IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1802.01143.html
   My bibliography  Save this paper

The Power of Trading Polarity: Evidence from China Stock Market Crash

Author

Listed:
  • Shan Lu
  • Jichang Zhao
  • Huiwen Wang

Abstract

The imbalance of buying and selling functions profoundly in the formation of market trends, however, a fine-granularity investigation of the imbalance is still missing. This paper investigates a unique transaction dataset that enables us to inspect the imbalance of buying and selling on the man-times level at high frequency, what we call 'trading polarity', for a large cross-section of stocks from Shenzhen Stock Exchange. The trading polarity measures the market sentiment toward stocks from a view of very essence of trading desire. When using the polarity to examine market crash, we find that trading polarity successfully reflects the changing of market-level behavior in terms of its flipping times, depth, and length. We further investigate the relationship between polarity and return. At market-level, trading polarity is negatively correlated with returns, while at stock-level, this correlation changes according to market conditions, which becomes a good signal of market psychology transition. Also, the significant correlation disclosed by the market polarity and market emotion implies that our presented polarity, which essentially calculated in the context of high-frequency trading data, can real-timely reflect the sentiment of the market. The trading polarity indeed provides a new way to understand and foresee the market behavior.

Suggested Citation

  • Shan Lu & Jichang Zhao & Huiwen Wang, 2018. "The Power of Trading Polarity: Evidence from China Stock Market Crash," Papers 1802.01143, arXiv.org.
    • Handle: RePEc:arx:papers:1802.01143
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1802.01143
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ron Kaniel & Shuming Liu & Gideon Saar & Sheridan Titman, 2012. "Individual Investor Trading and Return Patterns around Earnings Announcements," Journal of Finance, American Finance Association, vol. 67(2), pages 639-680, April.
    2. Huang, Roger D. & Masulis, Ronald W., 2003. "Trading activity and stock price volatility: evidence from the London Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 10(3), pages 249-269, May.
    3. Fei Ren & Wei-Xing Zhou, 2014. "Dynamic Evolution of Cross-Correlations in the Chinese Stock Market," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-15, May.
    4. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W., 1992. "The impact of institutional trading on stock prices," Journal of Financial Economics, Elsevier, vol. 32(1), pages 23-43, August.
    5. Wood, Robert A & McInish, Thomas H & Ord, J Keith, 1985. "An Investigation of Transactions Data for NYSE Stocks," Journal of Finance, American Finance Association, vol. 40(3), pages 723-739, July.
    6. Alfonso Dufour & Robert F. Engle, 2000. "Time and the Price Impact of a Trade," Journal of Finance, American Finance Association, vol. 55(6), pages 2467-2498, December.
    7. Fabrizio Lillo & J. Doyne Farmer & Rosario N. Mantegna, 2003. "Master curve for price-impact function," Nature, Nature, vol. 421(6919), pages 129-130, January.
    8. Robert J. Shiller, 1987. "Investor Behavior in the October 1987 Stock Market Crash: Survey Evidence," NBER Working Papers 2446, National Bureau of Economic Research, Inc.
    9. Menkveld, Albert J. & Yueshen, Bart Zhou & Zhu, Haoxiang, 2017. "Shades of darkness: A pecking order of trading venues," Journal of Financial Economics, Elsevier, vol. 124(3), pages 503-534.
    10. Ron Kaniel & Gideon Saar & Sheridan Titman, 2008. "Individual Investor Trading and Stock Returns," Journal of Finance, American Finance Association, vol. 63(1), pages 273-310, February.
    11. Ilaria Bordino & Stefano Battiston & Guido Caldarelli & Matthieu Cristelli & Antti Ukkonen & Ingmar Weber, 2012. "Web Search Queries Can Predict Stock Market Volumes," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-17, July.
    12. Grinblatt, Mark & Keloharju, Matti & Linnainmaa, Juhani T., 2012. "IQ, trading behavior, and performance," Journal of Financial Economics, Elsevier, vol. 104(2), pages 339-362.
    13. Yingying Xu & Zhixin Liu & Jichang Zhao & Chiwei Su, 2017. "Weibo sentiments and stock return: A time-frequency view," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-21, July.
    14. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, October.
    15. Danilo Delpini & Stefano Battiston & Guido Caldarelli & Massimo Riccaboni, 2018. "The Network of U.S. Mutual Fund Investments: Diversification, Similarity and Fragility throughout the Global Financial Crisis," Papers 1801.02205, arXiv.org.
    16. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    17. Russ Wermers, 1999. "Mutual Fund Herding and the Impact on Stock Prices," Journal of Finance, American Finance Association, vol. 54(2), pages 581-622, April.
    18. Shan Lu & Jichang Zhao & Huiwen Wang & Ruoen Ren, 2017. "Herding boosts too-connected-to-fail risk in stock market of China," Papers 1705.08240, arXiv.org, revised Apr 2018.
