Imagen de Portada

ClusterLOB: Enhancing Trading Strategies by Clustering Orders in Limit Order Books

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhang, Yichi, Cucuringu, Mihai, Shestopaloff, Alexander Y., Zohren, Stefan
Formato:	Preprint
Publicado:	2025
Materias:	Trading and Market Microstructure
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

The Market Maker's Dilemma: Navigating the Fill Probability vs. Post-Fill Returns Trade-Off
por: Albers, Jakob, et al.
Publicado: (2025)

Trade Co-occurrence, Trade Flow Decomposition, and Conditional Order Imbalance in Equity Markets
por: Lu, Yutong, et al.
Publicado: (2022)

Bridging the Reality Gap in Limit Order Book Simulation
por: Noble, Patrick, et al.
Publicado: (2026)

LOB-Bench: Benchmarking Generative AI for Finance -- an Application to Limit Order Book Data
por: Nagy, Peer, et al.
Publicado: (2025)

JaxMARL-HFT: GPU-Accelerated Large-Scale Multi-Agent Reinforcement Learning for High-Frequency Trading
por: Mohl, Valentin, et al.
Publicado: (2025)

Competition and Incentives in a Shared Order Book
por: Aïd, René, et al.
Publicado: (2025)

Deep Limit Order Book Forecasting
por: Briola, Antonio, et al.
Publicado: (2024)

Trading Large Orders in the Presence of Multiple High-Frequency Anticipatory Traders
por: Xu, Ziyi, et al.
Publicado: (2024)

Limit Order Book Simulations: A Review
por: Jain, Konark, et al.
Publicado: (2024)

Painting the market: generative diffusion models for financial limit order book simulation and forecasting
por: Backhouse, Alfred, et al.
Publicado: (2025)

Co-trading networks for modeling dynamic interdependency structures and estimating high-dimensional covariances in US equity markets
por: Lu, Yutong, et al.
Publicado: (2023)

HLOB -- Information Persistence and Structure in Limit Order Books
por: Briola, Antonio, et al.
Publicado: (2024)

Toward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading Tasks
por: Miyazaki, Kunihiro, et al.
Publicado: (2026)

DiffVolume: Diffusion Models for Volume Generation in Limit Order Books
por: Wang, Zhuohan, et al.
Publicado: (2025)

Learning the Spoofability of Limit Order Books With Interpretable Probabilistic Neural Networks
por: Fabre, Timothée, et al.
Publicado: (2025)

An Efficient deep learning model to Predict Stock Price Movement Based on Limit Order Book
por: Yang, Jiahao, et al.
Publicado: (2025)

Forecasting High Frequency Order Flow Imbalance
por: Anantha, Aditya Nittur, et al.
Publicado: (2024)

Quantifying Price Improvement in Order Flow Auctions
por: Bachu, Brad, et al.
Publicado: (2024)

An Impulse Control Approach to Market Making in a Hawkes LOB Market
por: Jain, Konark, et al.
Publicado: (2025)

Deep Learning Meets Queue-Reactive: A Framework for Realistic Limit Order Book Simulation
por: Bodor, Hamza, et al.
Publicado: (2025)

To Hedge or Not to Hedge: Optimal Strategies for Stochastic Trade Flow Management
por: Bergault, Philippe, et al.
Publicado: (2025)

An End-To-End LLM Enhanced Trading System
por: Zhou, Ziyao, et al.
Publicado: (2025)

A Novel Approach to Queue-Reactive Models: The Importance of Order Sizes
por: Bodor, Hamza, et al.
Publicado: (2024)

Dynamic Grid Trading Strategy: From Zero Expectation to Market Outperformance
por: Chen, Kai-Yuan, et al.
Publicado: (2025)

Calculating Profits and Losses for Algorithmic Trading Strategies: A Short Guide
por: Glattfelder, James B., et al.
Publicado: (2024)

DeePM: Regime-Robust Deep Learning for Systematic Macro Portfolio Management
por: Wood, Kieran, et al.
Publicado: (2026)

Reinforcement Learning-Based Market Making as a Stochastic Control on Non-Stationary Limit Order Book Dynamics
por: Zimmer, Rafael, et al.
Publicado: (2025)

Against a Universal Trading Strategy: No-Arbitrage, No-Free-Lunch, and Adversarial Cantor Diagonalization
por: Svozil, Karl
Publicado: (2026)

Directional Liquidity and Geometric Shear in Pregeometric Order Books
por: da Cruz, João P.
Publicado: (2026)

Pregeometric Origins of Liquidity Geometry in Financial Order Books
por: da Cruz, João P.
Publicado: (2026)

Temporal Kolmogorov-Arnold Networks (T-KAN) for High-Frequency Limit Order Book Forecasting: Efficiency, Interpretability, and Alpha Decay
por: Makinde, Ahmad
Publicado: (2026)

The Subtle Interplay between Square-root Impact, Order Imbalance & Volatility II: An Artificial Market Generator
por: Maitrier, Guillaume, et al.
Publicado: (2025)

Estimation of an Order Book Dependent Hawkes Process for Large Datasets
por: Mucciante, Luca, et al.
Publicado: (2023)

Exploring Microstructural Dynamics in Cryptocurrency Limit Order Books: Better Inputs Matter More Than Stacking Another Hidden Layer
por: Wang, Haochuan
Publicado: (2025)

Reinforcement Learning for Trade Execution with Market and Limit Orders
por: Cheridito, Patrick, et al.
Publicado: (2025)

Deep Learning for Financial Time Series: A Large-Scale Benchmark of Risk-Adjusted Performance
por: Saly-Kaufmann, Adir, et al.
Publicado: (2026)

A Modern Paradigm for Algorithmic Trading
por: Glattfelder, James B., et al.
Publicado: (2025)

Model Predictive Control For Trade Execution
por: McAuliffe, Thomas P., et al.
Publicado: (2026)

Strategic Learning and Trading in Broker-Mediated Markets
por: Aqsha, Alif, et al.
Publicado: (2024)

An Application of the Ornstein-Uhlenbeck Process to Pairs Trading
por: Suchato, Jirat, et al.
Publicado: (2024)