Finance and insurance

Educational objectives

The course aims at introducing students to the theory, the techniques and the advanced practice of econometric analysis in economics and in finance, with special regard to: measuring non observable economic variables, verifying economic theories, forecasting future pattern of real economic and financial variables, evaluating the effects of macro and micro-economic policies.
Furthermore, the course will also address some situations where the assumptions of the Ordinary Least Squares estimator do not hold and thus classical regression analysis is not applicable. Particular attention will be paid to models for limited dependent variables and to Vector Autoregressive (VAR) models. Concepts will be presented by means of an extensive use of examples with real economic and financial data, in order to achieve a better understanding of the theoretical concepts and to introduce the students to the practice of computationally-based estimation and validation techniques.
Students who pass the exam will know and understand the basic instruments of econometrics and their use to solve empirical economic and financial problems. The discussion of case-studies will make students able to apply econometric tools to answer economic and financial questions of interest.
Students will be able to autonomously conduct and comment empirical analyses, also evaluating possible violations of the basic assumptions.
Finally, students will be able to interpret and present the results coming from the estimated models, both in oral and in written form.

Educational objectives

The course introduces and develops the most important risk measures for risk management, like Value at Risk and Expected Shortfall, teaches how to build models that are able to estimate and to forecast them using financial data. During the course we will build static and dynamic models to forecast future risk situations. Distinct risk measures have different impacts on asset pricing, portfolio hedging, capital allocation, and investment performance evaluation. Moreover statistical tools and systemic risk measures will be considered in order to evaluate the interconnection in risk propagation between financial systems. Real data will be analyzed using the most common statistical software.
Students who pass the exam will know the main concepts and procedures for quantifying model risk and for evaluating systemic risk also in a forecasting framework, using backtesting to find the best model.
Students who pass the exam will acquire skills for real data analysis. Starting from real data, they will be able to find the best model to control risk in a financial environment.
They will also be able to analyze in a critical way the obtained results, highlighting advantages and disadvantages of the chosen procedures. Students’ skills are stimulated by tackling real case studies and developing a research project which will be discussed in class. The evaluation of the report will also concern students’ communication skills and their ability to explain what they learned and the results of the quantitative analysis.
The deep comprehension of the learned methodologies, will allow students to tackle risk problem related with the risk management environment both from a job and from a research point of view.

Educational objectives

The aim of the course is to provide students with the advanced quantitative tools for developing an economic capital model to measure and control the financial stability of Banks, Investment Funds and Insurances, in accordance with the international rules imposed by Regulators. Main topics of the course are: (a) to define a quantitative model of a measure of economic value (e.g., EVA, embedded value, economic capital), (b) to apply risk measures and to demonstrate how to use them in an economic capital theoretical framework, (c) to propose techniques of allocation/appropriating the “cost” of risk/capital/hedge strategy to business units in order to gauge risk adjusted performances (e.g., returns on marginal capital).

Knowledge and comprehension.

After attending the course, students will be able to know the evaluation methods of capital requirements and to understand the results of mathematical models used to control the risk exposure of a financial entity.

Ability to apply knowledge and comprehension.

At the end of the course, students will be able to use advanced computational tools to evaluate financial stability of financial institutions in accordance with the international regulation and to apply a right knowledge in their use to monitor the stability level of a bank, an investment fund and an insurance company.

Judgment skills.

At the end of the course students will be able to understand the results derived from a specific risks aggregation formula adopted to calculate the capital allocation and to explain the contribution of each risk source (interest risk, equity risk, spread risk, concentration risk, correlation risk, operational risk, etc.) to the entity financial stability.

Communication skills.

After passing the exam, students will be able to explain and discuss about the arguments treated during the course, giving their comments and remarks on the use of the quantitative tools learnt.

Self-learning skills.

After passing the exam, students will have a knowledge of the advanced quantitative and technical tools for capital requirements evaluation under a risk based approach that will permit them to face future studies and applications in the risk management sector.