Julius Döbelt

Cross-Sectional Heterogeneity in LSTM Networks for Financial Time Series

Predicting financial asset returns remains one of the most difficult challenges in empirical finance, driven by the low signal-to-noise ratio and the semi-strong form of market efficiency. While deep learning models, especially LSTM networks, have shown promise in capturing temporal dependencies, standard architectures...