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An Agent-Based Approach for Time-Series Momentum and Reversal

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Abstract

This paper proposes a novel agent-based model combining private information diffusion to explain time-series momentum and reversal. Private information transmission allows heterogeneous trading strategies coexist in the artificial market. The experiments reproduce momentum in short horizon and reversal in long horizon in the artificial financial market. Moreover, the authors also analyze how the private information contagion affects the momentum. Meanwhile, the authors find the significant price trend and excess volatility of volume when private information diffuses gradually.

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Author information

Authors and Affiliations

  1. School of Economics and Management, Beihang University, Beijing, 100191, China

    Zhaoyuan Wang, Shancun Liu & Haijun Yang

  2. Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, 100191, China

    Haijun Yang

  3. College of Business and Public Administration, Old Dominion University, Norfolk, Virginia, USA

    Harris Wu

Authors
  1. Zhaoyuan Wang
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  2. Shancun Liu
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  3. Haijun Yang
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  4. Harris Wu
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Corresponding author

Correspondence to Haijun Yang.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant Nos. 71771006 and 71771008.

This paper was recommended for publication by Editor YANG Xiaoguang.

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Wang, Z., Liu, S., Yang, H. et al. An Agent-Based Approach for Time-Series Momentum and Reversal. J Syst Sci Complex 33, 461–474 (2020). https://doi.org/10.1007/s11424-020-8042-2

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  • DOI: https://doi.org/10.1007/s11424-020-8042-2

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