899 resultados para Asset Pricing
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This paper studies a portfolio choice problem such that the pricing rule may incorporate transaction costs and the risk measure is coherent and expectation bounded. We will prove the necessity of dealing with pricing rules such that there exists an essentially bounded stochastic discount factor, which must be also bounded from below by a strictly positive value. Otherwise good deals will be available to traders, i.e., depending on the selected risk measure, investors can build portfolios whose (risk, return) will be as close as desired to (−infinity, infinity) or (0, infinity). This pathologic property still holds for vector risk measures (i.e., if we minimize a vector valued function whose components are risk measures). It is worthwhile to point out that essentially bounded stochastic discount factors are not usual in financial literature. In particular, the most famous frictionless, complete and arbitrage free pricing models imply the existence of good deals for every coherent and expectation bounded (scalar or vector) measure of risk, and the incorporation of transaction costs will not guarantee the solution of this caveat.
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Financial literature and financial industry use often zero coupon yield curves as input for testing hypotheses, pricing assets or managing risk. They assume this provided data as accurate. We analyse implications of the methodology and of the sample selection criteria used to estimate the zero coupon bond yield term structure on the resulting volatility of spot rates with different maturities. We obtain the volatility term structure using historical volatilities and Egarch volatilities. As input for these volatilities we consider our own spot rates estimation from GovPX bond data and three popular interest rates data sets: from the Federal Reserve Board, from the US Department of the Treasury (H15), and from Bloomberg. We find strong evidence that the resulting zero coupon bond yield volatility estimates as well as the correlation coefficients among spot and forward rates depend significantly on the data set. We observe relevant differences in economic terms when volatilities are used to price derivatives.
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The mis-evaluation of risk in securitized financial products is central to understanding the global financial crisis. This paper characterizes the evolution of risk factors affecting collateralized debt obligations (CDOs) based on subprime mortgages. A key feature of subprime mortgage-backed indices is that they are distinct in their vintage of issuance. Using a latent factor framework that incorporates this vintage effect, we show the increasing importance of common factors on more senior tranches during the crisis. An innovation of the paper is that we use the unbalanced panel structure of the data to identify the vintage, credit, common and idiosyncratic effects from a state-space specification.
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Although stock prices fluctuate, the variations are relatively small and are frequently assumed to be normal distributed on a large time scale. But sometimes these fluctuations can become determinant, especially when unforeseen large drops in asset prices are observed that could result in huge losses or even in market crashes. The evidence shows that these events happen far more often than would be expected under the generalized assumption of normal distributed financial returns. Thus it is crucial to properly model the distribution tails so as to be able to predict the frequency and magnitude of extreme stock price returns. In this paper we follow the approach suggested by McNeil and Frey (2000) and combine the GARCH-type models with the Extreme Value Theory (EVT) to estimate the tails of three financial index returns DJI,FTSE 100 and NIKKEI 225 representing three important financial areas in the world. Our results indicate that EVT-based conditional quantile estimates are much more accurate than those from conventional AR-GARCH models assuming normal or Student’s t-distribution innovations when doing out-of-sample estimation (within the insample estimation, this is so for the right tail of the distribution of returns).
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Most financial and economic time-series display a strong volatility around their trends. The difficulty in explaining this volatility has led economists to interpret it as exogenous, i.e., as the result of forces that lie outside the scope of the assumed economic relations. Consequently, it becomes hard or impossible to formulate short-run forecasts on asset prices or on values of macroeconomic variables. However, many random looking economic and financial series may, in fact, be subject to deterministic irregular behavior, which can be measured and modelled. We address the notion of endogenous volatility and exemplify the concept with a simple business-cycles model.
