Finance and insurance

Educational objectives

The course aims to provide an in-depth understanding of the theoretical principles and analytical methodologies of contemporary economics and monetary policy, with particular attention to the functioning of monetary and financial institutions and markets, and to monetary policy decisions in major economic systems.
Students will acquire a systematic understanding of advanced monetary policy theories, transmission mechanisms, and the ways in which expectations and strategic interactions among agents influence macroeconomic equilibria.
At the end of the course, students will be able to understand and critically analyse theoretical models and empirical evidence regarding the role and actions of central banks, evaluate the outcomes and limitations of monetary policies in different international contexts, and independently interpret the scientific and institutional debate on the topic. The course also aims to consolidate independent judgment in evaluating complex economic information and communication skills in presenting concepts and results, both in academic and professional contexts. The competences acquired will provide a solid methodological foundation for accessing post-graduate pathways, such as second-level master’s programs or doctoral research in economic–quantitative fields.

Educational objectives

The course provides students with the fundamental methods of econometrics applied to finance, aiming to analyse and interpret complex economic and financial phenomena through the processing and evaluation of high-variability data. Particular attention is given to linear and non-linear regression techniques, the management of endogeneity issues, and panel data analysis, combining methodological rigor with empirical application. At the end of the course, students will be able to recognize, understand, and apply the main tools of financial econometrics, formalize real-world problems in terms of econometric models, and critically analyse and interpret the obtained results. They will also be able to assess the adequacy of the methodologies employed, select the most appropriate models, and implement estimation procedures consistent with the model assumptions. The course approach promotes the development of independent judgment in the interpretation of empirical results, communication skills in the use of the technical-scientific language of the discipline, and autonomous learning abilities for exploring new quantitative analysis tools. The competences acquired will enable students to successfully approach subsequent quantitative courses and consolidate a rigorous analytical method applicable across various areas of empirical finance.

Educational objectives

The course aims to provide an in-depth understanding of the theoretical principles and analytical methodologies of contemporary economics and monetary policy, with particular attention to the functioning of monetary and financial institutions and markets, and to monetary policy decisions in major economic systems.
Students will acquire a systematic understanding of advanced monetary policy theories, transmission mechanisms, and the ways in which expectations and strategic interactions among agents influence macroeconomic equilibria.
At the end of the course, students will be able to understand and critically analyse theoretical models and empirical evidence regarding the role and actions of central banks, evaluate the outcomes and limitations of monetary policies in different international contexts, and independently interpret the scientific and institutional debate on the topic. The course also aims to consolidate independent judgment in evaluating complex economic information and communication skills in presenting concepts and results, both in academic and professional contexts. The competences acquired will provide a solid methodological foundation for accessing post-graduate pathways, such as second-level master’s programs or doctoral research in economic–quantitative fields.

Educational objectives

The course provides students with the fundamental methods of econometrics applied to finance, aiming to analyse and interpret complex economic and financial phenomena through the processing and evaluation of high-variability data. Particular attention is given to linear and non-linear regression techniques, the management of endogeneity issues, and panel data analysis, combining methodological rigor with empirical application. At the end of the course, students will be able to recognize, understand, and apply the main tools of financial econometrics, formalize real-world problems in terms of econometric models, and critically analyse and interpret the obtained results. They will also be able to assess the adequacy of the methodologies employed, select the most appropriate models, and implement estimation procedures consistent with the model assumptions. The course approach promotes the development of independent judgment in the interpretation of empirical results, communication skills in the use of the technical-scientific language of the discipline, and autonomous learning abilities for exploring new quantitative analysis tools. The competences acquired will enable students to successfully approach subsequent quantitative courses and consolidate a rigorous analytical method applicable across various areas of empirical finance.

Educational objectives

The course gradually introduces students to applied programming and the simulation of random phenomena in financial contexts, starting from the fundamentals of programming and requiring no prior experience. It provides skills in formalizing uncertainty, implementing probabilistic and stochastic models, and using simulation methods to analyze and interpret the dynamics of financial phenomena. By the end of the course, students will be familiar with the main probabilistic and stochastic models used to formalize problems under uncertainty and will be able to implement simulation models to study financial processes. They will develop practical skills in programming languages and applications to perform simulations and compare numerical results with analytical solutions. Students will be able to independently identify the most appropriate model for studying each financial phenomenon, analyze and understand financial dynamics, and assess the reliability and appropriateness of the results within the considered context. They will be able to communicate rigorously using precise formal language, clearly articulating hypotheses, results, and insights. Finally, students will have acquired a solid foundational knowledge and a systematic study method, essential for understanding more advanced techniques of quantitative modeling and simulation.

