Educational objectives The course introduces students to the principles, techniques, and advanced practice of econometric analysis for economic and financial problems. It focuses on the measurement of economic and financial variables, forecasting their future evolution, evaluating the effects of macro- and microeconomic policies, and the quantitative modeling of risk. Topics are presented with extensive applications to real-world economic and financial data, facilitating a deeper understanding of the concepts and practical experience with estimation and validation techniques. By the end of the course, students will have acquired fundamental knowledge of financial econometric models and tools and will be able to apply them to real-world problems. They will be able to critically select the most appropriate models for each problem, implement and calibrate parameters using computational tools, and simulate, analyze, and evaluate complex financial scenarios. Students will conduct independent empirical analyses, critically assessing the validity of model assumptions in practical financial contexts. They will be able to interpret and present the results of applied models, both orally and in writing, using appropriate technical language and a specialized glossary. Students will also gain the foundation and tools to continue and autonomously develop their studies in the course subject, enabling ongoing learning of new quantitative methodologies for professional and research applications.
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Educational objectives This course provides students with the opportunity to consolidate and apply the knowledge acquired in the year’s coursework by observing, describing, and interpreting phenomena in finance and risk management. The training activities, organized in collaboration with institutions and companies, cover professional communication, emerging technologies, soft skills, and management, aiming to develop competencies that enable students to understand the challenges and opportunities arising from the use of technological tools and relational skills for analyzing, managing, and presenting financial phenomena.
At the end of the course, students will have acquired proficiency in using specific software and platforms, such as Matlab and Python applied to financial contexts, and key transversal skills necessary for teamwork, conflict management, professional interviews, and emotional awareness. Practical laboratories, group work, and collaborative sessions foster autonomy in the evaluation and selection of the most suitable analysis tools and methodologies, as well as communication skills for presenting and arguing results, and the ability to independently update their knowledge on emerging techniques. In particular, the course strengthens the soft skills required to work effectively in collaborative contexts and manage complex professional situations, preparing students for careers in finance, risk management, or further advanced studies.
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