IDEAS home Printed from https://ideas.repec.org/a/ibn/ijefaa/v9y2017i9p123-132.html
   My bibliography  Save this article

Informed Trading of Futures Markets During the Financial Crisis: Evidence from the VPIN

Author

Listed:
  • Yen-Hsien Lee
  • Wen-Chien Liu
  • Chia-Lin Hsieh

Abstract

This paper examines the impact of informed trading on futures returns during the 2008-2009 financial crisis. To precisely capture the informed trading in the highly volatile market during this period, we adopt the Volume-Synchronized Probability of Informed Trading (VPIN) of Easley, Hvidkjaer and O¡¯Hara (2012) as our main measurement for informed trading. Besides, we also use a unique transaction dataset with investor identity to classify investors into domestic and foreign institutional investors, which the foreign institutional investors are supposed to be characterized by a higher degree of informed trading. Our empirical results show that the VPIN of foreign institutional investors has indeed significantly positive impacts on futures returns at the individual level. By contrast, the effect of the VPIN of domestic institutional investors on futures returns is only significant on Wednesdays, which could be seen as a special kind of day-of-the-week effect.

Suggested Citation

  • Yen-Hsien Lee & Wen-Chien Liu & Chia-Lin Hsieh, 2017. "Informed Trading of Futures Markets During the Financial Crisis: Evidence from the VPIN," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(9), pages 123-132, September.
  • Handle: RePEc:ibn:ijefaa:v:9:y:2017:i:9:p:123-132
    as

    Download full text from publisher

    File URL: http://ccsenet.org/journal/index.php/ijef/article/view/69216/38153
    Download Restriction: no

    File URL: http://ccsenet.org/journal/index.php/ijef/article/view/69216
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Harris, Lawrence, 1986. "A transaction data study of weekly and intradaily patterns in stock returns," Journal of Financial Economics, Elsevier, vol. 16(1), pages 99-117, May.
    2. Lai, Hung-Cheng & Wang, Kuan-Min, 2014. "Relationship between the trading behavior of three institutional investors and Taiwan Stock Index futures returns," Economic Modelling, Elsevier, vol. 41(C), pages 156-165.
    3. Yan, Zhipeng & Cheng, Lee-Young & Zhao, Yan & Huang, Chung-Yuan, 2016. "Daily short covering activity and the weekend effect: Evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 166-184.
    4. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
    5. Xu, Feng & Wan, Difang, 2015. "The impacts of institutional and individual investors on the price discovery in stock index futures market: Evidence from China," Finance Research Letters, Elsevier, vol. 15(C), pages 221-231.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Haijun & Xue, Feng, 2021. "Analysis of stock market volatility: Adjusted VPIN with high-frequency data," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 210-222.
    2. Yildiz, Serhat & Van Ness, Bonnie & Van Ness, Robert, 2020. "VPIN, liquidity, and return volatility in the U.S. equity markets," Global Finance Journal, Elsevier, vol. 45(C).

    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. Ya-Wen Lai, 2023. "Impact of futures’ trader types on stock market quality: evidence from Taiwan," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(2), pages 417-436, June.
    2. Chang, Sanders S. & Wang, F. Albert, 2015. "Adverse selection and the presence of informed trading," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 19-33.
    3. Muchnik, Lev & Bunde, Armin & Havlin, Shlomo, 2009. "Long term memory in extreme returns of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4145-4150.
    4. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174.
    5. Ben Omrane, Walid & Hussain, Syed Mujahid, 2016. "Foreign news and the structure of co-movement in European equity markets: An intraday analysis," Research in International Business and Finance, Elsevier, vol. 37(C), pages 572-582.
    6. Siyi Liu & Xin Liu & Chuancai Zhang & Lingli Zhang, 2023. "Institutional and individual investors' short‐term reactions to the COVID‐19 crisis in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 4333-4355, December.
    7. Bank, Matthias & Baumann, Ralf H., 2016. "Price formation, market quality and the effects of reduced latency in the very short run," Research in International Business and Finance, Elsevier, vol. 37(C), pages 629-645.
    8. Lof, Matthijs & van Bommel, Jos, 2023. "Asymmetric information and the distribution of trading volume," Journal of Corporate Finance, Elsevier, vol. 82(C).
    9. Torben G. Andersen & Oleg Bondarenko, 2013. "Assessing Measures of Order Flow Toxicity via Perfect Trade Classification," CREATES Research Papers 2013-43, Department of Economics and Business Economics, Aarhus University.
    10. de Jong, Frank & Nijman, Theo & Roell, Ailsa, 1996. "Price effects of trading and components of the bid-ask spread on the Paris Bourse," Journal of Empirical Finance, Elsevier, vol. 3(2), pages 193-213, June.
    11. Köksal, Bülent, 2012. "An Analysis of Intraday Patterns and Liquidity on the Istanbul Stock Exchange," MPRA Paper 35968, University Library of Munich, Germany.
    12. Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
    13. Abad, David & Massot, Magdalena & Nawn, Samarpan & Pascual, Roberto & Yagüe, José, 2025. "Message traffic and short-term illiquidity in high-speed markets," Emerging Markets Review, Elsevier, vol. 65(C).
    14. Guglielmo Caporale & Luis Gil-Alana & Alex Plastun & Inna Makarenko, 2016. "Intraday Anomalies and Market Efficiency: A Trading Robot Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 275-295, February.
    15. Abdul Rahman & Neelesh Upadhye, 2024. "Hybrid Vector Auto Regression and Neural Network Model for Order Flow Imbalance Prediction in High Frequency Trading," Papers 2411.08382, arXiv.org.
    16. Paul Mcguinness, 1997. "Inter-day return behaviour for stocks quoted 'back-to-back' in Hong Kong and London," Applied Economics Letters, Taylor & Francis Journals, vol. 4(8), pages 459-464.
    17. Mazza, Paolo, 2015. "Price dynamics and market liquidity: An intraday event study on Euronext," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 139-153.
    18. Francis Breedon & Angelo Ranaldo, 2013. "Intraday Patterns in FX Returns and Order Flow," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(5), pages 953-965, August.
    19. Davis, Ryan L. & Roseman, Brian S. & Van Ness, Bonnie F. & Van Ness, Robert, 2017. "1-share orders and trades," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 109-117.
    20. Al-Suhaibani, Mohammad & Kryzanowski, Lawrence, 2000. "An exploratory analysis of the order book, and order flow and execution on the Saudi stock market," Journal of Banking & Finance, Elsevier, vol. 24(8), pages 1323-1357, August.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:ijefaa:v:9:y:2017:i:9:p:123-132. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.