    19. Robert J. Shiller, 1987. "Investor Behavior in the 1987-10 Stock Market Crash: Survey Evidence," Cowles Foundation Discussion Papers 853, Cowles Foundation for Research in Economics, Yale University.
    20. Chordia, Tarun & Subrahmanyam, Avanidhar, 2004. "Order imbalance and individual stock returns: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 72(3), pages 485-518, June.
    21. Mizuno, Takayuki & Nakano, Tohur & Takayasu, Misako & Takayasu, Hideki, 2004. "Traders' strategy with price feedbacks in financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 330-334.
    22. Dror Y Kenett & Michele Tumminello & Asaf Madi & Gitit Gur-Gershgoren & Rosario N Mantegna & Eshel Ben-Jacob, 2010. "Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-14, December.
    23. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    24. Jeff Alstott & Ed Bullmore & Dietmar Plenz, 2014. "powerlaw: A Python Package for Analysis of Heavy-Tailed Distributions," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
    25. Albert-László Barabási, 2005. "The origin of bursts and heavy tails in human dynamics," Nature, Nature, vol. 435(7039), pages 207-211, May.
    26. Wu, Yajing & Guo, Jinzhong & Chen, Qinghua & Wang, Yougui, 2011. "Socioeconomic implications of donation distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4325-4331.
    27. Plamen Ch Ivanov & Ainslie Yuen & Pandelis Perakakis, 2014. "Impact of Stock Market Structure on Intertrade Time and Price Dynamics," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
    28. Wen-Jie Xie & Ming-Xia Li & Hai-Chuan Xu & Wei Chen & Wei-Xing Zhou & H. E. Stanley, 2016. "Quantifying immediate price impact of trades based on the $k$-shell decomposition of stock trading networks," Papers 1611.06666, arXiv.org, revised Dec 2016.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lu, Shan & Zhao, Jichang & Wang, Huiwen & Ren, Ruoen, 2018. "Herding boosts too-connected-to-fail risk in stock market of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 945-964.
    2. Li, Wei & Wang, Steven Shuye, 2010. "Daily institutional trades and stock price volatility in a retail investor dominated emerging market," Journal of Financial Markets, Elsevier, vol. 13(4), pages 448-474, November.
    3. I-Chun Tsai, 2010. "Order imbalances from after-hours trading," Applied Financial Economics, Taylor & Francis Journals, vol. 20(12), pages 983-987.
    4. Chen, Hung-Ling & Chow, Edward H. & Shiu, Cheng-Yi, 2015. "The informational role of individual investors in stock pricing: Evidence from large individual and small retail investors," Pacific-Basin Finance Journal, Elsevier, vol. 31(C), pages 36-56.
    5. Campbell, John Y. & Ramadorai, Tarun & Schwartz, Allie, 2009. "Caught on tape: Institutional trading, stock returns, and earnings announcements," Journal of Financial Economics, Elsevier, vol. 92(1), pages 66-91, April.
    6. repec:zbw:bofism:2012_047 is not listed on IDEAS
    7. Fei, Tianlun & Liu, Xiaoquan, 2021. "Herding and market volatility," International Review of Financial Analysis, Elsevier, vol. 78(C).
    8. Suchismita Mishra & Le Zhao, 2021. "Order Routing Decisions for a Fragmented Market: A Review," JRFM, MDPI, vol. 14(11), pages 1-32, November.
    9. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Scientific Monographs, Bank of Finland, number 2012_047.
    10. Yue Zhao & Difang Wan, 2018. "Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 243-270, February.
    11. Ülkü, Numan & Weber, Enzo, 2013. "Identifying the interaction between stock market returns and trading flows of investor types: Looking into the day using daily data," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 2733-2749.
    12. Jeffrey R. Black & Pankaj K. Jain & Wei Sun, 2023. "Trade-time clustering," Review of Quantitative Finance and Accounting, Springer, vol. 60(3), pages 1209-1242, April.
    13. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    14. Hu, Gang & Jo, Koren M. & Wang, Yi Alex & Xie, Jing, 2018. "Institutional trading and Abel Noser data," Journal of Corporate Finance, Elsevier, vol. 52(C), pages 143-167.
    15. Thomas, Ashok & Spataro, Luca & Mathew, Nanditha, 2014. "Pension funds and stock market volatility: An empirical analysis of OECD countries," Journal of Financial Stability, Elsevier, vol. 11(C), pages 92-103.
    16. Ting Zhang & George J. Jiang & Wei‐Xing Zhou, 2021. "Order imbalance and stock returns: New evidence from the Chinese stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(2), pages 2809-2836, June.
    17. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    18. Long Wen & Chang Liu & Haiyan Song, 2019. "Forecasting tourism demand using search query data: A hybrid modelling approach," Tourism Economics, , vol. 25(3), pages 309-329, May.
    19. Amil Dasgupta & Andrea Prat & Michela Verardo, 2011. "The Price Impact of Institutional Herding," The Review of Financial Studies, Society for Financial Studies, vol. 24(3), pages 892-925.
    20. Civitarese, Jamil, 2016. "Volatility and correlation-based systemic risk measures in the US market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 459(C), pages 55-67.
    21. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4-2015, January-A.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1802.01143. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.