Master Meetings

Fundamentals of Informatics

The goal of the course is to acquire/refresh basic knowledge on the mathematical basis of Informatics, such as Logic and Discrete Mathematics, as well as of the important notions and concepts of Algorithmics, Computability, and Complexity theory.

High-Performance Computing

The goal of the HPC course is that students will learn the principles and practices of basic numerical methods and HPC to enable large-scale scientific simulations. This goal will be achieved within six to eight mini-projects with a focus on HPC, CSE, and AI. The content of the course is tailored for 1st year Master students interested in both learning parallel programming models, scientific mathematical libraries, and having hands-on experience using HPC systems. The course will be offered online as well to also allow double-degree Master students and EUMaster4HPC master students to enroll.

Introduction to Programming

The course discusses the functioning of financial markets and trading and price determination in these markets. Topics covered include order submission and trading strategies, market structure and quality, settlement, transaction costs and liquidity, bubbles and crashes, price formation and technical analysis. The lectures will draw on academic and practitioner research as well as information from markets.

Investments

The course is an introduction to the institutions and economic functioning of financial markets. First, the course provides a general description of the basic features of these markets: the asset classes, the trading mechanisms, and the main actors. Then, it deals with individual portfolio choice. Next, individual portfolios are aggregated to derive the main concepts of equilibrium in equity markets (CAPM, APT). These concepts are used to introduce the notion of market efficiency. The empirical evidence on market efficiency is discussed and analyzed from the point of view of classical and alternative theories of capital markets, such as Behavioral Finance. The course then examines the tools that financial analysts use to make investment decisions (equity analysis). Using these notions, the students will be introduced to the concept of active portfolio management. As a final chapter, the course deals with fixed income securities (prices, yields, the term structure, and bond portfolios management).

Data Analytics for Finance I & II

Tukey (1962) defines Data Analysis to be “Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data.”

The goal of this course is 

1. 1. to provide the students with the tools and thinking framework for data analysis
   2. to foster creativity in using existing or or creating new datasets
   3. to equip students with techniques to communicate their results