Transportation infrastructure, a vital component to sustain economic prosperity, represents the largest public-owned infrastructure asset in the U.S. With over a trillion invested dollars invested into long-lived physical assets such as roads and bridges, transportation agencies are tasked with maintenance and rehabilitation efforts to ensure that the access to transportation facilities is readily available and that the infrastructure is properly preserved. The management of these assets and the determination of their value, however, have been at the forefront of discussions in many state agencies and local governments. As a consequence, asset valuation has become a key component in asset management because it links the performance of infrastructure and deterioration process with the value of the infrastructure and its depreciation, providing critical information for decision makers at various levels to make more informed decisions. A utility-based methodological framework for the valuation of transportation infrastructure is presented along with a case study to demonstrate its applicability. A general framework is presented with emphasis on the valuation of pavement infrastructure. The results from the framework is then compared to existing valuation methods in addition to a series of sensitivity analysis on the variation of performance measures and their effect on the value of an asset. The development of this valuation approach serves as a starting point for assessing, in addition to the physical condition of an asset, the operational measures that can often make an asset less useful to its customers and managing agency. Utility theory can be utilized to combine the effect of performance indicators of varying measures and scales on the value of an asset. The proposed framework can assist state and local transportation agencies in the optimization of resource allocation procedures for better coordination of asset investments, facilitating benefit-cost analyses to quantify the impact of infrastructure investments. This tool allows agencies to detect deficiencies if any, in the management of its assets, providing a feedback mechanism that can foster an introspective review of its current management practices that may need further refinement or possibly elimination. / text

Diss. Stockholm : Kungliga Tekniska högskolan, 2007.

The deregulation of energy markets around the world, including power markets has changed the way operating assets in these markets are managed. Independent power asset owners and even utilities operating in these markets no longer operate their assets based on the cost of service approach that prevailed under regulation. Just as in other competitive markets, the objectives of asset owners in power markets revolve around maximizing profit for their shareholders. To this end, financial valuation of physical assets in power markets should incorporate different strategies that are used by asset operators to maximize profit. A lot of observed strategies in power markets are driven by a number of factors, the key among which are: • asset operators are no longer obligated to supply service or manage their assets in certain prescribed ways, rather they have rights to operate, within applicable market rules, using techniques that maximize their profits, • revenues are driven by uncertain market factors, including power price, cost and/or availability of fuel stock and technical uncertainties, and • power assets have physical operating and equipment constraints and limits. Having flexibilties (“options”) to optimize their assets (inline with shareholders’ objectives), rational asset managers react strategically to gradual arrival of information , given applicable equipment constraints, by revising previous decisions in such a way that only optimal (or near optimal) decisions are implemented. As a result, the appropriate approach to valuing power assets in competitive markets must account for managerial flexibilities or “real options” in the presence of uncertainties and technical constraints. The focus of this work is to develop a robust valuation framework for physical power assets operating in competitive markets such as peaking or mid-merit thermal power plants and baseload power plants. The goal is to develop a modeling framework that can be adapted to different energy assets with different types of operating flexibilities and technical constraints and which can be employed for various purposes such as capital budgeting, business planning, risk management and strategic bidding planning among others. The valuation framework must also be able to capture the reality of power market rules and opportunities, as well as technical constraints of different assets. The modeling framework developed conceptualizes operating flexibilities of power assets as “switching options’ whereby the asset operator decides at every decision point whether to switch from one operating mode to another mutually exclusive mode, within the limits of the equipment constraints of the asset. As a current decision to switch operating modes (in the face of current realization of relevant uncertainty factors) may affect future operating flexibilities of the asset and hence cash flows , a dynamic optimization framework is employed. The developed