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 EconomicsAlthough being very profitable in the past years, the contrarian strategy, that tries to exploit the reversion of the stock prices after an overreaction of the new available information, had decline in the past years. To boost the profitability of that specific strategy, I tried to divide the assets of Eurostoxx 600 by some firm specific factors. The results of such improvement were not clear, since the new strategy beat the benchmark in some periods, but none systematically achieved better results in all the sample periods

Overcoming organisational tensions : strategic actions taken by social enterprises

This dissertation looks to explain the response of social enterprise in the face of organisational tensions from the implemented of strategic actions, mainly through company culture, organisational structure, and hiring process. Organisational tensions emerge through an organisation’s commitment to contradictory structures, cultures, practices and processes. The aim of this paper is to evaluate the strategic decisions taken by social enterprises operating in Portugal and explain how they allow them to deal with the internal tensions. To that purpose, a qualitative study was conducted based on semi-structured, face-to-face interviews to managers of social enterprise, and support through analysis of secondary data. The research concluded that the strategic actions helped the enterprises by ensuring a consistent level of internal communication, through the construction of a holographic company culture, and a hiring process that identified potential employees with a commitment to social causes. However, the findings proved that research into the field of social enterprises is still required to further support these finds. This dissertation was only able to explain the influence of these actions on a surface level, with more research needed to be able to justify the true implications. Nonetheless, this dissertation has made contributions to the field of social enterprises that can serve as a reference point for further research.Esta dissertação procura explicar a resposta da empresa social face às tensões organizacionais geradas a partir da implementação de ações estratégicas, principalmente por meio da cultura da empresa, estrutura organizacional e processo de contratação. As tensões organizacionais emergem através do vínculo de uma organização a estruturas, culturas, práticas e processos contraditórios. O objetivo deste artigo é avaliar as decisões estratégicas tomadas pelas empresas sociais que operam em Portugal e explicar como elas permitem lidar com as tensões internas. Para tal, foi realizado um estudo qualitativo, baseado em entrevistas semiestruturadas, presenciais, com gestores de empresas sociais. Para suporte, foram também executadas análises de dados secundários ao tema. A pesquisa concluiu que as ações estratégicas ajudaram as empresas sociais, garantindo um nível consistente de comunicação interna, por meio da construção de uma cultura de empresa homogénea e um processo de contratação que identificou o compromisso com as causas sociais dos potenciais trabalhadores. No entanto, este estudo provou também que pesquisa adicional no campo das empresas sociais é necessária para apoiar ainda mais estes resultados. Esta dissertação só foi capaz de explicar a influência das ações num nível superficial, sendo necessárias mais pesquisas para justificar e relacionar outras implicações. No entanto, esta dissertação contribui para a área do empreendedorismo social e poderá servir como ponto de referência para futuros estudos

Gaussian mixture model based probabilistic modeling of images for medical image segmentation

In this paper, we propose a novel image segmentation algorithm that is based on the probability distributions of the object and background. It uses the variational level sets formulation with a novel region based term in addition to the edge-based term giving a complementary functional, that can potentially result in a robust segmentation of the images. The main theme of the method is that in most of the medical imaging scenarios, the objects are characterized by some typical characteristics such a color, texture, etc. Consequently, an image can be modeled as a Gaussian mixture of distributions corresponding to the object and background. During the procedure of curve evolution, a novel term is incorporated in the segmentation framework which is based on the maximization of the distance between the GMM corresponding to the object and background. The maximization of this distance using differential calculus potentially leads to the desired segmentation results. The proposed method has been used for segmenting images from three distinct imaging modalities i.e. magnetic resonance imaging (MRI), dermoscopy and chromoendoscopy. Experiments show the effectiveness of the proposed method giving better qualitative and quantitative results when compared with the current state-of-the-art. INDEX TERMS Gaussian Mixture Model, Level Sets, Active Contours, Biomedical Engineerin

Segmentation and Optimal Region Selection of Physiological Signals using Deep Neural Networks and Combinatorial Optimization

Physiological signals, such as the electrocardiogram and the phonocardiogram are very often corrupted by noisy sources. Usually, artificial intelligent algorithms analyze the signal regardless of its quality. On the other hand, physicians use a completely orthogonal strategy. They do not assess the entire recording, instead they search for a segment where the fundamental and abnormal waves are easily detected, and only then a prognostic is attempted. Inspired by this fact, a new algorithm that automatically selects an optimal segment for a post-processing stage, according to a criteria defined by the user is proposed. In the process, a Neural Network is used to compute the output state probability distribution for each sample. Using the aforementioned quantities, a graph is designed, whereas state transition constraints are physically imposed into the graph and a set of constraints are used to retrieve a subset of the recording that maximizes the likelihood function, proposed by the user. The developed framework is tested and validated in two applications. In both cases, the system performance is boosted significantly, e.g in heart sound segmentation, sensitivity increases 2.4% when compared to the standard approaches in the literature

phyloDB: A framework for large-scale phylogenetic analysis

phyloDB is a modular and extensible framework for large-scale phylogenetic analyses, which are essential for understanding epidemics evolution. It relies on the Neo4j graph database for data storage and processing, providing a schema and an API for representing and querying phylogenetic data. Custom algorithms are also supported, allowing to perform heavy computations directly over the data, and to store results in the database. Multiple computation results are stored as multilayer networks, promoting and facilitating comparative analyses, as well as avoiding unnecessary ab initio computations. The experimental evaluation results showcase that phyloDB is efficient and scalable with respect to both API operations and algorithms execution.Comment: arXiv admin note: text overlap with arXiv:2012.1336

Characterization of soluble coffee and spent coffee grain extracts

Near the end of the Maillard reaction several polymer-like compounds are formed. These compounds can be extracted from byproducts of processed foods such as spent coffee grounds (SCG), allowing for their valorization. They possess several biological properties that may improve human health, such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, and prebiotic activities. The raw materials from where these compounds can be obtained (soluble coffee (SC) and SCG) also have some of the same biological properties, and therefore were characterized regarding these properties. Antioxidant activity as well as several physicochemical and thermal properties of soluble coffee and spent coffee grounds were characterized in this work.FCTCompete 2020Norte 2020Pedro Silva acknowledges the Foundation for Science and Technology (FCT) for his fellowship (SFRD/BD/130247/2017). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469 unit and COMPETE 2020 (POCI-01- 0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte.info:eu-repo/semantics/publishedVersio