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.
Stylized Facts and Market Microstructure: An In-Depth Exploration of German Bond Futures Market
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abstract
This paper presents an in-depth analysis of stylized facts in the context of futures on German bonds. The study examines four futures contracts on German bonds: Schatz, Bobl, Bund and Buxl, using tick-by-tick limit order book datasets. It uncovers a range of stylized facts and empirical observations, including the distribution of order sizes, patterns of order flow, and inter-arrival times of orders. The findings reveal both commonalities and unique characteristics across the different futures, thereby enriching our understanding of these markets. Furthermore, the paper introduces insightful realism metrics that can be used to benchmark market simulators. The study contributes to the literature on financial stylized facts by extending empirical observations to this class of assets, which has been relatively underexplored in existing research. This work provides valuable guidance for the development of more accurate and realistic market simulators.
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q-fin.TR 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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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.