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 ...
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. ...
The course covers advanced topics in corporate finance such as the design and valuation of corporate securities, the issuing process for theses securities, real options, and their implications for valuation, financial structuring, and business development. ...
Participants of this course will master computational techniques frequently used in mathematical finance applications. Emphasis will be put on the implementation and practical aspects. ...