framework accounts for the uncertain nature of key value drivers by representing them with appropriate stochastic processes. Specifically, the framework developed conceptualizes the operation of a power asset as a multi-stage decision making problem where the operator has to make a decision at every stage to alter operating mode given currently available information about key value drivers. The problem is then solved dynamically by decomposing it into a series of two-stage sub-problems according to Bellman’s optimality principle. The solution algorithm employed is the Least Squares Monte Carlo (LSM) method. The developed valuation framework was adapted for a gas-fired thermal power plant, a peaking hydroelectric power plant and a baseload power plant. This work built on previously published real options valuation methodologies for gas-fired thermal power plants by factoring in uncertainty from gas supply/consumption imbalance which is usually faced by gas-fired power generators. This source of uncertainty which has yet to be addressed in the literature, in the context of real options valuation, arises because of mismatch between natural gas and electricity wholesale markets. Natural gas markets in North America operate on a day-ahead basis while power plants are dispatched in real time. Inability of a power generator to match its gas supply and consumption in real time, leading to unauthorized gas over-run or under-run, attracts penalty charges from the gas supplier to the extent that the generator can not manage the imbalance through other means. A savvy gas-fired power plant operator will factor in the potential costs of gas imbalance into its operating strategies resulting in optimal operating decisions that may be different from when gas-imbalance is not considered. By considering an illustrative power plant operating in Ontario, we show effects of gas-imbalance on dispatch strategies on a daily cycling operation basis and the resulting impact on net revenue. Results show that a gas-fired power plant is over-valued by ignoring the impacts of gas imbalance on valuation. Similarly, we employ the developed valuation framework to value a peaking hydroelectric power plant. This application also builds on previous real options valuation work for peaking hydroelectric power plants by considering their operations in a joint energy and ancillary services market. Specifically, the valuation model is developed to capture the value of a peaking power plant whose owner has the flexibility to participate in a joint operating reserve market and an energy market, which is currently the case in the Ontario wholesale power market. The model factors in water inflow uncertainty into the reservoir forebay of a hydroelectric facility and also considers uncertain energy and operating reserve prices. The switching options considered include (i) a joint energy and operating reserve bid (ii) an energy only bid and (iii) a do nothing (idle) strategy. Being an energy limited power plant, by doing nothing at a decision interval, the power asset operator is able to time-shift scarce water for use at a future period when market situations are expected to be better. An illustrative example considered shows the impact of the different value drivers on the plant’s value and dispatch strategies. Results show that by ignoring the flexibility of the asset owner to participate in an operating reserve market, a peaking hydroelectric power plant is undervalued. Finally, the developed valuation framework was employed to optimize life-cycle management decisions of a baseload power plant, such as a nuclear power plant. The applicability of real-options framework to the operations of baseload power plants has not attracted much attention in the literature given their inflexibility with respect to short-term operation. However, owners of baseload power plants, such as nuclear plants, have the right to optimize scheduling and spending of life cycle management projects such as preventative maintenance and equipment inspection. Given uncertainty of long-term value drivers, including power prices, equipment performance and the relationship between current life cycle spending and future equipment degradation, optimization is carried out with the objective of minimizing overall life-cycle related costs. These life-cycle costs include (i) lost revenue during planned and unplanned outages (ii) potential costs of future equipment degradation due to inadequate preventative maintenance and (iii) the direct costs of implementing the life-cycle projects. The switching options in this context include the option to shutdown the power plant in order to execute a given preventative maintenance and inspection project and the option to keep the option “alive” by choosing to delay a planned life-cycle activity. Results of an illustrative example analyzed show that the flexibility of the asset owner to delay spending or to suspend it entirely affects the asset’s value accordingly and should be factored into valuation. Applications can be found for the developed framework and models in different areas important to firms operating in competitive energy markets. These areas include capital budgeting, trading, risk management, business planning and strategic/tactitcal bidding among others.

