Ciências e Tecnologia | Comunicações em congressos, conferências, seminários/Communications in congresses, conferences, seminars
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Percorrer Ciências e Tecnologia | Comunicações em congressos, conferências, seminários/Communications in congresses, conferences, seminars por Objetivos de Desenvolvimento Sustentável (ODS) "08:Trabalho Digno e Crescimento Económico"
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- An overview of the systemic risk measuresPublication . Basílio, Jorge; Oliveira, Amilcar; Mahmoudvand, RahimSystemic risk is a specific type of risk that refers to the risk of an complex system to be affect or even collapse due to individual action taken by the agents that compounds that complex system. The goals of this work is based on an axiomatic approach establish a critic description of the most relevant methods used in the determination of systemic risk and identify advantages and disadvantages associated to those methods.
- Fitting heavy Tail distributions with mixture modelsPublication . Basílio, Jorge; Oliveira, AmilcarThe normal probability distribution as assumption for financial returns have been recognized as inappropriate, and a source of inaccurate estimation of Value at Risk. Empirical evidence also have been shown that financial returns shows a more accentuated leptokurtic distribution when compared with a Normal distribution and also skewed. This is usually a cause of underestimated values of VaR, specially when the quantiles are very low. Therefore it is necessary to focus on the tail of the distribution and identify models to fit that behavior. We will highlight the differences between the quality of fitting in the tails of the distribution and the fitting for all the distribution. This work compares and interprets the results obtained by applying mixture models as a method to estimate the behavior on the extremes for heavy tail data distributions. This results will be then used to describe an analytical solution of VaR under mixture models.
- Preface of the “Symposium on Exploring Statistical Methodologies and Applications”Publication . Oliveira, Amilcar; Oliveira, Teresa A.
- Professional training for effective adoption of Generative AI in the corporate world: bridging the gapPublication . Guedes, Fernando; Rocio, Vitor; Martins, PauloThis position paper emphasizes the critical role of professional training in facilitating the effective adoption of Generative AI (GenAI) in the corporate world. GenAI, with its ability to create new content from existing data, holds immense potential for transforming business processes, enhancing decision-making, and driving innovation. However, the adoption of GenAI faces significant challenges, including a shortage of skilled professionals, high implementation costs, data privacy concerns, and the complexity of integrating these technologies into existing systems. To address these challenges, this paper highlights the importance of comprehensive education and training programs tailored to equip employees with the necessary skills and knowledge. Such programs should focus on developing technical competencies and understanding the operational implications of GenAI. By analyzing current literature and case studies, this paper identifies key strategies for effective training and outlines best practices for integrating GenAI into corporate environments. The findings underscore the need for a strategic approach to training that aligns with the evolving demands of AI-driven innovation. This includes continuous learning and development initiatives, the promotion of a culture of innovation, and the implementation of responsible AI practices. By investing in professional training, organizations can bridge the skills gap, mitigate risks, and fully leverage the transformative potential of GenAI technologies, ultimately gaining a competitive edge in the market. Through this comprehensive exploration, the paper advocates for the integration of robust training frameworks that support the sustainable adoption of GenAI, ensuring that businesses are well-prepared to navigate the complexities and opportunities of the digital age.
- Statistics and big data: different perspectivesPublication . Oliveira, Teresa A. ; Nunes, Sandra; Oliveira, AmilcarBig Data has become the new slang in the world of information collection and analysis. The researches we conduct and the data we collect continue to grow, due to rapidly expansion of technology. Disciplines such as Computer Science, Engineering, and Statistics play a key role in the analysis of big data, each with its specificity but all equally important, an opinion that is not shared by all, being the Statistic considered the weakest link. This work attempts to show that Statistics have a distinct and essential role in this new world of Big Data, showing that Statistics and Big Data denote a crucial union. We will start with a brief introduction to Big Data and the several existing definitions.