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Data Science Training for Finance and Risk Analysis
| Nome: | Descrição: | Tamanho: | Formato: | |
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| 1 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
The main discussion of this paper is a method of data science training, which allows responding to the complex challenges of finance. To create and deploy financial models for risk management, the ability to incorporate new data and Big Data sources, as well as benefit from emerging technologies such as web technologies, remote data collection methods, user experience Platforms, and ensemble machine learning methods, becomes increasingly important. Automating, analysing, and optimizing a set of complex financial systems requires a wide range of skills and competencies that are rarely taught in typical finance and econometrics courses. Adoption of these technologies for financial problems necessitates new skills, and knowledge about processes, quality assurance frameworks, technologies, security needs, privacy, and legal issues. In this paper, I discuss a pedagogical approach for data science training in finance and risk analysis, with a graphical summary of necessary skills. A case study of active learning and learning by doing for financial data science course is presented, following with the results of a teaching experience of this course, online and in-person, with a combination of diferent technologies and platforms in an integrated manner. The outcomes of an online Q/A on the Kaggle competition platform, an online book club, an online video platform, and an online discussion group for this course are presented with their advantages and disadvantages, and vulnerabilities.
Descrição
Ashofteh, A. (2022). Data Science Training for Finance and Risk Analysis: A Pedagogical Approach with Integrating Online Platforms. 40-41. Abstract from 9th International Conference on Risk Analysis (ICRA9), Perugia, Italy. http://icra9.unipg.it/wp-content/uploads/2020/02/BOA_ICRA9.pdf
Palavras-chave
Data science Finance Risk Pedagogical Active learning