The deregulation of energy markets around the world, including power markets has changed the way operating assets in these markets are managed. Independent power asset owners and even utilities operating in these markets no longer operate their assets based on the cost of service approach that prevailed under regulation. Just as in other competitive markets, the objectives of asset owners in power markets revolve around maximizing profit for their shareholders. To this end, financial valuation of physical assets in power markets should incorporate different strategies that are used by asset operators to maximize profit. A lot of observed strategies in power markets are driven by a number of factors, the key among which are: • asset operators are no longer obligated to supply service or manage their assets in certain prescribed ways, rather they have rights to operate, within applicable market rules, using techniques that maximize their profits, • revenues are driven by uncertain market factors, including power price, cost and/or availability of fuel stock and technical uncertainties, and • power assets have physical operating and equipment constraints and limits. Having flexibilties (“options”) to optimize their assets (inline with shareholders’ objectives), rational asset managers react strategically to gradual arrival of information , given applicable equipment constraints, by revising previous decisions in such a way that only optimal (or near optimal) decisions are implemented. As a result, the appropriate approach to valuing power assets in competitive markets must account for managerial flexibilities or “real options” in the presence of uncertainties and technical constraints. The focus of this work is to develop a robust valuation framework for physical power assets operating in competitive markets such as peaking or mid-merit thermal power plants and baseload power plants. The goal is to develop a modeling framework that can be adapted to different energy assets with different types of operating flexibilities and technical constraints and which can be employed for various purposes such as capital budgeting, business planning, risk management and strategic bidding planning among others. The valuation framework must also be able to capture the reality of power market rules and opportunities, as well as technical constraints of different assets. The modeling framework developed conceptualizes operating flexibilities of power assets as “switching options’ whereby the asset operator decides at every decision point whether to switch from one operating mode to another mutually exclusive mode, within the limits of the equipment constraints of the asset. As a current decision to switch operating modes (in the face of current realization of relevant uncertainty factors) may affect future operating flexibilities of the asset and hence cash flows , a dynamic optimization framework is employed. The developed framework accounts for the uncertain nature of key value drivers by representing them with appropriate stochastic processes. Specifically, the framework developed conceptualizes the operation of a power asset as a multi-stage decision making problem where the operator has to make a decision at every stage to alter operating mode given currently available information about key value drivers. The problem is then solved dynamically by decomposing it into a series of two-stage sub-problems according to Bellman’s optimality principle. The solution algorithm employed is the Least Squares Monte Carlo (LSM) method. The developed valuation framework was adapted for a gas-fired thermal power plant, a peaking hydroelectric power plant and a baseload power plant. This work built on previously published real options valuation methodologies for gas-fired thermal power plants by factoring in uncertainty from gas supply/consumption imbalance which is usually faced by gas-fired power generators. This source of uncertainty which has yet to be addressed in the literature, in the context of real options valuation, arises because of mismatch between natural gas and electricity wholesale markets. Natural gas markets in North America operate on a day-ahead basis while power plants are dispatched in real time. Inability of a power generator to match its gas supply and consumption in real time, leading to unauthorized gas over-run or under-run, attracts penalty charges from the gas supplier to the extent that the generator can not manage the imbalance through other means. A savvy gas-fired power plant operator will factor in the potential costs of gas imbalance into its operating strategies resulting in optimal operating decisions that may be different from when gas-imbalance is not considered. By considering an illustrative power plant operating in Ontario, we show effects of gas-imbalance on dispatch strategies on a daily cycling operation basis and the resulting impact on net revenue. Results show that a gas-fired power plant is over-valued by ignoring the impacts of gas imbalance on valuation. Similarly, we employ the developed valuation framework to value a peaking hydroelectric power plant. This application also builds on previous real options valuation work for peaking hydroelectric power plants by considering their operations in a joint energy and ancillary services market. Specifically, the valuation model is developed to capture the value of a peaking power plant whose owner has the flexibility to participate in a joint operating reserve market and an energy market, which is currently the case in the Ontario wholesale power market. The model factors in water inflow uncertainty into the reservoir forebay of a hydroelectric facility and also considers uncertain energy and operating reserve prices. The switching options considered include (i) a joint energy and operating reserve bid (ii) an energy only bid and (iii) a do nothing (idle) strategy. Being an energy limited power plant, by doing nothing at a decision interval, the power asset operator is able to time-shift scarce water for use at a future period when market situations are expected to be better. An illustrative example considered shows the impact of the different value drivers on the plant’s value and dispatch strategies. Results show that by ignoring the flexibility of the asset owner to participate in an operating reserve market, a peaking hydroelectric power plant is undervalued. Finally, the developed valuation framework was employed to optimize life-cycle management decisions of a baseload power plant, such as a nuclear power plant. The applicability of real-options framework to the operations of baseload power plants has not attracted much attention in the literature given their inflexibility with respect to short-term operation. However, owners of baseload power plants, such as nuclear plants, have the right to optimize scheduling and spending of life cycle management projects such as preventative maintenance and equipment inspection. Given uncertainty of long-term value drivers, including power prices, equipment performance and the relationship between current life cycle spending and future equipment degradation, optimization is carried out with the objective of minimizing overall life-cycle related costs. These life-cycle costs include (i) lost revenue during planned and unplanned outages (ii) potential costs of future equipment degradation due to inadequate preventative maintenance and (iii) the direct costs of implementing the life-cycle projects. The switching options in this context include the option to shutdown the power plant in order to execute a given preventative maintenance and inspection project and the option to keep the option “alive” by choosing to delay a planned life-cycle activity. Results of an illustrative example analyzed show that the flexibility of the asset owner to delay spending or to suspend it entirely affects the asset’s value accordingly and should be factored into valuation. Applications can be found for the developed framework and models in different areas important to firms operating in competitive energy markets. These areas include capital budgeting, trading, risk management, business planning and strategic/tactitcal bidding among others.

