Thesis awarded by the European Finance Forum

The thesis from Georg Sebastian Kaiser, co-supervised by Prof. Vitor Azevedo and Prof. Sebastian Müller was awarded as the second place at the European Finance Forum (more information in the link here).

The thesis entitled Leveraging International Stock Market Anomalies with Machine Learning examines the out-of-sample performance of 240 stock market anomalies enhanced by 49 machine learning algorithms and over 260 individually trained models across an international data sample of nearly 1.9 billion stock-month-anomaly observations from 1980 to 2019. The author finds significant monthly returns of around 1.8-2.2\%, while more than 85\% of the tested models show superiority over the linearly composed baseline factor benchmark. Apart from a reliable post-publication decline exclusively in the United States, the results are risk-adjusted by allowing for transaction costs up to 300 basis points and avoiding any forward-looking bias with composite predictors based on the tested machine learning approaches. The results of our non-linear models are significant across several classical asset pricing models and uncover market inefficiencies that challenge current international asset pricing theories.

Previously, the thesis from Martin Lehrhuber, also supervised by Prof. Vitor Azevedo was awarded as the best thesis by the Acatis Value Preis 2021.