Educational objectives

The training and career-enabling skills development activities aim to strengthen students' transversal and practical skills, facilitating their entry into the workforce and preparing them for complex professional environments. These activities include seminars, workshops, internships, and online certification or micro-credential programs, in collaboration with leading companies and institutions. The goal is to enhance students' professional profiles with additional skills, improving adaptability, productivity, and the ability to address real-world situations in the financial, insurance, and technology fields. Students will participate in practical and collaborative experiences that foster independent judgment, critical thinking, analytical, and communication skills, acquiring valuable tools for defining and pursuing personal and professional goals. Upon completion of the program, students will be able to apply the transversal skills they have acquired, interact effectively with professionals and experts, and understand the dynamics of the business world.

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.

Educational objectives

The course offers students the opportunity to consolidate and apply the knowledge acquired in the same year's courses by observing, describing, and interpreting financial phenomena and related risk management. Dedicated training activities are provided through agreements with organizations and companies. The program encompasses the areas of business communication, new technologies, soft skills, and management, with the goal of developing skills that allow students to appreciate the challenges and opportunities that arise from technological and communication skills for a more complete understanding of the world (particularly the financial and insurance world).
By the end of the course, students will have mastered specific software and platforms, as well as fundamental soft skills for teamwork, conflict management, job interviews, and emotional awareness. Practical workshops for case study and data analysis, group work, and collaborative sessions foster independence in choosing tools and methodologies, communication skills for presenting and arguing results, and independent learning abilities to stay abreast of emerging techniques. Specifically, the course strengthens the soft skills needed for working in collaborative environments and for effective financial and risk management operations.

Educational objectives

The course introduces students to the main risk measures used in risk management, such as Value at Risk (VaR) and Expected Shortfall (ES), and to the construction of models that provide estimates of these measures using financial data. The course covers dynamic models evolving over time to forecast future risk. Various financial risk measures are introduced, with discussion of their differing impacts on asset pricing, capital allocation, portfolio decisions, and investment strategies. Systemic risk indices are also presented to evaluate risk propagation within interconnected economic and financial systems. Students will gain theoretical knowledge of risk models and practical techniques for quantifying risk. They will be able to assess the appropriateness of different measures depending on the problem, using backtesting techniques, and perform predictive risk analyses. They will develop sensitivity to empirical data analysis and, starting from real problems, will define optimal strategies for measuring and controlling financial risk. Students will critically evaluate results, highlighting strengths and limitations of the adopted methods. Practical case studies will enhance critical thinking, presentation, and argumentation skills. By the end of the course, students will have acquired both formal foundations and operational tools to continue specializing in risk management in professional and research contexts.

Educational objectives

The course presents quantitative models and methods for the measurement and management of default and credit risk, as well as for the management of portfolios of credit derivatives. With particular reference to the Basel III framework and the introduction of Credit Value Adjustment (CVA), the course provides an in-depth analysis of the models used in counterparty risk assessment and in the determination of capital requirements. A significant part of the course is devoted to the mathematical and numerical modeling of CVA and Wrong-Way Risk, with applications to the design of counterparty risk mitigation strategies in derivatives portfolios. By the end of the course, students will have acquired the quantitative skills necessary for the analysis and management of credit risk in modern financial systems. They will be able to analyze and implement default and pricing models for financial instruments linked to credit events, such as defaultable bonds and Credit Default Swaps, and will possess the theoretical knowledge required to estimate default probabilities and expected losses in the event of insolvency. The practical component of the course, based on the application of advanced quantitative models through the use of specialized software, enables students to develop autonomy in model evaluation, calibration, and validation. Empirical analyses conducted on real data enhance students’ ability to interpret results in a professional risk management context and to present them appropriately, using a specific technical glossary. At the end of the course, students will have developed independent learning skills that will allow them both to pursue advanced studies in quantitative financial market analysis and risk management, and to establish themselves as professionals in these fields.