Yes / Using a three-factor stochastic real option model framework, this paper examines the effects of abandonment on the investment decision. Abandonment is classified according to whether the opportunity arises for an active operating asset post-investment, or for holding the project opportunity pre-investment. Separate analytical models are developed for the alternative forms of abandonment optionality. Numerical sensitivity analysis shows that the presence of a post-investment abandonment opportunity makes the investment opportunity appear to be more attractive because of the abandonment option value, but not by a considerable amount. Also, in contrast to the standard real option finding, an abandonment value volatility increase produces a project value threshold fall owing to the increase in the abandonment option value.

Esta dissertação tratará do tema da geração de energia elétrica no Brasil e a análise financeira de projetos. Mais especificamente será abordada a energia eólica a qual é o aproveitamento dos ventos para a geração de energia. Nos últimos 10 anos, a capacidade instalada mundial de energia eólica cresceu em média 28% ao ano sendo que na Europa 3% da energia consumida já tem origem nos ventos. No Brasil, esse tipo de aproveitamento atinge apenas 0,3% de participação no fornecimento de energia elétrica do país apesar de excelentes condições naturais. Como objetivo geral, este estudo analisará a viabilidade financeira de um projeto de energia eólica no Estado brasileiro do Ceará. A metodologia utilizada será o estudo de caso, uma empresa geradora de energia eólica, sendo avaliada, financeiramente, pela teoria das opções reais. A TOR surge como alternativa aos métodos tradicionais de análise de investimentos e tenta superar as suas limitações incluindo a questão da incerteza. Os resultados obtidos comprovam a importância, tanto da energia eólica para a matriz energética brasileira, quanto da TOR como forma de precificar oportunidades / riscos embutidos em projetos. / This thesis will broach the generation of electricity in Brazil using wind power and project valuation analysis. During the last 10 years, the worldwide wind power installed capacity grew 28% on average per year and in Europe 3% of the energy consumption comes from this source of energy. In Brazil, this type of energy reaches only 0.3% of national energy supply besides the fact that the Country has excellent natural resources for this type of generation. The objective of this study is to make the valuation analysis of a wind energy project in the Brazilian State of Ceará. The research methodology used in this thesis will be the case study of a wind energy generation plant using the real option analysis. The ROA comes as an alternative method for the traditional valuation analysis and tries to overcome its limitations adding uncertainty. The result of this study confirms the importance not only of wind power to the Brazilian energy matrix but also the ROA as an alternative method to calculate risks and opportunities included in projects.

Esta dissertação tratará do tema da geração de energia elétrica no Brasil e a análise financeira de projetos. Mais especificamente será abordada a energia eólica a qual é o aproveitamento dos ventos para a geração de energia. Nos últimos 10 anos, a capacidade instalada mundial de energia eólica cresceu em média 28% ao ano sendo que na Europa 3% da energia consumida já tem origem nos ventos. No Brasil, esse tipo de aproveitamento atinge apenas 0,3% de participação no fornecimento de energia elétrica do país apesar de excelentes condições naturais. Como objetivo geral, este estudo analisará a viabilidade financeira de um projeto de energia eólica no Estado brasileiro do Ceará. A metodologia utilizada será o estudo de caso, uma empresa geradora de energia eólica, sendo avaliada, financeiramente, pela teoria das opções reais. A TOR surge como alternativa aos métodos tradicionais de análise de investimentos e tenta superar as suas limitações incluindo a questão da incerteza. Os resultados obtidos comprovam a importância, tanto da energia eólica para a matriz energética brasileira, quanto da TOR como forma de precificar oportunidades / riscos embutidos em projetos. / This thesis will broach the generation of electricity in Brazil using wind power and project valuation analysis. During the last 10 years, the worldwide wind power installed capacity grew 28% on average per year and in Europe 3% of the energy consumption comes from this source of energy. In Brazil, this type of energy reaches only 0.3% of national energy supply besides the fact that the Country has excellent natural resources for this type of generation. The objective of this study is to make the valuation analysis of a wind energy project in the Brazilian State of Ceará. The research methodology used in this thesis will be the case study of a wind energy generation plant using the real option analysis. The ROA comes as an alternative method for the traditional valuation analysis and tries to overcome its limitations adding uncertainty. The result of this study confirms the importance not only of wind power to the Brazilian energy matrix but also the ROA as an alternative method to calculate risks and opportunities included in projects.

