Long-term dependence in financial prices: evidence from the Belgian stock market returns

This article aims to contribute to the discussion of long-term dependence, focusing on the behavior of the main Belgian stock index. Non-parametric analyzes of the general characteristics of temporal frequency show that daily returns are non-ergodic and non-stationary. Therefore, we use the rescaled-range analysis (R/S) and the detrended fluctuation analysis (DFA), under the fractional Brownian motion approach, and we found slight evidence of long-term dependence. These results refute the random walk hypothesis with i.i.d. increments, which is the basis of the EMH in its weak form, and call into question some theoretical modeling of asset pricing. Other more localized complementary study, to identify the evolution of the degree of dependence over time windows, showed that the index has become less persistent from 2010. This may mean a maturing market by the extension of the effects of current financial crisis.

Long-term memory in financial prices: evidence from the Dutch stock market returns

Prepared for presentation at the Portuguese Finance Network International Conference 2014, Vilamoura, Portugal, June 18-20

O Plano geral de contabilidade angolano e o sistema de normalização contabilística de Portugal: uma análise comparada

Dissertação de Mestrado apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças, sob orientação da Professora Doutora Ana Maria Alves Bandeira

A política agrícola comum (PAC) e o comércio internacional - estudo econométrico do efeito da PAC sobre as exportações agrícolas portuguesas para a União Europeia (1975-2012)

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientadora: Professora Doutora Maria Clara Ribeiro Coorientadora: Mestre Maria Luísa Verdelho Alves

Negotiation mechanism for self-organized scheduling system with collective intelligence

Current Manufacturing Systems challenges due to international economic crisis, market globalization and e-business trends, incites the development of intelligent systems to support decision making, which allows managers to concentrate on high-level tasks management while improving decision response and effectiveness towards manufacturing agility. This paper presents a novel negotiation mechanism for dynamic scheduling based on social and collective intelligence. Under the proposed negotiation mechanism, agents must interact and collaborate in order to improve the global schedule. Swarm Intelligence (SI) is considered a general aggregation term for several computational techniques, which use ideas and inspiration from the social behaviors of insects and other biological systems. This work is primarily concerned with negotiation, where multiple self-interested agents can reach agreement over the exchange of operations on competitive resources. Experimental analysis was performed in order to validate the influence of negotiation mechanism in the system performance and the SI technique. Empirical results and statistical evidence illustrate that the negotiation mechanism influence significantly the overall system performance and the effectiveness of Artificial Bee Colony for makespan minimization and on the machine occupation maximization.

Desenvolvimento de código pictográfico para identificação de medicamentos

Trabalho de Projeto

Stochastic Framework for Strategic Decision-making of Load-serving Entities for Day-ahead Market

The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

Smart Grid Market Using Joint Energy and Ancillary Services Bids

The power systems operation in the smart grid context increases significantly the complexity of their management. New approaches for ancillary services procurement are essential to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. These approaches should include market mechanisms which allow the participation of small and medium distributed energy resources players in a competitive market environment. In this paper, an energy and ancillary services joint market model used by an aggregator is proposed, considering bids of several types of distributed energy resources. In order to improve economic efficiency in the market, ancillary services cascading market mechanism is also considered in the model. The proposed model is included in MASCEM – a multi-agent system electricity market simulator. A case study considering a distribution network with high penetration of distributed energy resources is presented.

Elspot: Nord Pool Spot Integration in MASCEM Electricity Market Simulator

The energy sector in industrialized countries has been restructured in the last years, with the purpose of decreasing electricity prices through the increase in competition, and facilitating the integration of distributed energy resources. However, the restructuring process increased the complexity in market players' interactions and generated emerging problems and new issues to be addressed. In order to provide players with competitive advantage in the market, decision support tools that facilitate the study and understanding of these markets become extremely useful. In this context arises MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), a multi-agent based simulator that models real electricity markets. To reinforce MASCEM with the capability of recreating the electricity markets reality in the fullest possible extent, it is crucial to make it able to simulate as many market models and player types as possible. This paper presents a new negotiation model implemented in MASCEM based on the negotiation model used in day-ahead market (Elspot) of Nord Pool. This is a key module to study competitive electricity markets, as it presents well defined and distinct characteristics from the already implemented markets, and it is a reference electricity market in Europe (the one with the larger amount of traded power).

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Incentive-based demand response programs designed by asset-light retailers for day-ahead market

Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.

Towards a unified European electricity market: The contribution of data-mining to support realistic simulation studies

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European Electricity Market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. The continuous transformations electricity markets have been experiencing over the years create the need to use simulation platforms to support operators, regulators, and involved players for understanding and dealing with this complex environment. This paper focuses on demonstrating the advantage that real electricity markets data has for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations will bring to the participant countries. A case study using MASCEM (Multi-Agent System for Competitive Electricity Markets) is presented, with a scenario based on real data, simulating the European Electricity Market environment, and comparing its performance when using several different market mechanisms.

