2024
Authors
Freitas, JC; Pinto, AA; Felgueiras, O;
Publication
MATHEMATICS
Abstract
We model the financial markets as a game and make predictions using Markov chain estimators. We extract the possible patterns displayed by the financial markets, define a game where one of the players is the speculator, whose strategies depend on his/her risk-to-reward preferences, and the market is the other player, whose strategies are the previously observed patterns. Then, we estimate the market's mixed probabilities by defining Markov chains and utilizing its transition matrices. Afterwards, we use these probabilities to determine which is the optimal strategy for the speculator. Finally, we apply these models to real-time market data to determine its feasibility. From this, we obtained a model for the financial markets that has a good performance in terms of accuracy and profitability.
2024
Authors
Mousa, AS; Pinheiro, D; Pinheiro, S; Pinto, AA;
Publication
OPTIMIZATION
Abstract
We study the optimal consumption, investment and life-insurance purchase and selection strategies for a wage-earner with an uncertain lifetime with access to a financial market comprised of one risk-free security and one risky-asset whose prices evolve according to linear diffusions modulated by a continuous-time stochastic process determined by an additional diffusive nonlinear stochastic differential equation. The process modulating the linear diffusions may be regarded as an indicator describing the state of the economy in a given instant of time. Additionally, we allow the Brownian motions driving each of these equations to be correlated. The life-insurance market under consideration herein consists of a fixed number of providers offering pairwise distinct contracts. We use dynamic programming techniques to characterize the solutions to the problem described above for a general family of utility functions, studying the case of discounted constant relative risk aversion utilities with more detail.
2024
Authors
Figueiredo, AMS; Figueiredo, FO;
Publication
Research in Statistics
Abstract
Abstract.: We consider the headline indicators of the Europe 2020 agenda for the European Union countries for several years of the period 2010–2019 and their own national targets for these indicators. The indicators belong to five thematic areas: employment; education; research, development, and innovation; poverty and social exclusion; climate change; and energy. The main objective of this article is to analyze the dynamics and evolution of the EU countries and the Agenda Europe 2020 indicators over the period, taking into account the relations between the indicators for the EU countries along the years. In order to analyze the different data tables, we have used a three-way data methodology, the STATIS methodology. The results obtained show that the countries of the European Union as a whole have made progress towards the global targets set for the different indicators, with some countries making more significant progress than others. The indicators related to research, development, and innovation, as well as climate change and energy, are the ones where the most improvement is needed. The targets set individually for each country, less demanding for some and more daring for others, were generally already achieved in 2019 or are very close to being achieved. © 2025 Elsevier B.V., All rights reserved.
2024
Authors
Carvalho, M; Borges, A; Gavina, A; Duarte, L; Leite, J; Polidoro, MJ; Aleixo, SM; Dias, S;
Publication
KDIR
Abstract
The textile industry, a vital sector in global production, relies heavily on dyeing processes to meet stringent quality and consistency standards. This study addresses the challenge of identifying and mitigating non-conformities in dyeing patterns, such as stains, fading and coloration issues, through advanced data analysis and machine learning techniques. The authors applied Random Forest and Gradient Boosted Trees algorithms to a dataset provided by a Portuguese textile company, identifying key factors influencing dyeing non-conformities. Our models highlight critical features impacting non-conformities, offering predictive capabilities that allow for preemptive adjustments to the dyeing process. The results demonstrate significant potential for reducing non-conformities, improving efficiency and enhancing overall product quality.
2024
Authors
Soeiro, R; David, G; Neves, A;
Publication
Journal on Teaching Engineering
Abstract
2024
Authors
Monteiro, M; Pereira, F; Gaspar, M; Jorge, I; Poínhos, R; Oliveira, BM; Rodrigues, S; Afonso, C;
Publication
Acta Portuguesa de Nutrição
Abstract
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