McNeil, A., Frey, R. and Embrechts, P. (2015). Quantitative Risk Management: Concepts, Techniques and Tools. Princeton University Press.
Learning Objectives
Ability to measure market risk from financial data based on both numerical and analytical methods. Ability to write basic MATLAB code.
Prerequisites
To take this exam, the student must have passed the 1st-year exams: Quantitative Finance and Derivatives; Computational Finance.
Teaching Methods
Classes and tutorials.
Further information
Class attendance is highly recommended.
Type of Assessment
Attending students: 3 intermediate written tests and 2 group assignments.
Non-attending students: written test on the whole program of the course.
Course program
Introduction to MATLAB. Risk taxonomy. Stylized facts related to financial data. Risk measures based on loss distributions. Coherent and Convex risk measures. Spherical and Elliptical distributions. Extreme Value Theory. Dependence modeling with copulas. Standard methods for market risk. Implied and Realized volatility measures.