude. Furthermore, with this flexible quadrature scheme, we propose to value a gas storage based on a novel hybrid trading strategy that successfully incorporates both spot and forward trading, thus improving the storage valuation significantly by accounting for both the inter-month and intra-month operational flexibilities and price volatility. In the fourth part of this work, we develop a continuous-time formulation for power plant valuation in infinite time horizon. We propose a real-option-based model for a power plant to account for the embedded operational flexibility. This model incorporates start-up and shut-down costs as two major operational constraints. Under this continuous valuation model, spark spread is modeled directly as a continuous stochastic process to take account of the long term co-integration relationship between electricity and fuel prices. Instead of discretizing the stochastic process, we preserve continuity of the stochastic spark spread process and work directly with the value function. Closed-form of value function under threshold policy is obtained. The corresponding optimal operational strategy can then be solved. The advantage of this approach is that it reduces computational complexity while incorporates major operation characteristics. It enables fast computation of a power plant value that approximates the real market value and sensitivity analysis of the asset value with respect to the cost parameters of a power plant and the distribution parameters of spark spread.

Thesis (Ph. D.)--University of Oregon, 2007. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 109-114). Also available for download via the World Wide Web; free to University of Oregon users.

The feasibility of capital projects in an uncertain world can be determined in several ways. One of these methods is real options valuation which arose from financial option valuation theory. On the other hand fuzzy set theory was developed as a mathematical framework to capture uncertainty in project management. The valuation of real options using fuzzy numbers represents an important refinement to determining capital projects' feasibility using the real options approach. The aim of this study is to determine whether the deferral of the decommissioning time (by a decade) of an electricity-generating nuclear plant in South Africa increases decommissioning costs. Using the fuzzy binomial approach, decommissioning costs increase when decommissioning is postponed by a decade whereas use of the fuzzy Black-Scholes approach yields the opposite result. A python code was developed to assist in the computation of fuzzy binomial trees required in our study and the results of the program are incorporated in this thesis. / KMBT_363 / Adobe Acrobat 9.54 Paper Capture Plug-in

This study develops a real options model of agbiotechnology and is applied to three genetically modified (GM) traits. Each trait is evaluated as growth options where technical or marketing milestones must be completed before management can exercise the option to invest further in trait development. The real options values are evaluated by employing a binomial tree which is simulated using distributions for random elements within stages of the growth option. Mean option values were negative for the discovery stage for fusarium-resistant wheat and for all but the regulatory submission stage for Roundup Ready wheat. The length of the regulatory submission stage had the greatest negative impact on the value of the option while the ability of the firm to maximize technology-use-fees had the greatest positive impact. Additionally, traits adapted to crops with larger potential market size are more likely to be in the money than traits developed for smaller market segments.

Thesis (MBA)--Stellenbosch University, 2005. / ENGLISH ABSTRACT: This study project focuses on the use of real options valuation in a tactical financing setting. The objective is to identify real option values in financial restructuring situations. These options are generated by the use of hybrid financial instruments such as warrants, preferred stocks and convertibles. In the analysis, it will be demonstrated that the binomial approach, a method commonly used in real options analysis, can be applied to draw a monetary value from specific financial transactions (e.g., leverage buyouts). When used optimally, the binomial approach provides a forceful insight into the dynamics of the transaction. The study recognises the possible impact of capital structure decisions in the analysis, but understates it to avoid complexity. The real options perspective encourages a conscious search for monetary benefits and thus improves the decision-making of managers involved in financial restructuring operations. / AFRIKAANSE OPSOMMING: Hierde werkstuk fokus op die gebruik van rieëIe opsie teorie om taktiese finansieringsbesluitneming te evalueer. Opsies word gegenereer deur die gebruik van hibridiese finansiele instrumente soos bestuursopsie-orders, voorkeuraandele en omskepbare instrumente. In hierdie studie word 'n oorsig oor die teorie soos dit in literatuur verskyn gegee, asook voorbeelde van finansiele herstrukturering om die waarde van die toepassing daarvan te illustreer. In hierdie studie word erkenning gegee aan die moontlike impak wat kapitaalstruktuur-besluitneming op die ontleding mag hê. Die impak hiervan word egter weens die kompleksiteit daarvan ignoreer. Nieteenstaande hierdie beperking, word besluitneming rakende finansiele herstrukturering verbeter deur die perspektief wat deur die rieëIe opsie-benadering verkry word, soos in hierdie werkstuk uitgewys word.

