1 citations · 1 across the 2 of their papers we have counts for
4 papers
UQ-LOB: Uncertainty-Aware Limit Order Book Mid-Price Forecasting
Derrick Gilchrist Edward Manoharan, Eljas Linna, Kestutis Baltakys +2
Forecasting short-horizon mid-price movements from limit order book (LOB) data is central to algorithmic trading, yet most deep LOB forecasters are point predictors: they output a…
Repurposing Deep Limit Order Book Forecasting for Scenario-Conditioned Market Impact Modeling
Eljas Linna, Kestutis Baltakys, Derrick Manoharan +2
Deep Limit Order Book forecasting models capture nonlinear market dynamics, but their ability to quantify the effects of counterfactual order book messages has not been systematica…
LOBERT: Generative AI Foundation Model for Limit Order Book Messages
Eljas Linna, Kestutis Baltakys, Alexandros Iosifidis +1
Modeling the dynamics of financial Limit Order Books (LOB) at the message level is challenging due to irregular event timing, rapid regime shifts, and the reactions of high-frequen…
Challenges for Generative AI in Legal Reasoning
Eljas Linna, Tuula Linna
Large Language Models (LLMs) are being integrated into professional domains, yet their limitations in such high-stakes fields as law remain poorly understood. In response, this pap…