DE / EN

Registrations open until Oct 13

Registration on Portal2 is now open until October 13. The exam period is still preliminary.

FIN 687 – Python in Finance

This course teaches students the basics of Python necessary for quantitative seminar and master theses in finance. It covers programming fundamentals, data handling, visualization, and analysis. Additionally, it explores accessing and working with data commonly used in finance research, and additionally accessing APIs, machine learning, and managing large datasets. The course wraps up with a take-home exam applying these skills to solve a financial research question. Practical applications take priority over theoretical programming concepts, and examples are primarily drawn from finance literature.

Learning Outcomes

  • Work independently on quantitative finance topics using Python
  • Gain expertise in data acquisition, transformation, visualization, and analysis
  • Learn regressions and advanced techniques for finance applications

Registration

To participate in this course, you have to register for the course on Portal2.

Please note that the capacity is limited. If there are more registrations than seats, the allocation will be made based on a random draw after the registration deadline (not first-come first-serve).

Further Information

  • Time and Venue

    The course will take place in November in L9, 1–2 Room 001. It is scheduled as a series of full-day courses.

    The dates are (all in November): 08, 11, 14, 19, 21.

    The exam is expected to take place from November 25, 6pm to November 26, 6pm and is a take-home exam.

  • Language

    The course is taught entirely in English.

  • Assessment

    The final grade (only pass/fail) will be based on a take home exam.

    There is only one exam date per semester. A second attempt at the exam is hence only possible in the respective following semester. Please register for the course again and state that this is your second attempt.

Persons in Charge

Sven Vahlpahl

Sven Vahlpahl

Doctoral Student
University of Mannheim
Business School
L9, 1–2 – Room 505
68161 Mannheim
Consultation hour(s):
on appointment