Mergers and acquisitions within the chemical industry is a common practice to increase market presence and customer base. Common justifications for M&A include synergy, business growth and competitive advantages, and management reasoning. Synergies are benefits a combined firm is able to receive through cost reductions, market expansion, and efficiencies in processes. As a result, firms are able to grow and position themselves competitively. To prevent an overpriced acquisition, numerous valuation techniques exist. The discount cash flow examines the value of a firm based on future cash flow. The market multiple compares target firms to similar firms in the industry. Lastly, the asset valuation determines the value of a firm based on the liquidation of the firm. To maximize the return on an acquisition, proper due diligence should be conducted based on the needs and goals of the purchaser, and the value added by the target firm. The premium paid for an acquisition should be based on the valued added through the synergies identified. Current business cycles and future outlook should also factor into the pricing of the acquisition. Having a thorough analysis of a target firm can help the acquirer to clearly understand what is being purchased and hence, determine an appropriate price for the acquisition. / text

During the last two decades there has been an explosion in the number of complex financial instruments that are traded on the financial markets. Naturally, being able to value the increasing number of traded complex financial instruments has an academic interest. Such valuation methods are, however, certainly not only of interest to academics. For agents on the financial markets, it is of crucial importance to be able to assess the value of new exotic securities. This is equally true for financial services firms that construct and promote the instruments, borrowers that sell the products for the financing of their activities and investors that buy the products. Many new financial instruments have attributes that make Contingent Claims Analysis (CCA) superior to other currently known valuation methods. CCA is a technique for determining the price of an asset whose payoffs depend upon the evolution of one or more underlying state variables. One problem that often arises when this framework is used is that it is not possible to find a closed-form solution for the price. Numerical methods must therefore be relied on. Furthermore, in many cases and especially in cases where there is more than one underlying state variable, which many complex financial instruments require for accurate valuation, numerical methods become computationally laborious. Hence, research concerning and development of efficient numerical methods that can be used in the CCA context is important. This dissertation consists of four different papers (papers A to D). Paper A provides discussion of the process of financial innovation. A lengthy appendix is attached to paper A. In this appendix, more thn 100 more or less complex financial instruments are described briefly. Papers B to D have a common theme, which is valuation of complex financial instruments with the help of CCA and numerical methods. The research task of paper B is to answer a question that has unclear status in academic literature. The question is "How do errors (or different modelling choices) in boundary conditions affect solutions when the implicit finite difference method is used?". In papers C and D, numerical methods which can be used to price financial instruments with several underlying state variables are developed and tested. The methods in paper C are finite difference methods, and the method in paper D is a lattice (or tree) approach. / Diss. Stockholm : Handelshögsk.

This paper will cover the reasons as to why the current accounting standards have not been updated as necessary to account for the newly developed, intangible assets or “pho-assets” that companies are either generating or using for future economic benefit. This paper will cover a brief background on the current accounting standards for intangible asset valuation and identification and why they are not sufficient for the current accounting environment. Within this review of the accounting standards, this paper will highlight how the changing financial world has given rise to these new intangible assets, and why current regulations do not allow firms to recognize all the assets that it truly should have on its books, thereby not allowing firms to realize or gain precious valuation. Furthermore, I will provide evidence as to why the accounting standards have made it difficult for investors to properly gauge the risk of intangible investments due to the inconsistencies in valuation that the current standards produce.

This paper examines the components of the Capital Asset Pricing Model and the model's uses to analyze portfolios returns. It also looks at subsequent versions of the CAPM including a multi-variable CAPM with the inclusion of selected macro-variables as well as a non-stationary beta CAPM to estimate portfolio returns. A new model is proposed that combines the multi-variable component together with the non-stationary beta component to derive a new CAPM that is more effective at capturing current market conditions than the traditional CAPM with the fixed beta coefficient. The multi-variable CAPM with non-stationary beta is applied, together with the select macro-variables, to estimate the returns of a portfolio of assets in the oil-sector of the economy. It looks at returns during the period of 1995-2001 when the economy exhibited a wide range of variation in market returns. This paper tests the hypothesis that adapting the traditional CAPM to include beta non-stationarity will better estimate portfolio returns in a fluid market environment. The empirical results suggest that the new model is statistically significant at measuring portfolio returns. This model is estimated with an Ordinary Least Square (OLS) estimations process and identifies three factors that are statistically significant. These include quarterly changes in the Gross Domestic Product (GDP), the Unemployment Rate and the Consumer Price Index (CPI). / Master of Arts

