- Docente: Pietro Rossi
- Credits: 6
- SSD: SECS-S/06
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Quantitative Finance (cod. 8854)
Learning outcomes
The objective of the course is to address frontier topics in computational finance and muster the computational skills needed to tackle them. At the end of the course the student will have a working experience on selecting the most appropriate model and the capability to devise, and implement the numerical tools needed for problem at hand. The student will be able to judge the quality of the results from data analysis, and she will have enough knowledge to set up benchmarks to test for the accuracy of the numerical results. The topics addressed will refer to state-of-the-art issues in pricing, risk management and numerical techniques and programming languages. The student will be exposed, and gain proficiency, in rapid prototyping languages like Python and languages better suited to achieve high computational performance, like C/C++
Course contents
Generating Random Variables
Log Normal Processes
- Vanilla Options
- Cap and floor options
Jumps diffusion processes
- The Merton Model
- The Bernoulli model
- Kou double exponential model
- Variance Gamma model
Barrier Options
- The Feynman-Kac formula
- First passage time
- Knock-in and Knock-out options
Short Rate Models
- Vasicek model
- Hull-White model
Inflation Rate Models
- The Mercurio Model
- Jarrow-Yildirim Model
Readings/Bibliography
Lecture Notes from the Teacher
Seggested readings:
Monte Carlo method in financial engineering
by prof. Paul Glasserman
Assessment methods
At the end of the course studetns will have to realize a project consisting in a MC simulation to price options using one of the models introduced
Office hours
See the website of Pietro Rossi