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Analysis of trade packages in the Chinese stock market

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  • Fei Ren
  • Wei-Xing Zhou

Abstract

This paper conducts an empirical study on trade packages of 23 stocks of the Chinese stock market, each composed of a sequence of consecutive purchases or sales of a stock. We investigate the probability distributions of the execution time, the number of trades, and the total trading volume of trade packages, and analyse the possible scaling relations between them. Quantitative differences are observed between institutional and individual investors. The trading profile of trade packages is investigated to reveal the preference for large trades with respect to trading volume and transaction time of the day, and the different profiles of the two types of investors imply that institutions may be more informed than individuals. We further analyse the price impact of both the entire trade packages and the individual transactions within trade packages. We find that the price impact of trade packages is non-negligible over the period of the execution time and it may have a power-law relation with the total trading volume. The price impact of the transactions within trade packages displays a U-shaped profile with respect to the time of the day, and also shows a power-law dependence on the trading volume. The trading volumes of the transactions within trade packages made by institutions have a stronger impact on current returns, but the following price reversals persist over a relatively shorter horizon in comparison with those of individuals.

Suggested Citation

  • Fei Ren & Wei-Xing Zhou, 2013. "Analysis of trade packages in the Chinese stock market," Quantitative Finance, Taylor & Francis Journals, vol. 13(7), pages 1071-1089, January.
    • Handle: RePEc:taf:quantf:v:13:y:2013:i:7:p:1071-1089
    DOI: 10.1080/14697688.2013.765957
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    1. Naes, Randi & Skjeltorp, Johannes A., 2006. "Order book characteristics and the volume-volatility relation: Empirical evidence from a limit order market," Journal of Financial Markets, Elsevier, vol. 9(4), pages 408-432, November.
    2. Kraus, Alan & Stoll, Hans R, 1972. "Price Impacts of Block Trading on the New York Stock Exchange," Journal of Finance, American Finance Association, vol. 27(3), pages 569-588, June.
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    1. Michele Tumminello & Fabrizio Lillo & Jyrki Piilo & Rosario N. Mantegna, 2011. "Identification of clusters of investors from their real trading activity in a financial market," Papers 1107.3942, arXiv.org.
    2. Ren, Fei & Li, Sai-Ping & Liu, Chuang, 2017. "Information spreading on mobile communication networks: A new model that incorporates human behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 334-341.
    3. Musciotto, Federico & Marotta, Luca & Miccichè, Salvatore & Piilo, Jyrki & Mantegna, Rosario N., 2016. "Patterns of trading profiles at the Nordic Stock Exchange. A correlation-based approach," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 267-278.
    4. Jingzhong Li & Yongmei Liu & Mingming Cao & Bing Xue, 2015. "Space-Time Characteristics of Vegetation Cover and Distribution: Case of the Henan Province in China," Sustainability, MDPI, vol. 7(9), pages 1-13, August.
    5. Federico Musciotto & Luca Marotta & Jyrki Piilo & Rosario N. Mantegna, 2018. "Long-term ecology of investors in a financial market," Palgrave Communications, Palgrave Macmillan, vol. 4(1), pages 1-12, December.

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