This is an BYOD course.

Please note the prerequisites for this course at the bottom of the course description.

With the rise of high frequency trading on stock markets during the past decade, algorithmic trading plays an increasingly important role on stock markets, for example to exploit mispricing. In the course students will learn to build financial algorithms based on clear and feasible valuation logic. During the sessions students will learn what valuation techniques can be applied to a range of financial products. Moreover, the role of financial algorithms in modern finance and fintech will be discussed. This course is given with the support of an internationally leading firm in the field of market making. This firm trades a wide range of products: listed derivatives, cash equities, exchange–traded funds, bonds and foreign currencies. This cooperation enables students to test their algorithms by applying them to actual price data of a wide range of financial products.

The course is open to master’s students in either Banking and Finance or Financial Management at U.S.E. The programming of algorithms will be done in Python, a programming language that is used more and more in firms that work with big data and therefore helpful for your future career. As entry requirement for this course, students should be able to demonstrate solid Python skills. These skills can be acquired by (i) successfully completing the Python module during the course Fintech Research Project and (ii) executing a considerable amount of self-study during this Python module. To enable the actual programming of algorithms, the first two course weeks comprise a number of Python workshops which build on this entry requirement. All participants should therefore have an interest in programming. In addition, they should feel comfortable and motivated to work in a small team that jointly develops financial algorithms.
 
Format
Lectures and workshops

Assessment method
•         a number of programming assignments (75%)
•         written exam on finance theory (25%, individual)

In case online access is required for this course and you are not in the position to buy the access code, you are advised to contact the course coordinator for an alternative solution. Please note that access codes are not re-usable meaning that codes from second hand books do not work, as well as access codes from books with a different ISBN . Separate or spare codes are usually not available.