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

Relating the spatial component and users interests to improve applications based on questions, petitions and participatory processes

Nowadays, participatory processes attending the need for real democracy and transparency in governments and collectives are more needed than ever. Immediate participation through channels like social networks enable people to give their opinion and become pro-active citizens, seeking applications to interact with each other. The application described in this dissertation is a hybrid channel of communication of questions, petitions and participatory processes based on Public Participation Geographic Information System (PPGIS), Participation Geographic Information System (PGIS) and ‘soft’ (subjective data) Geographic Information System (SoftGIS) methodologies. To achieve a new approach to an application, its entire design is focused on the spatial component related with user interests. The spatial component is treated as main feature of the system to develop all others depending on it, enabling new features never seen before in social actions (questions, petitions and participatory processes). Results prove that it is possible to develop a working application mainly using open source software, with the possibility of spatial and subject filtering, visualizing and free download of actions within application. The resulting application empowers society by releasing soft data and defines a new breaking approach, unseen so far.

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.