The Matlab programming language is targeted at scientific and financial computation. Most notably, it is focused on matrix algebra.

It is the programming language I used the most during my two Quantitative Finance MSc years. I had Matlab coding classes and I used it mostly in three courses: Derivatives (I used Matlab for an assignment), Financial Risk Management (a team assignment) and Computational Methods for Finance.

Matlab and Python were also used in the ARPM courses.

I also took the online Machine Learning course by Andrew Ng, Stanford University, which was entirely based on Matlab, and I passed all the graded assignments.

Financial Risk Management

For my University course “Financial Risk Management” I built, together with some fellow students, a Mattlab application with its own Graphical User Interface. The application addressed a specific kind of commercial risks.

Financial Risk Management - Matlab Graphic User Interface

Video and explanation of the Risk Management application: LINK


Job: Derivatives

The job I did for the Derivatives course focused on the Heston model: I used simulations (Monte Carlo) and the analytical formula, volatility surface, smile effect, and I calibrated the model parameters on market data.

The volatility surface generated by an option
Volatility surface – Heston option

Code and complete paper: LINK

Computational Finance

Code examples from my exam: LINK

Machine Learning

Some code snippets: LINK