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Comparing Actual and Simulated HFT Traders' Behavior for Agent Design

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Recently financial markets have shown significant risks and levels of volatility. Understanding the sources of these risks require simulation models capable of representing adequately the real mechanisms of markets. In this paper, we compared data of the high-frequency-trader market-making (HFT-MM) strategy from both the real financial market and our simulation. Regarding the former, we extracted trader clusters and identified one cluster whose statistical indexes indicated HFT-MM features. We then analyzed the difference between these traders' orders and the market price. In our simulation, we built an artificial market model with a continuous double auction system, stylized trader agents, and HFT-MM trader agents based on prior research. As an experiment, we compared the distribution of the order placements of HFT-MM traders in the real and simulated financial data. We found that the order placement distribution near the market or best price in both the real data and the simulations were similar. However, the orders far from the market or best price differed significantly when the real data exhibited a wider range of orders. This indicates that in order to build more realistic simulation of financial markets, integrating fine-grained data is essential.

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  • Masanori Hirano & Kiyoshi Izumi & Hiroyasu Matsushima & Hiroki Sakaji, 2020. "Comparing Actual and Simulated HFT Traders' Behavior for Agent Design," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(3), pages 1-6.
    • Handle: RePEc:jas:jasssj:2019-114-5
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    Cited by:

    1. Isao Yagi & Yuji Masuda & Takanobu Mizuta, 2020. "Analysis of the Impact of High-Frequency Trading on Artificial Market Liquidity," Papers 2010.13038, arXiv.org.

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