MVE220 / MSA400 Financial risk
The exams are now corrected
This course covers some modern techniques and concepts for measuring risk in a financial setting. It requires no prior knowledge of finance, but is quite mathematical.
This page contains the program of the course: lectures and projects. Other information, such as learning outcomes, teachers, literature and examination, are in a separate course PM.
Literature
Stuart Coles, Introduction to Statistical Modeling of Extreme Values. Available in STORE or here. We will mainly cover 2.6.3-4, 2.6.7, 2.7, 3.1-4, 4. Everything related to profile likelihood is omitted.
Carl Lindberg, Lecture notes:
Comment on Structural Credit Risk 20231211.pdf
ExtremeValueTheory 20240306.pdf
Fisher Information 20240123.pdf
Guest Lecture:
Credit Risk Modelling at Norion Bank.pdf
Risk Project Slides
Enron Niclas Lindmark Daniel Alsén.pdf
Faulty CDOs and Stupidity - Brechter & Krantz.pdf
The Financial Crisis 2007 Krantz Brechter.pptx
THE MENZGOLD GHANA LIMITED SAGA 1.pptx
TheasianfinancialcrisisEkh&Nilsson.pptx
Old exams
Example_exam_MVE220.pdf
Program
The schedule of the course is in TimeEdit.
Lectures
| Week | Topic | Content |
|---|---|---|
| 1 | Introduction to Financial Risk, Extreme value theory | Derivation of the extreme value distributions and the Generalized Pareto Distribution |
| 2 | Statistical Modeling: Classical EVT with Statistics, Threshold models, Value-at-Risk, Expected shortfall | Distributions, independence, Fisher Information |
| 3 | Week 2 continued, Risk projects | General EV distributions with statistics |
| 4 | CHARM days, Risk project presentations | Generalized Pareto distribution, Peaks over Threshold |
| 5 | Guest Lecture on 13/2, Insurance risk, structural Credit risk | Cramér-Lundberg model, structural credit risk models |
| 6 | Markov Theory, Credit risk | Basic properties, hitting times, Strong Markov property, invariant distributions, Markov based credit risk models. |
| 7 | Project supervision | |
| 8 | Project supervision |
Recommended exercises
Learn all the derivations and examples covered in the lectures.
Statistical project
Each student is welcome to apply threshold models to a financial time series, e g from a stock or an equity index. The student should calculate VaR and Expected Shortfall for that time series, given an investment of 1 million "moneys" (I e, use SEK if you analyze Swedish stocks, USD if you analyze American stocks, and so on..). I will supervise these projects during week 8, and choose at least one exam question related to this particular problem, so doing the project can be regarded as studying for the exam. No bonus points are awarded for doing the projects.
Presentation risk project
Groups of 2 people will some time during week 7 present a topic related to financial risk (such as the Madoff scandal, Enron, LTCM, the Financial Crisis) during a 10 minute presentation. The presenting groups will hand in 1-2 pages (ChatGPT-tools are allowed, but check your facts!) The best presentations will be rewarded in the sense that I will choose exam questions from their presentations, so doing the project can be regarded as studying for the exam. No bonus points are awarded for doing the projects.
Guest lecture
There will likely be a guest lecture, held be a knowledgable industry practitioner. In that case, I will probably choose an exam question from that lecture, and alter the course schedule to fit that person's agenda.
Reference literature:
- Learning MATLAB, Tobin A. Driscoll. Provides a brief introduction to Matlab to the one who already knows computer programming. Available as e-book from Chalmers library.
- Physical Modeling in MATLAB 3/E, Allen B. Downey
The book is free to download from the web. The book gives an introduction for those who have not programmed before. It covers basic MATLAB programming with a focus on modeling and simulation of physical systems.
Course summary:
| Date | Details | Due |
|---|---|---|