Cochineal, a precious source of red: cochineal dyes characterization by high performance liquid chromatography with diode array detection and principal component analysis

Presented at Faculdade de Ciências e Tecnologias, Universidade de Lisboa, to obtain the Master Degree in Conservation and Restoration of Textiles

Corpos (Dócies)

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Antropologia, Especialização em Culturas Visuais

Simulação de escoamentos fluviais com estruturas verticais nas margens do leito principal

Dissertação para obtenção do Grau de Mestre em Engenharia Civil – Perfil de Estruturas

Principal component analysis of the yield curve

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

O Conselho Nacional das Mulheres Portuguesas: A Principal Associação de Mulheres da Primeira Metade do Século XX (1914-1947)

Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Estudos sobre as Mulheres

Schottky principal G-bundles over compact Riemann surfaces

Fundação para a Ciência e a Tecnologia (FCT)- PhD grant SFRH/BD/37151/2007; projects PTDC/MAT/099275/2008; PTDC/MAT/119689/2010; PTDC/MAT/120411/2010; PTDC/MAT-GEO/0675/2012

Pair trading: Clustering based on principal component analysis

This study focuses on the implementation of several pair trading strategies across three emerging markets, with the objective of comparing the results obtained from the different strategies and assessing if pair trading benefits from a more volatile environment. The results show that, indeed, there are higher potential profits arising from emerging markets. However, the higher excess return will be partially offset by higher transaction costs, which will be a determinant factor to the profitability of pair trading strategies. Also, a new clustering approach based on the Principal Component Analysis was tested as an alternative to the more standard clustering by Industry Groups. The new clustering approach delivers promising results, consistently reducing volatility to a greater extent than the Industry Group approach, with no significant harm to the excess returns.