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O estudo insere-se no âmbito da educação matemática, mais especificamente na área da geometria. Com esta investigação pretende-se compreender qual o contributo do Ambiente de Geometria Dinâmica (AGD), GeoGebra, e do material manipulável (geoplano) na identificação das propriedades e relações entre quadriláteros: trapézio, paralelogramo, retângulo, losango e quadrado. De acordo com o objetivo do estudo formularam-se três questões: Qual o papel das representações na identificação das propriedades dos quadriláteros? Que influência tem a visualização na identificação das propriedades dos quadriláteros? Quais os contributos da utilização do AGD, GeoGebra, e do material manipulável (geoplano) na compreensão das propriedades e relações entre os quadriláteros? Atendendo à problemática em estudo, optou-se por uma metodologia de investigação predominantemente qualitativa, baseada em três estudos de caso. A recolha de dados empÃricos foi realizada numa turma de 4.º ano do 1.º ciclo do ensino básico onde se implementou uma experiência de ensino, envolvendo todos os alunos e recorrendo ao geoplano e ao GeoGebra. Essa recolha incidiu na observação participante, em sala de aula, no registo de notas da investigadora, nos documentos produzidos pelos alunos e nos registos áudio e vÃdeo das discussões nos grupos e no coletivo da turma. Em termos de resultados, salienta-se que a utilização de representações evidenciou a compreensão que os alunos têm dos conceitos, facilitou a identificação das propriedades dos quadriláteros e a compreensão das relações entre eles. Os alunos identificaram as propriedades com base nas representações, no entanto focaram-se em casos particulares, de acordo com a imagem mental que têm da figura, especificamente o protótipo, indiciando a influência da visualização. Dos resultados sobressai também a dificuldade que os alunos sentiram em considerar uma figura como representante de uma classe e em distinguir atributos essenciais e não essenciais. Da análise dos dados ressalta também que tanto o geoplano como o GeoGebra foram uma mais-valia na concretização da experiência de ensino deste estudo. Os dois possuem vantagens e limitações e podem ser usados de maneira que um complemente o outro, podendo dessa forma contribuir, favoravelmente, para a aprendizagem da geometria. - ABSTRACT The study falls within the scope of mathematics education, specifically in the area of geometry. This research aims to understand the contribution of the Dynamic Geometry Environment (GeoGebra) and manipulative material (Geoboard) in the identification of properties and relations of quadrilaterals: trapezium, parallelogram, rectangle, diamond and square. According to the purpose of the study three questions were formulated: What is the role of the representations in the identification of the properties of quadrilaterals? What is the influence of visualization on the identification of the properties of quadrilaterals? What are the contributions on the use of Dynamic Geometry Environment (GeoGebra) and manipulative material (Geoboard) to understand the properties and relationships among quadrilaterals? Given the problem under study, it was chosen a predominantly qualitative research methodology based on three case studies. The empirical data collection was carried out on a fourth primary grade class, where it was implemented a teaching experience, involving all students and the use of Geoboard and GeoGebra. This collection was focused on participant observation in the classroom, in the record of the researcher’s notes, the documents produced by the students and the audio and video recordings of group discussions and collective class. In terms of results, it is noted that the use of representations showed the students understanding of the concepts and that it has facilitated the identification of the properties of quadrilaterals and understanding of the relationships between them. The students identified properties based on representations, however they focused in particular cases, according to the mental image that they have of the figure, specifically the prototype, indicating the influence of visualization. Results also highlights the difficulty that students felt in considering a figure as a representation of a group and distinguishing essential and nonessential attributes. Data analysis also highlights that both Geoboard and GeoGebra have been an asset in the delivery of teaching experience in this study. Both have advantages and limitations and they may be used to complement each other and contribute favorably to the learning of geometry.
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Trabalho de Projecto para a obtenção do Grau de Mestre em Contabilidade e Finanças Orientador: Mestre Armindo LicÃnio da Silva Macedo
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Dissertação para obtenção do Grau de Mestre em Contabilidade e Finanças Orientador: Doutor José Manuel da Veiga Pereira
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Dissertação apresentada ao Instituto Superior de Contabilidade para obtenção do Grau de Mestre em Auditoria Orientada por: Doutora Alcina Dias
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This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.
Using demand response to deal with unexpected low wind power generation in the context of smart grid
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Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).
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In smart grids context, the distributed generation units based in renewable resources, play an important rule. The photovoltaic solar units are a technology in evolution and their prices decrease significantly in recent years due to the high penetration of this technology in the low voltage and medium voltage networks supported by governmental policies and incentives. This paper proposes a methodology to determine the maximum penetration of photovoltaic units in a distribution network. The paper presents a case study, with four different scenarios, that considers a 32-bus medium voltage distribution network and the inclusion storage units.
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This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.
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In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.
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Locational Marginal Prices (LMP) are important pricing signals for the participants of competitive electricity markets, as the effects of transmission losses and binding constraints are embedded in LMPs [1],[2]. This paper presents a software tool that evaluates the nodal marginal prices considering losses and congestion. The initial dispatch is based on all the electricity transactions negotiated in the pool and in bilateral contracts. It must be checked if the proposed initial dispatch leads to congestion problems; if a congestion situation is detected, it must be solved. An AC power flow is used to verify if there are congestion situations in the initial dispatch. Whenever congestion situations are detected, they are solved and a feasible dispatch (re-dispatch) is obtained. After solving the congestion problems, the simulator evaluates LMP. The paper presents a case study based on the the 118 IEEE bus test network.