Quantitative Finance and Insurance

The course aims at presenting some numerical techniques used in financial applications. The students will be working with Python.

Ability to handle numerical techniques suitable for financial problems in Python.

Teaching sessions will combine lectures and practical tasks in Python.

 

The final exam consists of a group project.

Projects must be chosen among a list that I will provide by the end of the course.

Groups should be composed of 2-4 people.

The discussion of the project will consist in a short presentation of the project.

The group is also expected to deliver a short report in pdf format, containing:

- a description of the financial and mathematical problem;

- a description of the solution of the problem;

- the explanation of the numerical algorithms adopted;

- Code scripts and user-defined functions;

- discussion of the results.

I will supervise the projects and assist the groups in making the code.

 

    - Financial applications with Python: 

* Option pricing using binomial trees
* Monte Carlo methods for option pricing in Black-Scholes model
* Variance reduction techniques
* Numerical solution of stochastic differential equations and pricing in non-Black-Scholes markets
* Computation of Greeks and portfolio immunisation