Once a year, the Presidential Board of LUH awards the "Leibniz Talents" prize for outstanding students and student groups. This year, Annika Giese and Brian von Knoblauch, a junior researcher and a junior researcher from the Institute of Banking and Finance at the Faculty of Economics, are among the recipients. With this award, the university management wants to make high-performing students with innovative initiatives visible and encourage them to develop further.
Annika Giese, a Master's graduate from LUH and research assistant at the Faculty of Business, Economics and Informatics since May 2023, is researching the relationship between stock markets and bank deposits: the Presidential Board awarded the 'Leibniz Talents 2023' prize in recognition of her academic achievement in writing her Master's thesis entitled "Stock Market Attractiveness and Bank Deposits". "My thesis is based on the assumption that investors tend to invest in stocks that are geographically close to them and that they do not always make rational allocation decisions. Therefore, I use various measures based on psychological insights to investigate whether an attractive stock market at the local level leads to lower deposit growth at banks," she says, describing the subject of her research.
Brian von Knoblauch, a research associate at the Institute of Banking and Finance, was honored for his outstanding achievements, about whom the head of the Institute, Prof. Dr. Maik Dierkes, recently commented: "He is truly a Leibniz talent!" In his Master's thesis "Deep Learning in Asset Pricing", the best Bachelor's and Master's student in his faculty, two-time Wilhelm Launhardt Prize winner, Hannes Rehm Scholarship holder and participant in the Kurt Alten Excellence Program, combined practically relevant challenges with scientific theory in a special way. The aim of his work was to investigate whether it is possible to improve the explainability of stock returns with complex - but economically cleverly chosen - model architectures.
In recent years, the financial world has undergone significant changes, driven by the rapid development of technologies and the availability of large amounts of data. Machine learning has proven to be a powerful tool to identify patterns and correlations in financial data that are difficult to access for traditional linear regression analysis.
"The work has firmly convinced me that the integration of artificial intelligence and machine learning in capital market research can enable decisive progress in better understanding market mechanisms and effects," says Brian von Knoblauch, describing his motivation.
"The research work that I started with my Master's thesis is very close to my heart. I am therefore delighted to be able to continue this line of research at LUH as part of my doctorate."
