Financial Computing and Quantitative Investments

The aim of the course is to enable participants to understand and implement in Python key investment science concepts.

By the end of the course, participants should acquire the tools required for making sound investment decisions. They should be able to understand both the foundational theory and underlying concepts, as well as learn how to practically apply these concepts in Python in all stages of the work flow.

This course is required for all participants. It is taught in the first semester and carries 6 ECTS credits. Go to the next course or see the list of courses.

  • Essential Literature
  • D. Luenberger, Investment Science, Oxford University Press (1998).
  • T. Koller, M. Goedhart, D. Wessels (McKinsey & Co), Valuation – Measuring and Managing the Value of Companies, Ed 5, John Wiley (2010).
  • Y. Hilpisch, Python for Finance: Mastering the Data-Driven Finance, Second Edition, O’Reilly (2018).
  • M. Davis, Mathematical Finance: A Very Short Introduction, Oxford Univ. Press (2019).