The net present value (NPV) approach has been widely accepted by corporate practitioners and academics as the principle tool for evaluating the feasibility of corporate financial investment opportunities. It conceptually provides an estimate in present value terms of a proposed investment's incremental contribution to the firm, enabling the company to pursue its goal of value maximization with more assurance. NPV uses a discount rate that in theory captures market risks. In the stable growth or mature industries, NPV works well. However, in high investment/high risk-return (HI/HRR) industries, where the investment environment is often profiled as highly uncertain with high returns, NPV is insufficient to reflect the multidimensional risks, hence unable to capture the extensive investment returns that may consist of non-financial values. This dissertation applies the real option (RO) valuation methodology, supplementing the NPV method to evaluate the return of the sports retail industry (SRI) flagship stores investments. This study further demonstrates that there are strategic values captured by the RO valuation method, complementing the financial values attained by the NPV. To test this assertion, we use case methodology to analyze four flagship investment activities (proprietary business data are concealed). These investments represent various investment options, including growth, expansion, staging, and delay. The cases include projections made prior to the investment, the retrospective application of RO to estimate strategic value, and the actual returns from these investments. Findings demonstrate convincingly RO methodology can and should be usefully applied to supplement the NPV method in HI/HRR industries, and SRI in particular.

Thesis (MBA)--Stellenbosch University, 2005. / ENGLISH ABSTRACT: The oil industry is under pressure to select refinery projects that will provide higher and more predictable returns. In the past Discounted Cash Flow (DCF) techniques have been used to choose between refinery project alternatives. One of the problems with DCF techniques is that they ignore management flexibility when evaluating projects that contain embedded options. Real Option Valuation (ROV) is an approach that takes management flexibility into account and places a value on this flexibility. ROV has been used extensively by the oil industry for the evaluation of oil and gas reserves. The aim of this study is to determine the extent to which the use of ROV will improve the decision making process when evaluating a refining project containing embedded options as well as to determine the most appropriate option valuation method for refining projects. This was done by evaluating a refining project using both a probabilistic DCF approach and the various option pricing models and comparing the results. It was concluded that ROV will improve the decision making process when evaluating refining projects containing embedded options. The most appropriate option pricing method for refining projects was found to be the simulation approach since simulation is already being used by refineries to perform probabilistic DCF analysis. It is not recommended that ROV should be blindly applied to all refining projects containing embedded options. The use of ROV should be limited to larger refining projects for which probabilistic cash flows have been developed and the extent of the ROV analysis required should be determined by a careful review of the net present value (NPV) cumulative probability curves. / AFRIKAANSE OPSOMMING: Die olie industrie is onder druk geplaas om projekte te kies met 'n hoër opbrengs op kapitaal en 'n opbrengs wat meer voorspelbaar is. In die verlede is slegs die Verdiskonteerde Kontant Vloei (VKV) metode gebruik om projekte te selekteer vir die raffinadery. Een van die onderliggende tekortkominge met die gebruik van die VKV metode is dat verskillende bestuursopsies in terme van alternatiewe met ingeboude opsies, nie voldoende ondersoek word nie. Reële Opsie Waardasie (ROW) is 'n metode wat bestuursopsies in ag neem deur 'n waarde te plaas op elke beskikbare bestuursopsie. ROW het wye toepassings in die olie industrie vir die evaluasie van gas en olie reserves. Die doel van hierdie studie is om te bepaal tot watter mate die gebruik van ROW die besluitnemingsproses sal verbeter in terme van die evaluasie van projekte met ingeboude opsies vir raffinaderye en watter opsiewaardasie metode die mees geskikte is vir sulke projekte. 'n Raffinadery projek is evalueer deur beide KV en verskeie opsie-prysbepalingsmetodes te gebruik en die resultate is vergelyk. Die resultate van die studie het bewys dat die ROW metode die besluitnemingsproses verbeter. Die studie het gewys dat die mees geskikte opsie-waardasie metode vir projekte in the raffinadery die simulasie benadering is omdat simulasie alreeds vir probalisties VKV ontleding gebruik word. 'n Verdere aanbeveling is dat die ROW metode nie blindelings gevolg moet word vir alle projekte met ingeboude opsies nie. Die gebruik van ROW moet beperk word tot groter projekte waarvoor probabilistiese kontantvloei alreeds ontwikkel is. Die mate van ROW ontleding moet bepaal word deur 'n noukeurige ondersoek te doen van die kumulatiewe netto huidige waarde-waarskynlikheidskurwe.

