Portfolio optimization with options

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

Parametric portfolio policies: An application for a global tactical asset allocation model

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

A flexible navigation system for autonomous robots operating in heterogeneous environments

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

GuestCentric Systems and its internationalization to Brazil

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

User-centered design of the interface prototype of a business intelligence mobile application

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

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

Application of OSN in membrane cascade for purification of the API Amoxicillin

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Carbon monoxide, autophagy and cytoprotection in response to cerebral ischemia

Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina

Cancer theranostics: multifunctional gold nanoparticles for diagnostics and therapy

Doctorate in Biology, Specialty in Biotechnology

Electoral opportunism and fiscal policy before and after the EMU

A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

A distributed platform for the volunteer execution of workflows on a local area network

Thesis submitted in fulfilment of the requirements for the Degree of Master of Science in Computer Science

Heterogeneous computing with an algorithmic skeleton framework

The Graphics Processing Unit (GPU) is present in almost every modern day personal computer. Despite its specific purpose design, they have been increasingly used for general computations with very good results. Hence, there is a growing effort from the community to seamlessly integrate this kind of devices in everyday computing. However, to fully exploit the potential of a system comprising GPUs and CPUs, these devices should be presented to the programmer as a single platform. The efficient combination of the power of CPU and GPU devices is highly dependent on each device’s characteristics, resulting in platform specific applications that cannot be ported to different systems. Also, the most efficient work balance among devices is highly dependable on the computations to be performed and respective data sizes. In this work, we propose a solution for heterogeneous environments based on the abstraction level provided by algorithmic skeletons. Our goal is to take full advantage of the power of all CPU and GPU devices present in a system, without the need for different kernel implementations nor explicit work-distribution.To that end, we extended Marrow, an algorithmic skeleton framework for multi-GPUs, to support CPU computations and efficiently balance the work-load between devices. Our approach is based on an offline training execution that identifies the ideal work balance and platform configurations for a given application and input data size. The evaluation of this work shows that the combination of CPU and GPU devices can significantly boost the performance of our benchmarks in the tested environments, when compared to GPU-only executions.

Return Migration, Self-Selection and Entrepreneurship in Mozambique

Does return migration affect entrepreneurship? This question has important implications for the debate on the economic development effects of migration for origin countries. The existing literature has, however, not addressed how the estimation of the impact of return migration on entrepreneurship is affected by double unobservable migrant self-selection, both at the initial outward migration and at the final inward return migration stages. This paper uses a representative household survey conducted in Mozambique in order to address this research question. We exploit variation provided by displacement caused by civil war in Mozambique, as well as social unrest and other shocks in migrant destination countries. The results lend support to negative unobservable self-selection at both and each of the initial and return stages of migration, which results in an under-estimation of the effects of return migration on entrepreneurial outcomes when using a ‘naïve’ estimator not controlling for self-selection. Indeed, ‘naïve’ estimates point to a 13 pp increase in the probability of owning a business when there is a return migrant in the household relative to non-migrants only, whereas excluding the double effect of unobservable self-selection, this effect becomes significantly larger - between 24 pp and 29 pp, depending on the method of estimation and source of variation used.

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.

The good, the bad and the ugly: The fall and resolution of Banco Espírito Santo

This case study – and accompanying teaching note – briefly describes the history of the Espírito Santo family, a banking dynasty who led one of Portugal’s leading economic and financial groups, along with its “crown jewel”, Banco Espírito Santo. It chronicles how the corporate governance issues at BES allowed the family to exploit the bank, its shareholders and its customers, so as to support its unprofitable non-financial businesses. This left the bank in a poor financial situation, which deteriorated beyond control, leaving regulators – whose actions are also analysed here – with no alternative, amidst a severe liquidity crisis, but to apply a resolution measure, pinning large losses on junior bondholders and shareholders before recapitalising the bank.