- Docente: Marco Di Francesco
- Credits: 6
- SSD: STAT-04/A
- Language: English
- Teaching Mode: In-person learning (entirely or partially)
- Campus: Bologna
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Corso:
Second cycle degree programme (LM) in
Quantitative Finance (cod. 6692)
Also valid for Second cycle degree programme (LM) in Greening Energy Market and Finance (cod. 6693)
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from Nov 11, 2026 to Dec 10, 2026
Learning outcomes
At the end of the course the student knows how to transfer credit risk by means of swap arrangements (asset swaps and TRORS), and with credit derivatives. The student knows the analysis developed both on a single name basis (CDS) and on a multiname basis (CDO, CDX, iTraxx). The analysis is extended to large CDO, ABS and ABX.
Course contents
Bond market: The term structure of interest rates and bond pricing
Default-free bonds vs defaultable bonds. Green bonds vs traditional bonds.
The plethora of credit spreads and the puzzle of green premiums.
The basics of credit derivatives. The basic of weather derivatives.
Single name credit derivatives: ASW and CDS. The CDS-bond basis.
Single name credit models: structural and intensity-based models
Multi-name credit derivatives: credit indexes, first to default swaps. CDS index: Itaxx and CDX. Securitization: CDOs and ABS.
Multi-name credit models: copula functions
An introduction to credit valuation adjustment (XVA) with a case study.
Pricing Weather derivatives: models and assumptions. A case study: pricing options with payoff depending on temperature.
Readings/Bibliography
- Brigo D., Mercurio F., Interest Rate Models — Theory and Practice: With Smile, Inflation and Credit. Chapters 21-22-23
- D. Duffie and K. Singleton: Credit Risk: Pricing, Measurement and Management, Princeton University Press, 2003
- D. Lando: Credit Rsik Modeling: Theory and Applications. Princeton Series in Finance
- C. Bluhm, L. Overbeck and C. Wagner: An introduction to Credit Risk Modeling, Chapman & Hall/CRC, 2003
- M. Morini, "Understanding and Managing Model Risk. A practical guide for quants, traders and validators", Wiley, 2011.
- F. Benth, J. Benth: Modeling and pricing in financial market for weather derivatives, World Scientific, 2013
Teaching methods
Classroom lectures.
Theoretical lessons are accompanied and completed by interactive Lab sessions with real market data, examples and exercises.
Lessons are based on slides and Excel and Matlab or Python exercises.
Assessment methods
Before the exam, students must submit a paper on an assigned course topic, implemented in Python or MATLAB.
The learning test consists in a written exam to solve in 2 hours and which covers the entire course content. This exam is composed by 3 execises. During the exam it is permitted to use the calculator but it is not allowed to consult books or notes. It is attributed on average 10 points to each exercise. The students pass the exam with a score not lower than 18 points. There are not partial exams but just a full one at the end of the course
The students can take an oral exam about all the programme of the course. The final grade will be the average of the oral grade, the witten exam's grade and the assignment grade.
The maximum possible score is 30 cum laude (for both written and oral exam).
The grades are described as follows
< 18 failed
18-23 sufficient
24-27 good
28-30 very good
30 cum laude Excellent
Teaching tools
Teaching tools will be blackboard and slides.
Case studies analyses with real market data. Computer exercises.
Office hours
See the website of Marco Di Francesco