Big Data in Finance

Big data is one of the buzzwords in today’s business world. Since computers became more and more central to modern commerce, businesses have access to large amounts of data, for example, on their customers or transactions. This gives companies the opportunity to extract useful information using statistical and machine learning methods in order to gain a competitive advantage. The big internet companies are the obvious examples, but the topic is also especially relevant for the financial industry (like with credit analysis, fraud detection, insurance and robo-advising). In many areas these new technologies will disrupt existing business models.

The course will focus on the analysis of Big Data, and how it can be used for prediction, for example bankruptcies or stock prices. Even though the course will focus on supervised learning techniques such as regression and classification, we will also touch upon unsupervised learning techniques.

Learning objectives

Upon completion of this course, you will be able to:

  • practically analyse large-scale business data using machine learning techniques
  • apply basics of analysing data in R
  • apply learnings to real financial data
  • use statistical methods for strategic decision making

Key concepts

  • Machine learning
  • Regression and classification
  • Supervised and unsupervised learning
  • Data analysis in R

Course format

This course is offered in the part-time Master in Finance program and may be attended on a “no credit” basis by individuals not enrolled in the program. Course participants are visitors who are not responsible for assignments and do not take an exam. As the number of seats in the course is limited, we recommend to register online early.

Contact

Ludmila Ketterer

Senior Manager -
Master in Finance & Corporate Programs
+49 69 798 33512
E-Mail

Key Facts

Course materials
Course materials except books will be provided in electronic form.

Language
English

Course fee*
€ 950 (fee is exempt from VAT). Goethe Business School students and alumni receive a 20% discount off the regular fee.

Certificate of participation
A GBS certificate of participation is awarded upon completion of the course.

Venue
House of Finance, Goethe University, Theodor-W.-Adorno-Platz 3, 60323 Frankfurt

*Withdrawal and fee refund

In case the course withdrawal request is received two weeks prior to the start of classes, we will retain a withdrawal fee of EUR 50. In case the course withdrawal request is received less than two weeks prior to the start of classes, we will retain 50% of the payment made.

Prof. Dr. Uwe Walz holds the Chair of Industrial Organization at Goethe University, and is co-Director of the PhD Program in Economics. Uwe Walz received his Ph.D. in economics from the University of Tübingen in 1991 and completed his habilitation at the University of Mannheim in 1995. Prior to joining the faculty of Goethe University in October 2002 he was a Professor of Economics at the University of Bochum (1995-1997) and at the University of Tübingen (1997-2002). Furthermore, he was a visiting research fellow at the London School of Economics and at the University of California at Berkeley. Prof. Walz is Director of the research program “Entrepreneurial Finance” at the Center for Financial Studies (CFS) and research professor at the center for European Economic Research (ZEW). His main current research focuses on private equity, entrepreneurial finance and contract theory as well as on the economics of network industries. Prof. Walz has published widely in international journals, most recently on venture capital topics and organizational design. His work has appeared in journals such as the Journal of Corporate Finance, the Journal of Financial Intermediation, the Journal of International Economics, the European Economic Review, and the Journal of Public Economics.

Steffen Juranek is an Associate Professor at Norwegian School of Economics since 2017. He received his Ph.D. from Goethe University Frankfurt in 2012. His research focuses on the organization of firms and markets, and the role of intellectual property for firm strategy, financing and taxation. Prof. Dr. Juranek taught courses on statistics, management control, R&D and intellectual property. His research has been published in international journals.

Course schedule

DateSessions
Fri., Apr 3, 202018:00-20:00
Sat., Apr 4, 202011:30-13:30
Fri., Apr 17, 202015:30-17:30; 18:00-20:00
Fri., Apr 24, 202013:00-15:00
Fri., May 8, 202018:00-20:00
Sat., May 9, 202009:00-11:00; 11:30-13:30
Bulletin
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