Machine learning and the cross-section of emerging market stock returns
Präsentation
from 18. March 2025
Members Only
Machine learning techniques have become increasingly popular among academics and investing practitioners. In this webinar, we will explore how advanced machine learning models can outperform traditional linear approaches for emerging market stock selection. The discussion will focus on the performance, key drivers, and practical implications of these models in a real-world investment context.
Key Discussion Points:
- We compare linear and machine learning models in predicting emerging market stock returns
- Which non-linearities and interactions drive the superior out-of-sample performance of machine learning models?
- Is an underreaction or a risk-based explanation more likely?
- Can we achieve significant net return when considering real-life investment frictions such as transaction costs and short-selling limitations?
Please note that the presentation must not be shared.
