On December 3, the Bundesverband Alternative Investments e. V. (BAI), the central interest group of the alternative investments industry in Germany, awarded the fourteenth BAI Science Prize for excellent scientific work in the field of alternative investments. Prizes were awarded in four different categories, with a total of EUR 10,000 in prize money.
The winning papers were selected by an independent panel of experts from the fields of practice and science. The prizes were presented by Prof. Dr. Dirk Schiereck (TU Darmstadt), who represented the panel at the award ceremony, and Prof. Dr. Rolf Tilmes, member of the board of the BAI. In his laudatory speech, Prof. Schiereck emphasized: “This year, too, the winning papers are of a very high scientific standard and are all worthy of an award. This is entirely in the interest of science and also of the alternative investment industry, which also benefits from it”.
The particular broad impact of the Science Prize should be emphasized. The excellent quality of the submitted works is an incentive for the BAI to continue organizing the Science Award annually in the future. With over 200 submissions in the last fourteen years, the BAI Science Award has become a permanent fixture.
The following works were awarded:
In the category of bachelor theses, the work “The Black-Scholes Model versus the Heston-Nandi GARCH Option Pricing Model: A Comparison of Option Pricing Models” by Finn Cuber was convincing. This work compares the Black-Scholes model and the Heston-Nandi GARCH option pricing model in terms of their performance in estimating option prices. Various moneyness levels and maturities are used to compare the estimates with the actual prices.
The category for master's theses was won by Markus Bilz with his thesis “Improving Option Trade Classification with Machine Learning”. The thesis examines the potential of machine learning (ML) for classifying option trades according to the initiator of the trade as an alternative to classic heuristics such as the Lee-Ready algorithm. On two large option datasets from the ISE and CBOE, it achieves significantly higher accuracy than classic benchmarks with the approaches gradient-boosted trees and FT transformers, while also improving robustness. It is characterized by the fact that, for the first time, it considers both the supervised learning scenario and an extension to the semi-supervised scenario, which requires only partially labeled option trades and achieves high performance gains. Furthermore, the work shows through a Shapley-based feature importance analysis that classical heuristics and the ML models used share a common subset of trade information for classification, but that ML approaches exploit this more effectively.
In the category of dissertations, the work of Dr. Alexander Jürgens on the topic: “Essays on Cyclicality and Heterogeneity in Private Equity” was selected. The dissertation deals with the cyclicality and heterogeneity of the performance and value creation levers of private equity (PE) investments. The results of the work show that PE-financed companies are less susceptible to recessionary phases than comparable listed companies. However, the performance and value creation of investment firms in PE show significant systematic differences that can be difficult for investors to recognize. The paper emphasizes the importance of comprehensive data and introduces new statistical methods to reliably identify competent PE firms.
In the category of other scientific papers, the jury was won over by the paper “Book-to-Market, Mispricing, and the Cross-Section of Corporate Bond Returns” by the team of authors Prof. Dr. Söhnke M. Bartram, Prof. Mark Grinblatt and Prof. Yoshio Nozawa. The content: The book-to-market ratios of corporate bonds predict bond yields calculated from transaction prices. Senior bonds (even investment grade bonds) with the 20% highest ratios have 3-4% higher yields per year than those with the 20% lowest ratios after accounting for numerous liquidity, default, microstructure, and price risk attributes.
Summaries of the winning papers will appear in a BAI special newsletter in the near future.
BAI press release
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