ECTS : 0
Description du contenu de l'enseignement :
Our aim in this course is to implement some key concepts in quantitative finance using popular Python packages such as :
The data we will use is extracted from free online sources (Google, Yahoo, ...). The main parts of the course are the following :
1. Python basics : Data types, data structures, programs structure and packages.
2. Numpy, Matplotlib : discovering these packages with application to Monte Carlo simulation (look at the potential evolution of asset prices over time/Random walk).
3. Scipy : Introduction and application to a regression analysis of stock prices.
4. Pandas and Matplotlib. Introduction and Application (I) : importing, visualizing and analysing Time series financial data.
5. Pandas and Matplotlib. Advanced aspects and application (II) : Volatility calculation, Algorithmic trading, Creating, testing and improving a trading strategy.
Compétence à acquérir :
Mastering the structure of the Python language, a good knowledge of the most important libraries for financial applications (Numpy, Matlplotlib, Scipy, Pandas).
Mode de contrôle des connaissances :
Several programming assignments (one for each class).
Bibliographie, lectures recommandées :
Python for Finance, Mastering data driven finance, by Yves J. Hilpisch.