852 resultados para Decentralized markets


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By testing a simple asset pricing model of heterogeneous agents to characterize the power-law behavior of the DAX 30 from 1975 to 2007, we provide supporting evidence on empirical findings that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. By conducting econometric analysis via Monte Carlo simulations, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely the corresponding estimates for the DAX 30. A mechanism analysis based on the calibrated model provides further insights into the explanatory power of heterogeneous agent models.

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O mercado imobiliário tem um papel importante nas economias modernas, tanto a nível macro como a nível micro. Ao nível macro, a construção de habitação representa um sector importante e influente na economia, com efeitos multiplicadores significativos sobre a produção e o emprego. Ao nível micro, uma residência representa o activo mais valioso da maioria dos indivíduos e uma parcela muito relevante da riqueza das famílias. Para estas, o custo e a qualidade das suas habitações influencia directa e indirectamente a sua qualidade de vida. A habitação é por isso mesmo um tema, que avaliado nas suas múltiplas dimensões, se caracteriza por ser bastante complexo, mas também ao mesmo tempo desafiante. De modo a delimitar o objecto de análise do trabalho de investigação, esta tese realça os aspectos de localização e distribuição espacial das habitações urbanas. Será desenvolvido um quadro conceptual e respectiva metodologia para a compreender a estrutura espacial da habitação urbana realçando os três aspectos fundamentais da análise espacial: heterogenidade espacial, dependência espacial e escala espacial. A metodologia, aplicada à área urbana de Aveiro e Ílhavo é baseada numa análise hedónica factorial de preços e na noção não geométrica do espaço. Primeiro, é fixada uma escala territorial e são definidos submercados habitacional. Posteriormente, quer a heterogeneidade quer a dependência espaciais são estudados utilizando métodos econométricos, sem considerar qualquer padrão fixo e conhecido de interações espaciais. Em vez disso, são desenvolvidos novos métodos,tendo como base o modelo hedónico factorial, para inferir sobre os potenciais drivers de difusão espacial no valor de uma habitação. Este modelo, foi aplicado a duas diferentes escalas espaciais, para compreender as preferências dos indivíduos em Aveiro ao escolher os seus locais de residencia, e como estas afectam os preços da habitação. O trabalho empírico, utilizando duas bases de dados de habitação distintas, aplicadas ao mercado de habitação de Aveiro mostram: i) em linha com a literatura, a dificuldade de definir submercados e compreender as inter-relações entre esses mercados; ii) a utilidade de uma abordagem híbrida, combinando análise factorial com regressão; iii) a importância fundamental que o efeito escala espacial desempenha no estudo da heterogeneidade e dos spillovers e, finalmente, iv) uma metodologia inovadora para analisar spillovers sem assumir aprioristicamente uma estrutura espacial específica de difusão espacial. Esta metodologia considera a matriz de pesos espaciais (W) desconhecida e estimatima as interações espaciais dentro e entre submercados habitação.

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On the 25th anniversary of Economic Affairs this article examines the history of the journal from its founding in 1980 to the present. It presents an account of the key themes that have featured in the journal during that time and argues that its most important contribution has been to explain how markets operate and why well-meaning government intervention seldom improves upon the imperfect outcomes produced by markets.

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Consumer confidence indices (CCIs) are a closely monitored barometer of countries’ economic health and an informative forecasting tool. Using European and US data, we provide a case study of the two recent stock market meltdowns (the post-dotcom bubble correction of 2000–2002 and the 2007–2009 decline at the beginning of the financial crisis) to contribute to the discussion on their appropriateness as proxies for stock markets’ investor sentiment. Investor sentiment should positively covary with stock market movements (DeLong, Shleifer, Summers, and Waldmann 1990); however, we find that the CCI–stock market relationship is not universally positive.We also do not find support for the information effect documented in the previous literature, but identify a more subtle relationship between consumer expectations about future household finances and stock market fluctuations.

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In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

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The large increase of renewable energy sources and Distributed Generation (DG) of electricity gives place to the Virtual Power Producer (VPP) concept. VPPs may turn electricity generation by renewable sources valuable in electricity markets. Information availability and adequate decision-support tools are crucial for achieving VPPs’ goals. This involves information concerning associated producers and market operation. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, focusing mainly in the information requirements for adequate decision making.

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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 is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

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Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi- Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.

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The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.