Risk Management
A.Y. 2019/2020
Learning objectives
At the end of the course, the student will possess an adequate mathematical terminology, learned the main quantitative and computational tools to be able to work in the risk management unit of a bank or insurance company.
Expected learning outcomes
At the end of the course, the student will know the basic elements of the Basel and Solvency regulatory frameworks for banks and insurance companies; will possess an adequate mathematical terminology and learned the main quantitative tools related to the study of risk variables and measures in quantitative risk management; will be able to recognize statistically the presence of an elliptical or heavy-tailed distribution and determine its influence on a risk portfolio; will be able to code a software for the computation of the capital reserve needed by a financial institution to comply with the above regulatory frameworks; will be aware of the basic quantitative tools to perform the stochastic aggregation of various typologies of risks.
Lesson period: Second trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second trimester
Course syllabus
- Prerequisites
- Overview of Basel and Solvency regulatory frameworks.
- Basic Concept in Risk Management: Risk Measures (VaR and ES).
- Light tailed versus Heavy-tailed distributions. Regularly varying distributions. The Mean excess function.
- EVT: the POT method.
- Risk Aggregation via copulas
- Elliptical Distributions and Coherent Risk Measures.
- Model Uncertainty.
- Standard methods for Market Risk
- Model Uncertainty and the Rearrangement Algorithm
- Operational Risk: some case studies.
- Overview of Basel and Solvency regulatory frameworks.
- Basic Concept in Risk Management: Risk Measures (VaR and ES).
- Light tailed versus Heavy-tailed distributions. Regularly varying distributions. The Mean excess function.
- EVT: the POT method.
- Risk Aggregation via copulas
- Elliptical Distributions and Coherent Risk Measures.
- Model Uncertainty.
- Standard methods for Market Risk
- Model Uncertainty and the Rearrangement Algorithm
- Operational Risk: some case studies.
Prerequisites for admission
Theory of Integration and elementary probability.
Teaching methods
Lectures with exercises (also group assignments) and programming in R
Teaching Resources
Quantitative Risk Management: Concepts, Techniques and Tools. Revised Edition.
AJ McNeil, R Frey and P Embrechts
Princeton University Press, Princeton, 2015
Dropbox shared folder with extra material
AJ McNeil, R Frey and P Embrechts
Princeton University Press, Princeton, 2015
Dropbox shared folder with extra material
Assessment methods and Criteria
Two assignments to be delivered, a written exam and an oral interview
SECS-S/06 - MATHEMATICAL METHODS OF ECONOMICS, FINANCE AND ACTUARIAL SCIENCES - University credits: 6
Lessons: 40 hours
Professor:
Puccetti Giovanni
Shifts:
-
Professor:
Puccetti GiovanniProfessor(s)