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High Frequency Finance and Algorithmic Trading

This course covers the mechanics of trading in order/quote-driven markets which are the key elements of contemporary algorithmic trading in financial markets. This module contains ten topics on various theoretical, methodological and technical aspects of high frequency finance. Substantial amount of time will be spent on understanding the concepts related to high frequency big data analysis, designing algorithmic trading strategies and the associated risk analysis.

Exam info and full course description

Exam info and full course description can be found in the course catalogue

Admission Requirements

Course specific:

A Bachelor's degree in Economics and Business Administration or a related degree


Exchange students: nomination from your home university

Freemovers: documentation for English Language proficiency

You can read more about admission here.


Venkata Lakshmipathi Raju Chinthalapati


Academic profile

Raju is a Reader in Financial Technologies in the Department of Computing, Goldsmiths, University of London. Before joining University of London, Raju was Assistant Professor in Finance at University of Southampton.