Originally presented as the author's doctoral thesis to the European Business School, Oestrich-Winkel. / Includes bibliographical reference (p. [345]-353) and index.

With many genetic traits discovered and many more in progress, it is imperative to the industry that firms (biotechnology companies) decide on the trait valuation and pricing. This includes more than one trait (also referred to as stacked traits) in a single variety of crop; the risk and uncertainty of expected returns associated with the development and release of a variety increases even more in case of stacked traits. The purpose of this thesis is to develop a model that can be used for the valuing and pricing of genetically modified (GM) traits that are random, sporadic, and non-persistent (e.g. drought tolerance, heat/cold stress) using the real option approach. The efficiency gain in case of occurrence of random event and expression of GM traits will be measured and used as a decision factor in determining the value of GM trait(s) at different phases of development. Risk premiums representing the value of GM trait to growers is calculated across risk averse attitudes. The return to labor and management (RTLM) provided by a GM trait is used to calculate the risk premiums when variation in parameters is allowed to be same as that reflected in historical data and gains from GM traits are realized. Monte Carlo simulation and stochastic efficiency with respect to a function (SERF) are used to estimate the certainty equivalents that decision makers would place on a risky alternative relative to a no risk investment. Certainty equivalents are estimated across a range of risk aversion coefficients and used to rank alternatives and determine where preferences among alternatives change while estimating risk premiums for the base case (no trait), drought tolerance, cold tolerance, NUB, and All traits (all traits combined into one as a stacked trait). Premiums provide perspective on the magnitude of differences in relative preferences among choices. The range of ARAC utilized was from 0.00 to 0.15 for all three crops. The risk premiums are treated as a potential source of revenue in the model as a technology fee charged by a biotech company. This thesis uses the Real Option methodology to evaluate GM traits as Option values at various stages of development. This approach helps managers decide the best possible option in making a certain decision today. It is also helpful in comparing different pathways (series of decisions) and thus better exploits the potential cash return in the future from investments made today (Figure D.1, Figure D.2). Three possible options to "continue", "wait", and "abandon" were modeled in this thesis. Such modeling determines the possible option values of GM traits at different stages of development depending on the kind of choices made at different points of time. This thesis shows that various GM traits that are out-of-money (OTM) at initial stages have increased probability of being in-the-money (ITM) at later stages of development. Sensitivities show that a share of potential technology fees and acreage of GM crops play a significant role in option values being ITM. Stacked traits provide a better chance of being ITM, thus the option to continue will be exercised by management. The option to wait causes reduction in option value. Among individual traits, drought tolerance has the greatest maximum option value in most cases. Therefore, if management has to choose the development of only one GM trait, it is most likely to choose to invest in the development of drought tolerance.

Thesis (MComm (Business Management))--University of Stellenbosch, 2006. / For the last 40 years, academics advocated the use of the traditional Discounted Cash Flow (DCF) techniques but these suggestions were ignored by practitioners for a long time. The Net Present Value (NPV), Internal Rate of Return (IRR) and Present Value Payback Period (PVPP) are now some of the more widely used traditional DCF-based techniques, especially among large firms. However, academics are now criticising these techniques as they are based on rigid assumptions that ignore the management of flexibility in projects. The Real Option Valuation (ROV) is suggested as an alternative technique because it implicitly incorporates this flexibility in project valuation. With ROV, opportunities in projects are treated as real options and are therefore valued using financial option principles. Real options give the firm the opportunity to act on an investment project (invest, abandon, rescale) at a later date, when more information is available. As with the traditional DCF-based techniques in the past, few firms seem to have adopted ROV despite academics’ recommendations. This study is thus aimed at determining through a survey, whether the largest firms in South Africa, specifically those included in the JSE/FTSE Top 40 index, are using ROV. Based on the results of the survey, it is concluded that firms generally do not use ROV as only nine percent of the respondents were found to be using it. This is largely attributed to managers being unaware of the technique, and to some extent, to the technique’s complexity. On the other hand, managers were generally found to recognise the flexibility despite not using ROV, although it was not confirmed whether they quantify this flexibility.