Esta dissertação tratará do tema da geração de energia elétrica no Brasil e a análise financeira de projetos. Mais especificamente será abordada a energia eólica a qual é o aproveitamento dos ventos para a geração de energia. Nos últimos 10 anos, a capacidade instalada mundial de energia eólica cresceu em média 28% ao ano sendo que na Europa 3% da energia consumida já tem origem nos ventos. No Brasil, esse tipo de aproveitamento atinge apenas 0,3% de participação no fornecimento de energia elétrica do país apesar de excelentes condições naturais. Como objetivo geral, este estudo analisará a viabilidade financeira de um projeto de energia eólica no Estado brasileiro do Ceará. A metodologia utilizada será o estudo de caso, uma empresa geradora de energia eólica, sendo avaliada, financeiramente, pela teoria das opções reais. A TOR surge como alternativa aos métodos tradicionais de análise de investimentos e tenta superar as suas limitações incluindo a questão da incerteza. Os resultados obtidos comprovam a importância, tanto da energia eólica para a matriz energética brasileira, quanto da TOR como forma de precificar oportunidades / riscos embutidos em projetos. / This thesis will broach the generation of electricity in Brazil using wind power and project valuation analysis. During the last 10 years, the worldwide wind power installed capacity grew 28% on average per year and in Europe 3% of the energy consumption comes from this source of energy. In Brazil, this type of energy reaches only 0.3% of national energy supply besides the fact that the Country has excellent natural resources for this type of generation. The objective of this study is to make the valuation analysis of a wind energy project in the Brazilian State of Ceará. The research methodology used in this thesis will be the case study of a wind energy generation plant using the real option analysis. The ROA comes as an alternative method for the traditional valuation analysis and tries to overcome its limitations adding uncertainty. The result of this study confirms the importance not only of wind power to the Brazilian energy matrix but also the ROA as an alternative method to calculate risks and opportunities included in projects.

Includes abstract. / Includes bibliographical references (leaves 68-71). / Surveys of firms outside the property sector indicate the growth in the use of DCF methods such as the NPV and IRR methods to evaluate projects as compared to the use of such naïve methods as Payback and the Accounting rate of return. The growing convergence of theory and practice is indicated by the growing use of the NPV method. The objective of this study is to determine the capital budgeting methods used to evaluate real estate development projects and to compare the results of a survey with the results of other studies. Further, recent developments in capital budgeting theory, indicate that the investment valuation tools such as the Net Present Value (NPV), Internal Rate of Return (lRR), Payback Period (PP), and theAccounting Rate of Return (ARR) may fail to recognize flexibilities in real estate development projects. As a consequence, the discounted cash flow methods (DCF) may systematically undervalue strategic or large-scale real estate development projects. Two methods are introduced as an alternative to address the weaknesses of the DCF methods. Decision Tree Analysis (DTA) employs an approach to analyse flexibilities by creating a chain of possible options and allows alternative courses of action for management to adapt their initial strategies in order to capitalise on new opportunities or to minimise losses. Real Option Analysis (ROA) introduces the theory of valuing financial derivates, in particular call options, and allows the staging of the development. These instruments further introduce a risk management aspect, as call options have a limited down side and an unlimited upside. Each approach has advantages and shortcomings and should only be used in appropriate circumstances. DTA is suited for the analysis of the project specific risks. ROA on the other hand, is a superior tool when dealing with uncertainty. The thesis finds that that over 90% of all respondents are using a combination of NPV and IRR methods most often to evaluate development opportunities. Interestingly, 85% of all respondents are also using the payback period. Other methods used are the profitability index, residual value, free cash flow, economic value, and return on equity. Developers have adopted DCF methods such as NPV and IRR as the primary methods to evaluate projects rather than naïve methods such as Payback and ARR, although these latter methods remain in use. The use of decision tree analysis and real option analysis is very limited.

