Browsing by Issue Date, starting with "2025-01"
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- Exploring the connection between sentiment analysis and stock market: macroeconomic forecasting with machine learningPublication . Chen, Chenjie; Bastos, João Afonso; Cornea-Madeira, AdrianaNews is an important source of market insight for investors. Sentiment analysis of news has become a useful tool for quantifying market sentiment and has shown a potential correlation with stock prices. This study aims to explore the relationship between sentiment in Chinese and English news and stock price volatility, as well as its potential predictive power. To this end, we collected Chinese news data from 2009 to 2023 and English news data from 2009 to 2020, covering two major stock markets in the world, including the Shanghai Stock Exchange (SSE) and the Standard and Poor’s 500 (S&P 500) Index. We applied a variety of sentiment analysis methods, including lexicon-based techniques and machine learning models. To account for language differences, we constructed specific sentiment analysis methods for Chinese and English news, respectively. We used various sentiment analysis models, such as Vader and Textblob, as well as more complex models, such as BERT, and we also introduced machine learning models, such as Long Short-Term Memory (LSTM) and Random Forest (RF), to explore the potential relationship between sentiment and stock prices. The study examines the performance and potential predictive power of sentiment analysis of news in different language contexts. In addition, the impact of global events (such as the COVID-19 pandemic) on sentiment and stock prices was also assessed. Preliminary results show that the relatively complex BERT model does not necessarily guarantee a high correlation with stock prices, while simple models may perform better in sentiment analysis. At the same time, the sentiment of Chinese news and English news are moderately correlated with long-term stock price changes in the market, and sentiment analysis also has a certain positive effect on prediction. However, when it comes to predicting trends, the relatively complex FinBERT can maintain relative accuracy, while the performance of simple models has dropped significantly. Keywords: Sentiment analysis; Time Series Forecasting; Stock market; Machine Learning.
- The impact of ESG compliance on REITs performancesPublication . Pozzi, Riccardo; Carvalho, Joaquim Montezuma deThis thesis provides a thorough examination of the financial and operational advantages linked to sustainability practices while examining the effect of Environmental, Social, and Governance (ESG) compliance on the performance of Real Estate Investment Trusts (REITs). The study uses econometric models to assess the correlation between ESG scores and important performance indicators, such as Net Asset Value (NAV), Funds From Operations (FFO), and Return on Assets (ROA), based on a dataset that spans 15 years and includes 181 REITs from various countries. The results show that ESG compliance has a beneficial impact on REIT performance, with governance benefits taking time to manifest while environmental and social factors drive financial stability and efficiency. ESG's strategic significance in investments is further supported by the fact that its advantages are most noticeable in the short to medium term
- Asymptotic solutions for linear ODEs with not-necessarily meromorphic coefficients: A Levinson type theorem on complex domains, and applicationsPublication . Cotti, Giordano; Guzzetti, Davide; Masoero, DavideIn this paper, we consider systems of linear ordinary differential equations, with analytic coefficients on big sectorial domains, which are asymptotically diagonal for large values of . Inspired by [60], we introduce two conditions on the dominant diagonal term (the L-condition) and on the perturbation term (the good decay condition) of the coefficients of the system, respectively. Assuming the validity of these conditions, we then show the existence and uniqueness, on big sectorial domains, of an asymptotic fundamental matrix solution, i.e. asymptotically equivalent (for large ) to a fundamental system of solutions of the unperturbed diagonal system. Moreover, a refinement (in the case of subdominant solutions) and a generalization (in the case of systems depending on parameters) of this result are given. As a first application, we address the study of a class of ODEs with not-necessarily meromorphic coefficients, the leading diagonal term of the coefficient being a generalized polynomial in z with real exponents. We provide sufficient conditions on the coefficients ensuring the existence and uniqueness of an asymptotic fundamental system of solutions, and we give an explicit description of the maximal sectors of validity for such an asymptotics. Furthermore, we also focus on distinguished examples in this class of ODEs arising in the context of open conjectures in Mathematical Physics relating Integrable Quantum Field Theories and affine opers (ODE/IM correspondence). Notably, our results fill two significant gaps in the mathematical literature pertaining to these conjectural relations. Finally, as a second application, we consider the classical case of ODEs with meromorphic coefficients. Under an adequateness condition on the coefficients (allowing ramification of the irregular singularities), we show that our results reproduce (with a shorter proof) the main asymptotic existence theorems of Y. Sibuya [80], [81] and W. Wasow [94] in their optimal refinements: the sectors of validity of the asymptotics are maximal, and the asymptotic fundamental system of solutions is unique.
