The effects Ishares IBovespa index fund creation on the liquidity of underlying stocks

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

The impacts of free trade agreements on use of antidumping

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

Intraday volatility

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

Fearful asymmetry: An analysis of pre-earnings abnormal returns

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

Factor analysis in the stock market: An application to statistical arbitrage

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

Proposta de abordagem para gestão de ocorrências em Serviços de Sangue

RESUMO: A gestão de ocorrências, sendo um requisito, quer legal, ao nível da regulação, quer normativo, tal como surge na ISO 9001, é um componente crítico para garantir a melhoria contínua um Serviço de Sangue, dado ter como objetivo a satisfação contínua dos requisitos dos dadores e recetores. A gestão eficaz, mas com eficiência, depende, também da eficácia da abordagem para gestão de ocorrência, nomeadamente, através da geração de correções, ações corretivas e ações preventiva eficazes. Esta dissertação discute a relevância, propondo um modelo de abordagem de gestão da qualidade conforme com os requisitos da lei fundamental da regulação de Serviços de Sangue, DL 267/2007, e com a norma global para sistemas de gestão da qualidade, ISO 9001. Esta abordagem usada descreve as várias etapas para a gestão eficaz de ocorrências, desde o seu relato, à sua classificação, tratamento com medição e análise risco associado e verificação da eficácia das ações tomadas. A eficácia do modelo teórico proposto foi verificado através da sua passagem para algoritmo informático num software comercial. Foi evidenciado neste software o cumprimento dos requisitos da abordagem teórica, pelo que a aplicação informática está conforme com os requisitos estabelecidos num procedimento documentado. Foi evidenciado, também, a rastreabilidade dos dados ao longo e toda a metodologia. A utilização de uma ferramenta informática também acrescentou valor ao modelo teórico, dado o acesso a toda a informação ser mais célere e de fácil acesso, quando comparado com o uso em suporte de papel.---------ABSTRACT: The issues management is a law requirement intended for regulation of “Blood Banks” and a quality management global requirement from ISO 9001. It is a critical activity, intended to to ensure continuous improvement on “Blood Bank”. Its goal is the continuous satisfaction of blood donors and transfusion recipients. Effective management and efficiency also depend on the effectiveness of the management of occurrence approach, namely in successful corrections, corrective actions and preventive actions. This paper discusses the relevance and it proposes a model approach to quality management according to the requirements of the fundamental law of regulation of “Blood Bank”, DL 267/2007, and according to the global standard for quality management systems, ISO 9001. This approach describes the various steps for effective management of incidents, such as his account, its classification, measurement and treatment using risk analysis and verification of the effectiveness of actions taken. The efficiency of the proposed theoretical model was verified through its transition to a computer algorithm trading software. It was demonstrated in this software that the requirements of the theoretical approach has been fulfilled by the computer application, which complies with the requirements established in a documented procedure. It was also evident that traceability of data across the methodology. The use of a software tool also added value to the theoretical model due to the access to all information to be faster and more easily accessible, when compared to paper.

Individual and aggregate money demands

I construct a model in which money and bond holdings are consistent with individual decisions and aggregate variables such as production and interest rates. The agents are infinitely-lived, have constant-elasticity preferences, and receive a fraction of their income in money. Each agent solves a Baumol-Tobin money management problem. Markets are segmented because financial frictions make agents trade bonds for money at different times. Trading frequency, consumption, government decisions and prices are mutually consistent. An increase in inflation, for example, implies higher trading frequency, more bonds sold to account for seigniorage, and lower real balances.

Fossil fuel dependence and interfuel substitution in the electricity sector of Western European countries between 1990-2011

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

An intertemporal pricing model for CO2 allowances: The impact of the clean development mechanism

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

Exploring the predictive power of Google searches over the US stock market

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

Pricing of exchange traded funds

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

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

Evidence of market anomalies in the Eurozone: A practical implementation

A Work Project, presented as part of the requirements for the Award of a Master’s Double Degree in Finance and Financial Economics from NOVA – School of Business and Economics and Maastricht University

An analog model for global macro investing

This study proposes a systematic model that is able to fit the Global Macro Investing universe. The Analog Model tests the possibility of capturing the likelihood of an optimal investment allocation based on similarity across different periods in history. Instead of observing Macroeconomic data, the model uses financial markets’ variables to classify unknown short-term regimes. This methodology is particularly relevant considering that asset classes and investment strategies react differently to specific macro environment shifts.

Predicting market direction with hidden Markov models

This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.