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Determinants of immediate price impacts at the trade level in an emerging order-driven market

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  • Wei-Xing Zhou

    (ECUST)

Abstract

The common wisdom argues that, in general, large trades cause large price changes, while small trades cause small price changes. However, for extremely large price changes, the trade size and news play a minor role, while the liquidity (especially price gaps on the limit order book) is a more influencing factor. Hence, there might be other influencing factors of immediate price impacts of trades. In this paper, through mechanical analysis of price variations before and after a trade of arbitrary size, we identify that the trade size, the bid-ask spread, the price gaps and the outstanding volumes at the bid and ask sides of the limit order book have impacts on the changes of prices. We propose two regression models to investigate the influences of these microscopic factors on the price impact of buyer-initiated partially filled trades, seller-initiated partially filled trades, buyer-initiated filled trades, and seller-initiated filled trades. We find that they have quantitatively similar explanation powers and these factors can account for up to 44% of the price impacts. Large trade sizes, wide bid-ask spreads, high liquidity at the same side and low liquidity at the opposite side will cause a large price impact. We also find that the liquidity at the opposite side has a more influencing impact than the liquidity at the same side. Our results shed new lights on the determinants of immediate price impacts.

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  • Wei-Xing Zhou, 2012. "Determinants of immediate price impacts at the trade level in an emerging order-driven market," Papers 1201.5448, arXiv.org.
    • Handle: RePEc:arx:papers:1201.5448
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    Cited by:

    1. Zhao, Jingdong & Zhu, Hongliang & Li, Xindan, 2018. "Optimal execution with price impact under Cumulative Prospect Theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1228-1237.
    2. Gu, Gao-Feng & Xiong, Xiong & Zhang, Yong-Jie & Chen, Wei & Zhang, Wei & Zhou, Wei-Xing, 2016. "Stylized facts of price gaps in limit order books," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 48-58.
    3. Yu-Lei Wan & Wen-Jie Xie & Gao-Feng Gu & Zhi-Qiang Jiang & Wei Chen & Xiong Xiong & Wei Zhang & Wei-Xing Zhou, 2015. "Statistical Properties and Pre-Hit Dynamics of Price Limit Hits in the Chinese Stock Markets," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-20, April.
    4. Zhang, Wei & Bi, Zhengzheng & Shen, Dehua, 2017. "Investor structure and the price–volume relationship in a continuous double auction market: An agent-based modeling perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 345-355.
    5. Gao-Feng Gu & Xiong Xiong & Hai-Chuan Xu & Wei Zhang & Yongjie Zhang & Wei Chen & Wei-Xing Zhou, 2021. "An empirical behavioral order-driven model with price limit rules," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    6. Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei Chen & Wei Zhang & Wei-Xing Zhou, 2014. "Stylized facts of price gaps in limit order books: Evidence from Chinese stocks," Papers 1405.1247, arXiv.org.
    7. Zhang, Ting & Gu, Gao-Feng & Xu, Hai-Chuan & Xiong, Xiong & Chen, Wei & Zhou, Wei-Xing, 2017. "Power-law tails in the distribution of order imbalance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 201-208.
    8. Gao, Yan & Gao, Yao, 2015. "Statistical properties of short-selling and margin-trading activities and their impacts on returns in the Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 293-307.
    9. Zhang, Ting & Gu, Gao-Feng & Zhou, Wei-Xing, 2019. "Order imbalances and market efficiency: New evidence from the Chinese stock market," Emerging Markets Review, Elsevier, vol. 38(C), pages 458-467.
    10. Jian Zhou & Gao-Feng Gu & Zhi-Qiang Jiang & Xiong Xiong & Wei Chen & Wei Zhang & Wei-Xing Zhou, 2017. "Computational Experiments Successfully Predict the Emergence of Autocorrelations in Ultra-High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 50(4), pages 579-594, December.
    11. Wan, Yu-Lei & Wang, Gang-Jin & Jiang, Zhi-Qiang & Xie, Wen-Jie & Zhou, Wei-Xing, 2018. "The cooling-off effect of price limits in the Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 153-163.
    12. Hai-Chuan Xu & Zhi-Qiang Jiang & Wei-Xing Zhou, 2016. "Immediate price impact of a stock and its warrant: Power-law or logarithmic model?," Papers 1611.04091, arXiv.org.
    13. Wang, Kaiyang & Yang, Haizhen, 2018. "The price-volume relationship caused by asset allocation based on Kelly criterion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1-8.
    14. Xu, Hai-Chuan & Zhang, Wei & Xiong, Xiong & Wang, Xue & Zhou, Wei-Xing, 2021. "The double-edged role of social learning: Flash crash and lower total volatility," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 405-420.
    15. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Zhong, Chen-Yang & Qiu, Tian & Ren, Fei & He, Yun-Xing, 2018. "Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 301-310.
    16. Xie, Wen-Jie & Li, Mu-Yao & Zhou, Wei-Xing, 2021. "Learning representation of stock traders and immediate price impacts," Emerging Markets Review, Elsevier, vol. 48(C).
    17. Hai-Chuan Xu & Wei Chen & Xiong Xiong & Wei Zhang & Wei-Xing Zhou & H Eugene Stanley, 2016. "Limit-order book resiliency after effective market orders: Spread, depth and intensity," Papers 1602.00731, arXiv.org, revised Feb 2017.

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