- Internship report exploring blockchain adoption in supply chain management: challenges, opportunities, and sustainability impactsPublication . Lombard, Tanguy; Santiago, Joanna Katarzyna Krywalska Da SilveiraBlockchain technology has gained attention for its potential to transform supply chain management (SCM). This study focuses on understanding the key benefits, challenges, and barriers to adopting blockchain in SCM, while also exploring its integration with technologies like smart contracts and the Internet of Things (IoT). Although blockchain promises transparency, efficiency, and trust across supply chains, its adoption often faces burden like the resistance to change, the high implementation costs, and the legal uncertainties. To address these questions, this study used the Technology Acceptance Model (TAM) and Resistance Model (Davis, 1989) as a framework, guiding a qualitative study based on semistructured interviews with stakeholders involved in supply chain operations. Using MAXQDA for analysis, this study identified key benefits of the blockchain like improving the traceability, enhancing the operational efficiency, and its potential contribution to sustainability goals, aligning with SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production) (United Nations, n.d.). This study also discovered the barriers of the blockchain implementation like employee resistance, integration challenges with existing systems, and regulatory compliance issues. Finally, the findings of this research provide insights into the role of blockchain in advancing supply chain innovation and potential recommendations for businesses considering blockchain adoption.
- Marketing plan for eco utopia: a 100% renewable energy music festivalPublication . Delforge, Tanguy Jean A.; Chagas, Bernardo T.This project presents a marketing plan for Eco Utopia, a 100% renewable energy-powered music festival conceptualized by Utopia, an innovative events company. The plan’s primary objective is to position Eco Utopia as a leader in sustainable entertainment, increasing its brand visibility while creating a meaningful environmental and social impact. Set in Portugal’s iconic White Sand Mountains, Eco Utopia combines cutting-edge music experiences with a commitment to eco-friendly practices, catering to the growing demand for sustainable festivals. To develop this marketing plan, a Pragmatic Research Philosophy was applied, supported by Action Research as the guiding methodology. A mixed-methods approach was used to gather both qualitative and quantitative data, a survey of potential attendees and interviews with organizers of leading eco-festivals such as Pohoda and Øyafestivalen. The findings revealed strong consumer interest in renewable energy initiatives, waste reduction, and transparent sustainability practices, alongside a willingness to pay a premium for ecoconscious experiences. The insights gained informed the development of marketing strategies and marketingmix tactics designed to increase awareness, create community engagement, and ensure longterm viability. By addressing key challenges, leveraging digital platforms, and forming strategic partnerships, this marketing plan provides a clear roadmap for achieving Eco Utopia’s objectives and establishing it as a leader in the global festival industry.
- Youth players' subjective perception and experiences in German professional football academies: an explorative case studyPublication . Gronmayer, Jonah Lex; Guedes, Maria João CoelhoYouth academies of professional football clubs in Germany face the dual challenge of balancing competitive performance with ethical responsibilities often strained under the pressures of increasing commercialization. This study investigates existing challenges within such environments using a questionnaire-based research approach, gathering the subjective experiences and perceptions of 70 current and former German youth academy players. The findings reveal disparities based on contract status and gender inclusivity. While contracted players reported a more positive perception regarding financial support and transparency in decision-making processes, non-contract players described better experiences in terms of the mental and physical support received within these institutions. Furthermore, female participants reported substantially more negative experiences across almost all governance and ethics dimensions compared to their male counterparts, highlighting persistent gaps in inclusivity and support structures. These insights align with the goals outlined in SDG 5 (Gender Equality), emphasizing the need for equal opportunities and protections for all genders within sports development systems. This explorative research contributes to the broader discourse on ethics and governance in the development of professional football players, offering practical recommendations for policymakers, clubs, and stakeholders in the football industry. The findings underscore the importance of aligning youth development systems with SDG 4 (Quality Education), by promoting learning environments that are inclusive, supportive, and ethically grounded, as well as SDG 8 (Decent Work and Economic Growth), by advocating for fair treatment, mental and physical well-being, and equitable opportunities for young athletes. Future research could build upon these findings by exploring longitudinal data and conducting comparative studies across different countries and sports disciplines. Addressing the disclosed gaps will enable youth academies to better reconcile competitive aims with ethical imperatives ultimately fostering fairness, dignity, and sustainable growth within professional football. These findings thus aim to provide actionable insights for all policymakers and club stakeholders, emphasizing the necessity of embedding sustainable ethics into youth player development frameworks.
- Enhancing Bravilor Bonamat’s customer value proposition through refurbishmentPublication . Verheijen, Phoebe Isabelle; López, AníbalThis thesis investigates how integrating refurbished coffee machines into Bravilor Bonamat’s business model can enhance its customer value proposition. As sustainability increasingly influences consumer preferences and regulatory frameworks, the adoption of circular economy practices, such as refurbishment, presents an opportunity for Bravilor to align with environmental goals, cater to emerging market demands, and strengthen its competitive position. To address this, the study employed a strategic analysis using frameworks like the Business Model Canvas, PESTLE, and SWOT, complemented by qualitative insights from semi-structured interviews with employees and customers. The strategic analysis evaluated the company’s internal capabilities and external market influences, while the interviews provided perspectives on customer motivations, operational challenges, and business model preferences. The findings reveal that refurbishment offers significant potential to enhance Bravilor’s customer value proposition by combining affordability, quality, and sustainability. Refurbished machines meet customer demand for cost-effective alternatives, particularly among price-sensitive and eco-conscious segments, while aligning with circular economy principles by reducing waste and extending product lifecycles. Additionally, refurbishment reinforces Bravilor’s reputation for quality and innovation, differentiating it from competitors and appealing to a broader customer base. The servicebased model emerged as the most suitable approach, balancing operational efficiency with customer engagement while minimizing risks like cannibalization of new machine sales. In conclusion, integrating refurbishment allows Bravilor Bonamat to address modern market demands, enhance its sustainability efforts, and strengthen its premium brand image. By adopting a strategic approach to refurbishment, the company can expand its market reach and position itself as a leader in sustainable manufacturing practices. This study contributes to the academic understanding of circular business models in the coffee machine industry and offers practical recommendations for medium-sized manufacturers seeking to implement sustainable initiatives.
