3 papers
cs.LG2026
Predicting Stock Price Direction on Earnings Announcement Days using Multi-modal Deep Learning
Manuel Noseda, Nathan Soldati, Marco Paina
Predicting stock price movements during Earnings Announcements (EAs) is a significant challenge due to market noise and high-impact price discontinuities. In this study, we evaluat…
physics.flu-dyn2026
Chirality tomography: measuring local helicity from trajectory linking
Manuel Noseda, Bernardo Luciano Español, Pablo Daniel Mininni +1
We present the first three-dimensional helicity maps of fully developed turbulence obtained through chirality tomography, a Lagrangian voxel-based method that reconstructs helicity…
cs.LG2025
Federated Learning for Financial Forecasting
Manuel Noseda, Alberto De Luca, Lukas Von Briel +1
This paper studies Federated Learning (FL) for binary classification of volatile financial market trends. Using a shared Long Short-Term Memory (LSTM) classifier, we compare three…