In 2011, Tim Loughran and Bill McDonald published a seminal paper that paved the way for researchers and professionals to use a simple but powerful method to analyze text information in business and economics. More specifically, Tim Loughran and Bill McDonald developed a set of dictionaries that capture, for example, positive or negative sentiment, uncertainty, or vague language in a business setting.
Since then, corporate disclosures (e.g., annual and quarterly financial reports, ad-hoc announcements), manager statements (e.g., in earnings conference calls), and other financial reports have been extensively analyzed and linked to economic outcomes like future firm performance. At the same time, firms have adjusted their communication, for example, avoiding negative sentiment words and conveying negative information in ways that make it harder for algorithms to detect it. Recently, the arrival of powerful large language models like ChatGPT or FinBERT, a large language model specifically trained on financial documents, has created new opportunities to quantify the information content of financial documents more accurately and comprehensively.
- Gain a deeper understanding of information transmission in financial markets
- Identify which corporate disclosures market participants focus on
- Assess the informational value of earnings conference calls
- Analyze how companies and managers adjust their communication strategies
- Utilize various methods to analyze the text of financial documents, including dictionaries and the FinBERT model
- Implement selected textual analysis methods in Python through empirical exercises
This course is part of the prestigious part-time Master in Finance program, conducted in English on Fridays and Saturdays on Campus Westend. It offers a valuable opportunity to network and gain expertise without committing to a full degree program. As the number of seats is limited, we recommend to register early. If you’re a GBS alumni, explore our attractive alumni discount options.
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Participants have the choice of completing the course with a qualified certificate or attending as a guest auditor. As an auditor, you are not required to complete assignments, take exams or earn academic credits.
| ECTS | Certificate | |
|---|---|---|
| Guest auditor | - | Certificate of Participation |
| Full participant | 3 CP | Qualified Certificate |
This course can also be upgraded to a Certificate of Advanced Studies (CAS) in Financial Technology Management in combination with other courses from our Master in Finance program.
Prof. Dr. Alexander Hillert
Prof. Dr. Alexander Hillert is the Program Director of the Research Data Center and a Professor of Finance and Data Science at the Leibniz Institute for Financial Research SAFE. Before joining SAFE, he held the Chair of Sustainable Asset Management at Goethe University Frankfurt. He completed his Ph.D. at the University of Mannheim. Hillert's research centers on empirical asset pricing and corporate finance, with a focus on how market participants process information. He uses computational linguistics to examine the influence of text-based information on capital markets, with his work appearing in top journals like the Journal of Financial Economics and the Review of Financial Studies.
| Date | Session |
|---|---|
| Sat., May 17, 2025 | 09:00-16:30 |
| Fri., June 13, 2025 | 09:00-16:30 |