Current courses

MSc Level

• Empirical Finance (64h x 2), since 2021

Theory and Python lab classes on: probability and statistics for financial markets; linear regression model; factor models; principal component analysis.

• Computational Methods in Finance (24h), since 2017

Theory and Python lab classes on: Monte Carlo methods, lattice techniques and numerical schemes for PDEs for financial engineering.

Specialized Master Level

• Computational Methods and Machine Learning for Finance (32h), since 2020

Theory and Python lab classes on: optimization, estimation and calibration techniques, parametric pricing (Monte Carlo-, lattice-, PDE- based), non parametric pricing (machine learning-based), unsupervised and supervised learning.

• Advanced Topics in Empirical Finance (16h), since 2021

Theory and Python lab classes on: concrete portfolio optimization problems and solutions (Black-Litterman algorithm, VarCov matrix shrinkage and denoising)

Past courses

(selected ones)

• Quantitative Finance and Derivatives I (12h x 3), 2023-2025

Excel lab classes on pricing and hedging of financial derivatives within one-period, multiperiod and continuous time models

• Financial Econometrics and Empirical Finance II (12h x 3), 2021-2024

EViews lab classes on financial time series topics: ARMA and VAR models, stationarity/unit roots, cointegration, (G)ARCH models

• Stochastic Calculus (24h), 2020-2025

Stochastic processes in continuous time, Brownian motion, stochastic integration, multivariate generalizations, SDEs