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A Novel Approach to Queue-Reactive Models: The Importance of Order Sizes
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In this article, we delve into the applications and extensions of the queue-reactive model for the simulation of limit order books. Our approach emphasizes the importance of order sizes, in conjunction with their type and arrival rate, by integrating the current state of the order book to determine, not only the intensity of order arrivals and their type, but also their sizes. These extensions generate simulated markets that are in line with numerous stylized facts of the market. Our empirical calibration, using futures on German bonds, reveals that the extended queue-reactive model significantly improves the description of order flow properties and the shape of queue distributions. Moreover, our findings demonstrate that the extended model produces simulated markets with a volatility comparable to historical real data, utilizing only endogenous information from the limit order book. This research underscores the potential of the queue-reactive model and its extensions in accurately simulating market dynamics and providing valuable insights into the complex nature of limit order book modeling.
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Cited by 2 Pith papers
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Multi-dimensional queue-reactive model and signal-driven models: a unified framework
A multi-asset order book model with a latent efficient price is shown to produce diffusive observed prices at the macroscopic scale, and a numerical maximum likelihood estimator is developed.
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Deep Learning Meets Queue-Reactive: A Framework for Realistic Limit Order Book Simulation
A deep queue-reactive model with cross-level state and categorical order sizes reproduces Bund futures stylized facts including square-root market impact and queue correlations.
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