Yes / We provide a generalized analytical methodology for evaluating a real sequential investment opportunity, which does not rely on a multivariate distribution function, but which allows for stage-specific risks and drifts. This model may be a useful capital budgeting and valuation tool for exploration and development projects, where risks change over the stages. We construct a stage threshold pattern whereby the final stage threshold exceeds the early stage threshold due to drift differentials between the project values at the various stages, value volatility differences, and correlation differentials, implying a rich menu of parameter values that may be suitable for a variety of projects. Governments seeking to motivate early final stage investments might lower final stage project volatility or specify project value decline over time, unless prospective owners are willing to pay the real option value (ROV) for concessions. In contrast, concession owners, more interested in ROV than thresholds that motivate early investments, may welcome final stage value escalation, or guarantees that reduce the correlation between project value and construction cost.

The performance of a program can sometimes greatly improve if it was known in advance the features of the input the program is supposed to process, the actual operating parameters it is supposed to work with, or the specific environment it is to run on. However, this information is typically not available until too late in the program’s operation to take advantage of it. This is especially true for simulation algorithms, which are sensitive to this late-arriving information, and whose role in the solution of decision-making, inference and valuation problems is crucial. To overcome this limitation we need to provide the flexibility for a program to adapt its behaviour to late-arriving information once it becomes available. In this thesis, I study three adaptation mechanisms: run-time code generation, model-specific (quasi) Monte Carlo sampling and dynamic computation offloading, and evaluate their benefits on Monte Carlo algorithms. First, run-time code generation is studied in the context of Monte Carlo algorithms for time-series filtering in the form of the Input-Adaptive Kalman filter, a dynamically generated state estimator for non-linear, non-Gaussian dynamic systems. The second adaptation mechanism consists of the application of the functional-ANOVA decomposition to generate model-specific QMC-samplers which can then be used to improve Monte Carlo-based integration. The third adaptive mechanism treated here, dynamic computation offloading, is applied to wireless communication management, where network conditions are assessed via option valuation techniques to determine whether a program should offload computations or carry them out locally in order to achieve higher run-time (and correspondingly battery-usage) efficiency. This ability makes the program well suited for operation in mobile environments. At their core, all these applications carry out or make use of (quasi) Monte Carlo simulations on dynamic Bayesian networks (DBNs). The DBN formalism and its associated simulation-based algorithms are of great value in the solution to problems with a large uncertainty component. This characteristic makes adaptation techniques like those studied here likely to gain relevance in a world where computers are endowed with perception capabilities and are expected to deal with an ever-increasing stream of sensor and time-series data.

The performance of a program can sometimes greatly improve if it was known in advance the features of the input the program is supposed to process, the actual operating parameters it is supposed to work with, or the specific environment it is to run on. However, this information is typically not available until too late in the program’s operation to take advantage of it. This is especially true for simulation algorithms, which are sensitive to this late-arriving information, and whose role in the solution of decision-making, inference and valuation problems is crucial. To overcome this limitation we need to provide the flexibility for a program to adapt its behaviour to late-arriving information once it becomes available. In this thesis, I study three adaptation mechanisms: run-time code generation, model-specific (quasi) Monte Carlo sampling and dynamic computation offloading, and evaluate their benefits on Monte Carlo algorithms. First, run-time code generation is studied in the context of Monte Carlo algorithms for time-series filtering in the form of the Input-Adaptive Kalman filter, a dynamically generated state estimator for non-linear, non-Gaussian dynamic systems. The second adaptation mechanism consists of the application of the functional-ANOVA decomposition to generate model-specific QMC-samplers which can then be used to improve Monte Carlo-based integration. The third adaptive mechanism treated here, dynamic computation offloading, is applied to wireless communication management, where network conditions are assessed via option valuation techniques to determine whether a program should offload computations or carry them out locally in order to achieve higher run-time (and correspondingly battery-usage) efficiency. This ability makes the program well suited for operation in mobile environments. At their core, all these applications carry out or make use of (quasi) Monte Carlo simulations on dynamic Bayesian networks (DBNs). The DBN formalism and its associated simulation-based algorithms are of great value in the solution to problems with a large uncertainty component. This characteristic makes adaptation techniques like those studied here likely to gain relevance in a world where computers are endowed with perception capabilities and are expected to deal with an ever-increasing stream of sensor and time-series data.

