Oil prices assumptions in macroeconomic forecasts: should we follow futures market expectations?

In macroeconomic forecasting, in spite of its important role in prices and activity developments, oil prices are usually taken as an exogenous variable for which assumptions have to be made. This paper evaluates the forecasting performance of futures markets prices against other popular technical procedure, the carry-over assumption. The results suggest that it is almost indifferent to opt for the futures market prices or the carry over assumption for short-term forecasting horizons (up to 12 months), while, for longer-term horizons, they favour the use of futures market prices. However, as futures markets prices reflect the markets expectations for the world economic activity, futures oil prices should be adjusted whenever the market expectations for the world economic growth are different from the values underlying the macroeconomic scenarios in order to assure fully internal consistency of those scenarios.

Learning Equivariant Representations

State-of-the-art deep learning systems often require large amounts of data and computation. For this reason, leveraging known or unknown structure of the data is paramount. Convolutional neural networks (CNNs) are successful examples of this principle, their defining characteristic being the shift-equivariance. By sliding a filter over the input, when the input shifts, the response shifts by the same amount, exploiting the structure of natural images where semantic content is independent of absolute pixel positions. This property is essential to the success of CNNs in audio, image and video recognition tasks. In this thesis, we extend equivariance to other kinds of transformations, such as rotation and scaling. We propose equivariant models for different transformations defined by groups of symmetries. The main contributions are (i) polar transformer networks, achieving equivariance to the group of similarities on the plane, (ii) equivariant multi-view networks, achieving equivariance to the group of symmetries of the icosahedron, (iii) spherical CNNs, achieving equivariance to the continuous 3D rotation group, (iv) cross-domain image embeddings, achieving equivariance to 3D rotations for 2D inputs, and (v) spin-weighted spherical CNNs, generalizing the spherical CNNs and achieving equivariance to 3D rotations for spherical vector fields. Applications include image classification, 3D shape classification and retrieval, panoramic image classification and segmentation, shape alignment and pose estimation. What these models have in common is that they leverage symmetries in the data to reduce sample and model complexity and improve generalization performance. The advantages are more significant on (but not limited to) challenging tasks where data is limited or input perturbations such as arbitrary rotations are present

Building a hurricane risk map for continental Portugal based on loss data from hurricane Leslie

A complete model to analyse and predict future losses in the property portfolio of an insurance company due to hurricanes is proposed. A novel statistical model, in which weather data is not required, is considered. Climate data may not be reliable, or may be difficult to deal with or to obtain, hence we reconstruct the storm behaviour through the registered claims and respective losses. The model is calibrated using the loss data of the property portfolio of the insurance company Fidelidade, from hurricane Leslie, which hit the center of continental Portugal in October 2018. Several scenarios are simulated and risk maps are built. The simulated scenarios can be used to compute risk premiums per risk class in the portfolio. These can be used to adjust the policy premiums accounting for a storm risk. The risk map of the company also depends on its portfolio, namely its exposure, providing a hurricane risk management tool for the insurance company.info:eu-repo/semantics/publishedVersio

Portfolio diversification using Bitcoin

Mestrado em FinançasNormalmente, as Bitcoins são associadas a um lado mais controverso e ilegal - Bitcoin como meio de chantagem a pessoas ou empresas. Esquemas de pirâmide (Ponzi) ou ainda meio de pagamento no mercado negro, geralmente na dark-web. Mas, existem investidores que estão a utilizar Bitcoin como um ativo nos seus investimentos, seja numa estratégia mais passiva seja mais ativamente, com compra e venda consoante as flutuações cambiais. O aspeto negativo deste ativo financeiro é a sua volatilidade Apesar de, atualmente, Bitcoins e outras cripto moedas se encontrarem numa zona cinzenta, ou vazio legal, e serem um ativo de elevado risco, existe a possibilidade de estas pertencerem a portfolios de investimento, como agente de diversificação. Um agente diferente e recente, mas algo possível. Esta dissertação tem, portanto, como objetivo, analisar se a Bitcoin pode ser um agente diversificador num portfolio eficiente e bem diversificado.Usually, we associate Bitcoin with the dark side of the finance world - Bitcoin as a mean for online blackmail or scam, the black market or even for Ponzi schemes, where Bitcoin and other digital currencies are used as mean of payment, instead of physical currency. But, there are also investors who are using Bitcoin as an investment asset, whether for buy and hold strategies or trading The downside of this investment asset it is the volatility Although risky and legally in a grey zone, it can be used in an investment portfolio as a diversification agent, an odd one but perhaps feasible. The aim of this thesis is to analyze if Bitcoin can as a diversification agent in an efficient and well diversified portfolio.info:eu-repo/semantics/publishedVersio

Nonlinear seismic analysis of existing RC school buildings: the “P3” school typology

The seismic assessment of existing school buildings is an important issue in earthquake prone regions; such is the case of the Algarve, which is the southern region of Portugal mainland. Having this problem in mind, the PERSISTAH project (Projetos de Escolas Resilientes aos SISmos no Território do Algarve e de Huelva, in Portuguese) aimed to develop a computational approach enabling the damage evaluation of a large number of individual school buildings. One of the school typologies assessed was the so-called “P3” schools. This typology is composed of several different modules that are combined in different manners depending on the number of students. Each module was built in accordance with architectural standardised designs. For this reason, there are many replicas of these modules all over the Algarve region. The structural system of each module is composed of a frame of reinforced concrete (RC) elements. Nonlinear static seismic analysis procedures were adopted to evaluate the structural seismic behaviour, namely by using the new concept of performance curve. Based on the obtained results, it was possible to conclude that the seismic safety of this type of school building is mainly ruled by the shear capacity of the columns. This study also shows the difficulties of carrying out accurate seismic assessments of existing buildings using the methods of analysis that are established in the Eurocode 8.info:eu-repo/semantics/publishedVersio