A deep learning approach to estimating fill probabilities in a limit order book

DOI10.1080/14697688.2022.2124189zbMath1505.91372OpenAlexW4301368526MaRDI QIDQ5051972

Constantinos Maglaras, Ciamac Cyrus Moallemi, Muye Wang

Publication date: 18 November 2022

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697688.2022.2124189

zbMATH Keywords

simulationneural networklimit order bookfill probabilities

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Financial markets (91G15)

Uses Software

• TotalView

Cites Work

• A Stochastic Model for Order Book Dynamics
• Classification-based financial markets prediction using deep neural networks
• Deep learning for finance: deep portfolios
• Empirical Analysis of Limit Order Markets
• The order book as a queueing system: average depth and influence of the size of limit orders
• Deep learning for limit order books
• Universal features of price formation in financial markets: perspectives from deep learning
• DeepLOB: Deep Convolutional Neural Networks for Limit Order Books

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