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Found 4 papers, 1 papers with code
DGDNN: Decoupled Graph Diffusion Neural Network for Stock Movement Prediction
Moreover, the ablation study and sensitivity study further illustrate the effectiveness of the proposed method in modeling the time-evolving inter-stock and intra-stock dynamics.
Neural Stochastic Agent-Based Limit Order Book Simulation: A Hybrid Methodology
We show that the stylised facts remain and we demonstrate order flow impact and financial herding behaviours that are in accordance with empirical observations of real markets.
The Limit Order Book Recreation Model (LOBRM): An Extended Analysis
The limit order book (LOB) depicts the fine-grained demand and supply relationship for financial assets and is widely used in market microstructure studies.
The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network
In an order-driven financial market, the price of a financial asset is discovered through the interaction of orders - requests to buy or sell at a particular price - that are posted to the public limit order book (LOB).