Revisão, aplicação e avaliação dos mercados eletrónicos - emarket

Os mercados eletrónicos são sistemas de informação (SI) utilizados por várias entidades organizacionais distintas dentro de um ou vários níveis em termos das cadeias de valor económico (Journal Electronic Markets, 2012). Segundo (Bakos, 1998) têm um papel central na economia, facilitando a troca de informações, produtos, serviços e pagamentos. Durante o processo, é criado valor económico para o comprador, fornecedor, intermediários do mercado e para a sociedade em geral. O comércio eletrónico é o ato de realizar um qualquer tipo de negócio através de uma via eletrónica e é constituído por modelos diversificados onde se destacam o Business to Business (B2B) e o Business to Consumer (B2C). O modelo B2B possui uma quota de 90 % de todo o comércio, sendo esse sucesso intrinsecamente relacionado em grande parte às vantagens que as suas plataformas oferecem às empresas que inseridas nelas (Anacom, 2004). O âmbito principal deste trabalho é o estudo dos B2B, tendo sido para tal definidos os seguintes objetivos: Realizar a identificação do estado atual bem como a evolução dos mercados B2B em Portugal; Caraterização das funcionalidades das plataformas que atuam no tecido nacional e por fim fazer a criação de um conjunto de orientações de apoio a empresas que desejam fazer a inserção nestes mercados. Para serem alcançados os objetivos propostos na dissertação, foram inquiridas várias organizações ao mesmo tempo que foi realizada uma pesquisa de temas e artigos relacionados com os mercados eletrónicos e plataformas B2B, recorrendo a sites como a B-On.pt, e utilizando o motor de busca Google. Este relatório apresenta a seguinte estrutura: No capítulo 1 é apresentada a introdução teórica das matérias apresentadas nos capítulos seguintes; O capítulo 2 é centrado no comércio eletrónico, definições mais comuns e são demonstrados os modelos mais preponderantes do comércio eletrónico; No capítulo 3 são expostas todas as vertentes do modelo B2B, as principais plataformas B2B a atuar no tecido nacional, as suas funcionalidades e modo de operação bem como uma apresentação das principais plataformas a nível mundial; No capítulo 4 são apresentados um conjunto de tópicos de auxílio a empresas que desejem fazer a sua inserção neste tipo de mercados; Por último são descritas as principais conclusões retiradas na realização da dissertação. Em suma, este trabalho reúne um conjunto de dados e orientações úteis, decorrentes do estudo realizado de auxílio a empresas a aderirem aos mercados eletrónicos, visto ser uma abordagem promissora para as organizações.

Marketing experiencial, emoções, satisfação e lealdade

O marketing transacional apresenta-se nos dias de hoje insuficiente para fazer face às exigências de um consumidor mais participativo, seletivo e crítico. No mercado global, industrializado e em constante evolução tecnológica, é, cada vez mais, difícil obter um grau de diferenciação assente apenas nos benefícios funcionais e racionais. O marketing transacional evoluiu para o marketing relacional, constituindo o cliente o centro do processo de trocas. A economia das experiências alterou a forma como as marcas trabalham o mercado, introduzindo o conceito de experiências, o que por sua vez conceptualizou o marketing experiencial, orientado para a gestão da experiência do cliente, transformando o ato de consumo em algo memorável, cheio de estímulos sensoriais e emocionais, convertendo-se, por vezes, no próprio produto, seja ele de âmbito industrial, desportivo ou mesmo cultural. Este grau de envolvimento do cliente com a marca é elemento gerador de emoção, de satisfação, de lealdade e de valor. Este trabalho pretendeu analisar a importância e os componentes estimuladores do marketing experiencial e a sua relação com as emoções, satisfação e a lealdade dos consumidores no evento cultural “Serralves em festa 2013”. Para tal, utilizamos uma metodologia de investigação quantitativa, com recurso a análise de equações estruturais, suportada por uma pesquisa teórica. O estudo empírico realizado, baseado num inquérito por questionário, possibilitou obter uma amostra de 264 respostas válidas. Após a validação e melhoria das escalas de medida dos conceitos, os resultados destas e do modelo estrutural demonstraram valores adequados. Estudaram-se e comprovaram-se as relações previstas nas hipóteses, nomeadamente, a relação positiva do impacto das experiências no comportamento do consumidor, designadamente, na sua emoção e satisfação e o impacto destas na sua lealdade. Entre as variáveis estudadas foram obtidos interessantes níveis de correlação e capacidades preditivas.

Cantor exchange systems and renormalization

We prove a one-to-one correspondence between (i) C1+ conjugacy classes of C1+H Cantor exchange systems that are C1+H fixed points of renormalization and (ii) C1+ conjugacy classes of C1+H diffeomorphisms f with a codimension 1 hyperbolic attractor Lambda that admit an invariant measure absolutely continuous with respect to the Hausdorff measure on Lambda. However, we prove that there is no C1+alpha Cantor exchange system, with bounded geometry, that is a C1+alpha fixed point of renormalization with regularity alpha greater than the Hausdorff dimension of its invariant Cantor set.