國內外對BOT實質選擇權之研究，大多集中於BOT主體本身所隱含之各種選擇權價值，鮮少論及BOT附屬事業之選擇權價值。惟因交通運輸BOT主體之自償率往往偏低，故須以保證最小運量或特許經營附屬事業等方式，來吸引潛在投資者。附屬事業對整個BOT計畫價值的影響頗大，如何針對其選擇權之價值加以分析為本研究的主要課題。個案將以台灣南北高速鐵路計畫為例，對其附屬事業之放棄選擇權加以探討。 本研究將主要探討下列課題，並提出研究結果： 一、有限差分法及蒙地卡羅模擬法計算選擇權價值，其間之差異？本 文利用有限差分法及蒙地卡羅模擬法來各別求算BOT 附屬事業的 放棄選擇權價值，一來了解 BOT 附屬事業的放棄選擇權價的大 小，二來比較有限差分法及蒙地卡羅模擬法兩者間的差異。 二、BOT附屬事業的放棄選擇權是否受主體事業的經營績效所影響？ 三、BOT附屬事業是否須考量履約保證金之設計？ 四、BOT主體決定經營或放棄時，是否會影響其附屬事業之放棄選擇 權價值？ 本研究係以蒙地卡羅模擬法及有限差分法單獨估計台灣南北高速鐵路附屬事業之放棄選擇權價值，並建立運輸主體與附屬事業間價值的關聯，再以蒙地卡羅模擬法作更精確的估算。另使用單因子變異數分析及Tukey's Multiple Comparison Method之統計方法，驗證BOT主體與其附屬事業選擇權間之相關性，期能有助於日後BOT計畫之參與者評估及決策使用。 / The study of the Real Option Analysis (ROA) thesis of BOT generally focus is on the principal parts of the project only, rarely is considered the option of ancillary business of BOT. Because the self-liquidation-ratio of the transportation of BOT is low, it needs the government financial support (minimum traffic guarantee or revenue enhancements) to attract the interest of intended investors. The influence of the ancillary business of BOT is huge, so how to evaluate the option is the big issue of thesis. The case focus on the Taiwan High Speed Rail BOT project, and will study the option value of it’s ancillary business. Thesis will discuss the following issues, and develop the result of study. 1.The calculation difference between Monte Carlo Simulation & Finite Difference Method to work out option value, Thesis will use the Monte Carlo Simulation & Finite Difference Method to work out the abandon option value of ancillary business of BOT. To get the abandon option value and compare the calculation difference between Monte Carol Simulation & Finite Difference Method. 2.Will the abandon option value of ancillary business of BOT be influenced by the principal parts of the project？ 3.Is there a need to consider the performance security deposit of ancillary business of BOT？ 4.Will the decision of BOT impact the abandon option value of ancillary business or not？ The thesis will use the Monte Carol Simulation & Finite Difference Method to calculate the abandon option value of ancillary business of Taiwan North-South High-Speed Railway Project (THR), and create the relation between the BOT & it’s ancillary business. The thesis will use the ANOVA & Tuley’s Multiple Comparison Method to validate the relationship, and hope it will let the participator to consider in the future.