McNeil, A., Frey, R. and Embrechts, P. (2015). Quantitative Risk
Management: Concepts, Techniques and Tools. Princeton University
Press.
Learning Objectives
Ability to measure different types of 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" and "Computational Finance".
Teaching Methods
Classes, MATLAB tutorials, seminars from invited speakers.
Further information
Class attendance is recommended.
Type of Assessment
Attending students:
For attending students, the exam comprises a midterm written test, a
final written test and a group assignment related to the use of
the software MATLAB.
To qualify as an attending student, one must:
- submit the assignment within the due deadline;
- take the final test in June, July or September.
Participation to the midterm test is not compulsory.
The final grade will be the average of the grades of the final written test
and the assignment. The midterm test gives up to 3 additional points to
be added to the final grade. Active participation to classes may also give
additional points.
By rejecting the final grade, a student qualifies automatically as a non-attending
student (see below).
Non-attending students:
For non-attending students, the exam consists in a written test.
One of the exercises in the written test will be dedicated to verifying the
ability of writing basic code using the software MATLAB. For attending
student this ability is instead verified via the assignment.
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. Structural and reduced-form models for credit risk. Implied
and Realized volatility measures.