- Cancel culture in academia: a systematic literature reviewPublication . Martins, Madalena dos Santos Pedroso; Soares, Maria EduardaThis dissertation aims to investigate the impact of cancel culture in academia, analyzing the impact on professors, students, researchers and academic staff, and how it unfolds in different academic environments such as inside and outside classrooms, on departments, on events and paper publications. This topic was addressed through a Systematic Literature Review, which allowed the analysis of 27 relevant papersto provide insights on the research question “How impactful is the phenomenon of cancel culture nowadays on academia?”. The findings highlight eight main ideas such as how cancel culture has evolved over the years and the concerns it raises in academia, the factors that lead to variations of cancel culture effects, the sources and fields of attacks, the role of universities in this phenomenon, potential solutions to fight cancel culture and lastly the primary drivers of its emergence. Given the recency of the phenomenon of cancel culture, significant studies are still very limited. Therefore, this dissertation makes a novel contribution to the study of cancel culture by presenting a systematic literature review, a method that has not yet been applied to this topic, particularly within the academic context.
- The relationship between top managers’ personality and firms’ performancePublication . Botas, Rui Pedro Almeida; Guedes, Maria João CoelhoA investigação sobre a influência dos gestores de topo nas decisões de empresas e nos seus desempenhos possui um corpo de literatura promissor a investigar a relação entre a personalidade dos gestores de topo e o desempenho das empresas, no entanto, este tópico de pesquisa permanece com uma falta significante de consenso entre investigadores e tem sido amplamente inexplorado no contexto de empresas portuguesas. Este estudo propõe cobrir esta lacuna de pesquisa e acrescentar à literatura, utilizando uma abordagem inovadora que combina medidas objetivas e subjetivas de desempenho das empresas, o que tem sido uma metodologia negligenciada em pesquisas anteriores. Os dados foram recolhidos através de um questionário online usando uma amostra de gestores de topo de empresas portuguesas registadas com o intuito de analisar a influência dos cinco grandes traços de personalidade - extroversão, amabilidade, conscienciosidade, neuroticismo e abertura para a experiência – dos gestores de topo no desempenho das empresas. Os resultados apresentados neste estudo demonstram a associação positiva entre a extroversão e conscienciosidade dos gestores de topo e o desempenho subjetivo das empresas. Além disso, provou-se que o neuroticismo dos gestores de topo influencia negativamente o desempenho subjetivo das empresas enquanto que os seus níveis de amabilidade e abertura para a experiência não estão associados a este desempenho. Todavia, apenas a extroversão dos gestores de topo exibiu uma relação negativa com a performance objetiva das empresas sendo que a sua amabilidade, conscienciosidade e abertura para a experiência não impactam o desempenho objetivo das empresas, contrastando com a maioria dos estudos anteriores. Neste sentido, os nossos resultados indicam que um desempenho subjetivo não se traduz necessariamente num desempenho objetivo similar, o que sugere um viés potencial nas autoavaliações dos gestores de topo. Este estudo sublinha a influência promissora da personalidade dos gestores de topo e providencia potenciais perceções e explicações para as tomadas de decisões das organizações e para os seus resultados.
- Explainable machine learning models for the probability of credit defaultPublication . Elias, Ana Rita dos Santos; Bastos, João AfonsoThis dissertation addresses the challenge of balancing predictive accuracy and interpretability in credit risk assessment models within regulated financial environments. Using annual panel data from a company’s credit application in 2024, the study conducts a comparative analysis of traditional logistic regression and two advanced machine learning models: Catboost and Explainable Boosting Machine, EBM. Through empirical evaluation using standardized metrics for both accuracy and interpretability, the research demonstrates that modern machine learning models can effectively overcome the conventional trade-off between accuracy and interpretability. This study’s results revealed that both Catboost and Explainable Boosting Machine outperform logistic regression in predictive accuracy while meeting the interpretability standards required by regulatory frameworks. Catboost achieved superior predictive performance and utilized SHAP values for post-hoc interpretation. Meanwhile, EBM demonstrated competitive accuracy with built-in interpretability features. These findings indicate that financial institutions can modernize their credit risk assessment frameworks without compromising regulatory compliance or stakeholder trust. The present work contributes to the broader discourse on responsible machine learning in financial services, providing empirical evidence that advanced models can simultaneously achieve high accuracy and interpretability in credit risk assessment applications.