860 resultados para Volatility Models, Volatility, Equity Markets


Relevância:

30.00% 30.00%

Publicador:

Resumo:

Mestrado em Contabilidade e análise financeira

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Mestrado em Contabilidade e Análise Financeira

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Energia

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Mestrado em Contabilidade e Análise Financeira

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Nesta tese estudamos os efeitos de contágio financeiro e de memória longa causados pelas crises financeiras de 2008 e 2010 em alguns mercados acionistas internacionais. A tese é composta por três ensaios interligados. No Ensaio 1, recorremos à teoria das cópulas para testar a existência de contágio e revelar os canais “investor induced” de transmissão da crise de 2008 aos mercados da Bélgica, França, Holanda e Portugal (grupo NYSE Euronext). Concluímos que existe contágio nestes mercados, que o canal “portfolio rebalancing” é o mecanismo mais importante de transmissão da crise, e que o fenómeno “flight to quality” está presente nos mercados. No Ensaio 2, usando novamente modelos de cópulas, avaliamos os efeitos de contágio provocados pelo mercado acionista grego nos mercados do grupo NYSE Euronext, no contexto da crise de 2010. Os resultados obtidos sugerem que durante a crise de 2010 apenas o mercado português foi objeto de contágio; além disso, conclui-se que os efeitos de contágio provocados pela crise de 2008 são claramente superiores aos efeitos provocados pela crise de 2010. No Ensaio 3, abordamos o tema da memória longa através do estudo do expoente de Hurst dos mercados acionistas da Bélgica, E.U.A., França, Grécia, Holanda, Japão, Reino Unido e Portugal. Verificamos que as propriedades de memória longa dos mercados foram afetadas pelas crises, especialmente a de 2008 – que aumentou a memória longa dos mercados e tornou-os mais persistentes. Finalmente, usando cópulas mais uma vez, verificamos que as crises provocaram, em geral, um aumento na correlação entre os expoentes de Hurst locais dos mercados foco das crises (E.U.A. e Grécia) e os expoentes de Hurst locais dos outros mercados da amostra, sugerindo que o expoente de Hurst pode ser utilizado para detetar efeitos de contágio financeiro. Em síntese, os resultados desta tese sugerem que comparativamente com períodos de acalmia, os períodos de crises financeiras tendem a provocar ineficiência nos mercados acionistas e a conduzi-los na direção da persistência e do contágio financeiro.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Com este trabalho pretende-se efetuar o levantamento e análise dos fatores que estão na base da volatilidade do preço da energia elétrica no mercado ibérico de energia. Posteriormente à definição dos potenciais métodos utilizados na previsão do preço da energia elétrica, é desenvolvido um modelo capaz de prever os preços do mercado de energia para um horizonte de vários períodos temporais (trimestral, mensal, semanal e diário). Por fim são comparados os resultados dos modelos aplicados, tendo como base a análise qualitativa e quantitativa da evolução das respetivas previsões, bem como a análise estatística obtida em cada um deles.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

No contexto da penetração de energias renováveis no sistema elétrico, Portugal ocupa uma posição de destaque a nível mundial, muito devido à produção de eólica. Com um sistema elétrico com forte presença de fontes de energia renováveis, novos desafios surgem, nomeadamente no caso da energia eólica pela sua imprevisibilidade e volatilidade. O recurso eólico embora seja ilimitado não é armazenável, surgindo assim a necessidade da procura de modelos de previsão de produção de energia elétrica dos parques eólicos de modo a permitir uma boa gestão do sistema. Nesta dissertação apresentam-se as contribuições resultantes de um trabalho de pesquisa e investigação sobre modelos de previsão da potência elétrica com base em valores de previsões meteorológicas, nomeadamente, valores previstos da intensidade e direção do vento. Consideraram-se dois tipos de modelos: paramétricos e não paramétricos. Os primeiros são funções polinomiais de vários graus e a função sigmoide, os segundos são redes neuronais artificiais. Para a estimação dos modelos e respetiva validação, são usados dados recolhidos ao longo de dois anos e três meses no parque eólico do Pico Alto de potência instalada de 6 MW. De forma a otimizar os resultados da previsão, consideram-se diferentes classes de perfis de produção, definidas com base em quatro e oito direções do vento, e ajustam-se os modelos propostos em cada uma das classes. São apresentados e discutidos resultados de uma análise comparativa do desempenho dos diferentes modelos propostos para a previsão da potência.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Gestão das Organizações, Ramo Gestão de Empresas Orientador: Professor Doutor Eduardo Manuel Lopes de Sá e Silva Co-orientador: Mestre Maria de Fátima Mendes Monteiro

Relevância:

30.00% 30.00%

Publicador:

Resumo:

The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Electricity markets worldwide are complex and dynamic environments with very particular characteristics. These are the result of electricity markets’ restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources. The rising complexity and unpredictability in electricity markets has increased the need for the intervenient entities in foreseeing market behaviour. Market players and regulators are very interested in predicting the market’s behaviour. Market players need to understand the market behaviour and operation in order to maximize their profits, while market regulators need to test new rules and detect market inefficiencies before they are implemented. The growth of usage of simulation tools was driven by the need for understanding those mechanisms and how the involved players' interactions affect the markets' outcomes. Multi-agent based software is particularly well fitted to analyse dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. Several modelling tools directed to the study of restructured wholesale electricity markets have emerged. Still, they have a common limitation: the lack of interoperability between the various systems to allow the exchange of information and knowledge, to test different market models and to allow market players from different systems to interact in common market environments. This dissertation proposes the development and implementation of ontologies for semantic interoperability between multi-agent simulation platforms in the scope of electricity markets. The added value provided to these platforms is given by enabling them sharing their knowledge and market models with other agent societies, which provides the means for an actual improvement in current electricity markets studies and development. The proposed ontologies are implemented in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) and tested through the interaction between MASCEM agents and agents from other multi-agent based simulators. The implementation of the proposed ontologies has also required a complete restructuring of MASCEM’s architecture and multi-agent model, which is also presented in this dissertation. The results achieved in the case studies allow identifying the advantages of the novel architecture of MASCEM, and most importantly, the added value of using the proposed ontologies. They facilitate the integration of independent multi-agent simulators, by providing a way for communications to be understood by heterogeneous agents from the various systems.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics