The course aims at analyzing the main numerical methods for derivative pricing and risk managment, in particular: - tree methods; - finite differences methods (implicit, explicit, Crank-Nicholson) - Monte Carlo methods. At the end of the course, tudents are able to efficiently implement the previous methods, by using Matlab. Although no formal prerequisites is needed, the knowledge of the topics related to Stochastic Models for Finance and Mathematical Finance is strongly recommended.
The course is devoted to introducing the main numerical methods used for the calculation of financial quantities, for the evaluation of derivative instruments and for the management of financial risk. These numerical methods will be developed with Matlab software.
In particular, the following topics will be covered:
- Tree methods for derivatives evaluation.
- Monte Carlo methods: Euler scheme for the simulation of stochastic processes.
- Finite difference methods for the evaluation of European and American derivatives.
| Author | Title | Publisher | Year | ISBN | Note |
| L. Clewlow and C. Strickland | Implementing Derivatives Models | Wiley | 1998 | ||
| Desmond J. Higham e Nicholas J. Higham | MATLAB Guide | SIAM | 2005 | ||
| P. Glasserman | Monte Carlo Methods for Financial Engineering | Springer | 2004 | ||
| Fabrice D. Rouah, Steven L. Heston | The Heston Model and its Extensions in Matlab and C# | 2013 |
The final exam is a written test: programming exercises and open questions.
The possibility to participate remotely to the exam is guaranteed for all the requesting students.
The content, the allowed time and the evaluation criteria of the test will be the same both for the students in the classroom and for the remote ones.
