This course consists of three parts: an introduction to financial time series data characteristics and analysis, a discussion on econometrics techniques (eg, GARCH models, cointegration, extreme values, truncation), and an exploration of machine learning t ...
This course introduces frameworks, concepts and tools to understand the economic dimensions of the world we live in. The course includes applications to real-world situations and events. Assessment is through group projects. The course is divided into two ...
This course provides an overview of the theory of asset pricing and portfolio choice theory following historical developments in the field and putting
emphasis on theoretical models that help our understanding of financial decision
making and financial mar ...
This course provides students with a working knowledge of macroeconomic models that explicitly incorporate financial markets. The goal is to develop a broad and analytical framework for analyzing the interaction of financial decisions, macroeconomic events ...
This course presents the problem of static optimization, with and without (equality and inequality) constraints, both from the theoretical (optimality conditions) and methodological (algorithms) point of view. Economics and financial applications are provi ...
We provide a comprehensive overview of the econometric tools that are essential to estimate financial models, both for asset pricing and
for corporate finance. ...
The objective of this course is to acquire experience in financial machine learning by solving real-world problems. Different groups of students will work on different industry projects during the semester. Lectures will discuss best practices and tools. ...
Participants of this course will master computational techniques frequently used in mathematical finance applications. Emphasis will be put on the implementation and practical aspects. ...
This course is introduces machine learning techniques for financial applications in algorithmic trading, derivatives pricing, model calibration, hedging, and risk management. The course format is hands on coding sessions in Python (Keras, Tensorflow, and S ...