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.

Integração da análise energética na gestão Industrial de uma refinaria de açúcar

Mestrado em Engenharia Química - Optimização Energética na Industria Química

The impact of national cultures on international marketing strategy and subsidiary performance of portuguese SME’s

The dynamic of the international business and its multidimensional nature requires the understanding of the complexities of different contexts dictated by cultural differences between countries. The purpose of this paper is to study, in depth howsmall and medium-sized companies develop their international marketing mix strategy in their overseas subsidiaries. We use the theoretical construct of Hofstede (1980, 1991) in the dimensions of Power Distance (PD), Uncertainty Avoidance (UA), Individualism (IND), Masculinity (MASC) and Long-Term Orientation (LTO) to assess the cross cultural differences between countries and the business practices to analyze the adaptation or standardization of the international marketing mix strategy of foreign Portuguese subsidiaries. Ourstudy uses an exploratoryand qualitative methodology. We conducted semi-structured interviews in order to achieve a good understanding ofinternational marketing mix strategy of four companies from different sectors. Our results show that the national cultural differences have great influence in the marketing strategy of the subsidiary. The business practices adjustments in the subsidiary company that proved to be necessary conditions for their performance are conducted by the products augmented offerings concerning the characteristics of the product, design and brand name in order to meet the requirements and specificities of the host country of the subsidiary.

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

Processo de internacionalização das filiais portuguesas de construção civil para Angola: alguns estudos de caso (Mota-Engil, Soares da Costa e Conduril)

Dissertação apresentada no Instituto Superior de Contabilidade e Administração do Instituto Politécnico do Porto para obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientador: Professor Doutor José de Freitas Santos

Estratégia de centralização de compras e minimização de custos estudo de caso do Grupo Pinto & Cruz

Trabalho de Projeto apresentado ao Instituto de Contabilidade e Administração do Porto, para a obtenção do grau de Mestre em Auditoria, sob orientação de Doutora Alcina Dias

Relatório de estágio: Letra Zen, Comunicação e Marketing, Lda.

Relatório de Estágio apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Marketing Digital, sob orientação da Prof. Doutora Sandrina Teixeira

A fractional perspective to financial indices

The application of mathematical methods and computer algorithms in the analysis of economic and financial data series aims to give empirical descriptions of the hidden relations between many complex or unknown variables and systems. This strategy overcomes the requirement for building models based on a set of ‘fundamental laws’, which is the paradigm for studying phenomena usual in physics and engineering. In spite of this shortcut, the fact is that financial series demonstrate to be hard to tackle, involving complex memory effects and a apparently chaotic behaviour. Several measures for describing these objects were adopted by market agents, but, due to their simplicity, they are not capable to cope with the diversity and complexity embedded in the data. Therefore, it is important to propose new measures that, on one hand, are highly interpretable by standard personal but, on the other hand, are capable of capturing a significant part of the dynamical effects.

Estudo de Caso: Processos de orçamentação de obras

O relatório inserido na Unidade Curricular de DIPRE do Mestrado em Engenharia Civil do ISEP e desenvolvido no âmbito do estágio curricular realizado na HESPOR – Construções Lda, tem como objetivo caraterizar o mercado nacional da construção civil, os procedimentos da orçamentação, analisando os seus processos no âmbito dos concursos públicos em Portugal. Deste modo, o relatório tem por base a importância da orçamentação na construção civil e a caraterização do mercado da construção na atual situação financeira que o País se depara. Em seguida foi realizado um estudo da arte sobre os temas de custos e orçamentos, e ainda uma abordagem aos custos associados à construção civil. Depois de analisada toda a metodologia inerente à orçamentação, são caraterizados os processos das empresas do grupo para o ato de orçamentação. Foi abordado um estudo de caso para demonstrar como é elaborado o ato de orçamentação e foi realizada uma análise em função das propostas apresentadas com o intuito de afinar o processo de orçamentação de forma a tornar a proposta competitiva mas salvaguardando sempre a viabilidade, que é a estratégia adotada pela empresa.

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.

Virtual Power Players Internal Negotiation and Management in MASCEM

Electricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in very helpful sophisticated tools. This paper presents a new methodology for the management of coalitions in electricity markets. This approach is tested using the multi-agent market simulator MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), taking advantage of its ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market and internally, with their members in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. A case study using real data from the Iberian Electricity Market is performed to validate and illustrate the proposed approach.

Strategic Bidding for Electricity Markets Negotiation Using Support Vector Machines

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 simulates the electricity markets environment. 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 the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.

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.