O presente trabalho tem como objetivo principal demonstrar que parcela da base de depositantes de instituições financeiras que se utilizam de depósitos (a prazo e a vista) como fonte de financiamento das suas atividades, identificada pelos depósitos estáveis, representa um ativo intangível da instituição depositária. Esse ativo intangível decorrente dos depósitos estáveis, quando passível de identificação específica, explica parte do goodwill da instituição depositária, pelo fato do goodwill ser um ativo residual dependente principalmente da avaliação da empresa como um todo. Sendo o valor do goodwill determinado pela diferença entre o fair value da entidade como um todo, como um ativo único em continuidade, e a soma algébrica dos fair values dos ativos líquidos identificáveis dessa entidade, à medida que novos ativos antes não contabilizados são identificados, está-se explicado a natureza do goodwill, assim como está-se auxiliando na sua atribuição de valor. Portanto a identificação de mais um ativo intangível das instituições financeiras implica na identificação de parcelas componentes do goodwill, que englobava esse ativo intangível antes da identificação do ativo intangível, assim como também implica na explicação econômica de parte do goodwill. Para que o objetivo pudesse ser alcançado, comparou-se as características econômicas e contábeis dos ativos, dos ativos intangíveis e do goodwill com as características econômicas e contábeis dos depósitos estáveis, chegando-se à conclusão de que tais depósitos representam um ativo intangível, identificável em separado e passível de registro contábil. O registro contábil desse ativo intangível nas demonstrações contábeis utilizadas para fins de publicação é atualmente possível somente quando a instituição depositária tiver sido objeto de compra por outra entidade. Caso isso não tenha ocorrido, alternativamente pode-se fazer uso do ativo intangível para fins de controle gerencial. O trabalho também apresenta um caso real de avaliação dos depósitos estáveis como forma de corroborar a possibilidade de identificação e avaliação do ativo intangível decorrente desses depósitos. / The main objective of the present work is to demonstrate that a part of the depository base of financial institutions that make use of (time and demand) deposits as a source of funding for their activities, which is identified by stable deposits, represents an intangible asset of the depositary institution. When its specific identification is possible, this intangible asset, which results from the stable deposits, explains a part of the goodwill of the depositary institution, considering that goodwill is a residual asset that mainly depends on the valuation of the company as a whole. As the value of goodwill is determined by the difference between the fair value of the entity as a whole, that is, as a unique asset in a going concern, and the algebraic sum of the fair values of the entity’s identifiable net assets, to the extent that new assets are identified, which were not recorded before, the nature of goodwill is explained and its value attribution is enhanced. Hence, the identification of another intangible asset in the financial institutions implies the identification of new parts of the goodwill, which incorporated this intangible asset before the identification of the intangible asset, as well as the explanation of the economic nature of goodwill. To achieve this goal, the economic and accounting characteristics of assets, intangible assets and goodwill were compared to the economic and accounting characteristics of the stable deposits, which led to the conclusion that those deposits represent an intangible asset, which can be identified separately and can be registered in the accounting records. The accounting record of this intangible asset in the financial statements, which are used for publication, is only possible nowadays when the depositary institution has been the target of a purchase by another entity. In case this has not happened, the intangible asset can alternatively be used for management control. The present work also presents a real case of stable deposit valuation, so as to corroborate the possibility of identification and valuation of intangibles resulting from the stable deposits.

Made available in DSpace on 2015-03-05T19:13:44Z (GMT). No. of bitstreams: 0 Previous issue date: 31 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / As transformações sociais e econômicas presenciadas desde o final da década de 1970 evidenciaram a importância do conhecimento como recurso econômico intangível e motivaram tanto a comunidade acadêmica quanto o mercado a identificar e mensurar este recurso, também denominado capital intelectual. O objetivo deste estudo foi analisar o uso combinado de experimentos com leilões e da avaliação de ativos pelo custo corrente como procedimento para mensuração do capital intelectual. Foram discutidas as relações entre ativos intangíveis, goodwill e capital intelectual, bem como os principais modelos de mensuração. Com base nos requisitos teóricos da economia experimental, foi desenhado e aplicado um experimento sob a forma de leilões, com a finalidade de indicar o valor de mercado das três empresas que compunham a amostra. Posteriormente foi realizada a avaliação dos itens do ativo permanente pelo custo corrente, alocando-se um valor contábil ajustado livre das distorções inerentes à avaliação pelo custo histórico. A / Social and economical transformations witnessed since the end of the decade of 1970 had evidenced the importance of knowledge as an intangible economic resource and motivated both academic community and market to identify and measure this resource, also denominated intellectual capital. The objective of this study is to analyze the combined usage of auction experiments and current cost asset valuation as a procedure to measure intellectual capital. Relations among intangible assets, goodwill and intellectual capital were discussed, as well as the main measurement models. Based on the theoretical requirements of experimental economy, an experiment was designed and executed in the format of an auction, aiming to indicate the market value of the three enterprises compounding the sample. Later a valuation of the permanent assets was conducted through current cost, allocating an adjusted book value free from distortions inherent to the historical cost valuation. From the difference between indicated market value a