IDEAS home Printed from https://ideas.repec.org/a/eee/intfin/v27y2013icp177-201.html
   My bibliography  Save this article

On the predictive role of large futures trades for S&P500 index returns: An analysis of COT data as an informative trading signal

Author

Listed:
  • Chen, Haojun
  • Maher, Daniela

Abstract

This study examines the information role of large S&P500 futures trades (commercial, noncommercial, dealers, asset managers, and hedge funds) in shaping index returns. Using consolidated data across both standard and E-mini futures contracts, we find that commercial firms’ net trading level appears positively correlated with future index returns but the relationship is not stable across time. Based on more recent data, amongst specialist traders, hedge funds appear superior in terms of access to information and/or trading ability but this advantage is only preserved at high frequency. Therefore, the current weekly Commitment of Traders (COT) report – published with a 3-day delay – prevents timely public access to this type of information. Also, trading signals generated by a popular, position-based sentiment index do not produce significant average returns. Overall, this calls into question the reliability of COT-based trading signals used by market professionals.

Suggested Citation

  • Chen, Haojun & Maher, Daniela, 2013. "On the predictive role of large futures trades for S&P500 index returns: An analysis of COT data as an informative trading signal," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 177-201.
    • Handle: RePEc:eee:intfin:v:27:y:2013:i:c:p:177-201
    DOI: 10.1016/j.intfin.2013.09.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1042443113000723
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intfin.2013.09.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    2. Chakravarty, Sugato, 2001. "Stealth-trading: Which traders' trades move stock prices?," Journal of Financial Economics, Elsevier, vol. 61(2), pages 289-307, August.
    3. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    4. Aaron Tornell & Chunming Yuan, 2012. "Speculation and hedging in the currency futures markets: Are they informative to the spot exchange rates," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(2), pages 122-151, February.
    5. Stefan Nagel, 2012. "Evaporating Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 25(7), pages 2005-2039.
    6. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    7. Changyun Wang, 2003. "The behavior and performance of major types of futures traders," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(1), pages 1-31, January.
    8. Sanders, Dwight R. & Boris, Keith & Manfredo, Mark, 2004. "Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports," Energy Economics, Elsevier, vol. 26(3), pages 425-445, May.
    9. Hoffmann, Arvid O.I. & Post, Thomas & Pennings, Joost M.E., 2013. "Individual investor perceptions and behavior during the financial crisis," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 60-74.
    10. Xuemin (Sterling) Yan & Zhe Zhang, 2009. "Institutional Investors and Equity Returns: Are Short-term Institutions Better Informed?," The Review of Financial Studies, Society for Financial Studies, vol. 22(2), pages 893-924, February.
    11. Ming‐Yuan Leon Li, 2009. "The dynamics of the relationship between spot and futures markets under high and low variance regimes," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(6), pages 696-718, November.
    12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    13. Stoll, Hans R. & Whaley, Robert E., 1990. "The Dynamics of Stock Index and Stock Index Futures Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(4), pages 441-468, December.
    14. Schmeling, Maik, 2007. "Institutional and individual sentiment: Smart money and noise trader risk?," International Journal of Forecasting, Elsevier, vol. 23(1), pages 127-145.
    15. Bin Ke & Kathy Petroni, 2004. "How Informed Are Actively Trading Institutional Investors? Evidence from Their Trading Behavior before a Break in a String of Consecutive Earnings Increases," Journal of Accounting Research, Wiley Blackwell, vol. 42(5), pages 895-927, December.
    16. Frans A. De Roon & Theo E. Nijman & Chris Veld, 2000. "Hedging Pressure Effects in Futures Markets," Journal of Finance, American Finance Association, vol. 55(3), pages 1437-1456, June.
    17. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    18. Krista Schwarz, 2012. "Are speculators informed?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(1), pages 1-23, January.
    19. Sanders, Dwight R. & Irwin, Scott H. & Merrin, Robert P., 2009. "Smart Money: The Forecasting Ability of CFTC Large Traders in Agricultural Futures Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(2), pages 1-21, August.
    20. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    21. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    22. Leuthold, Raymond M & Garcia, Philip & Lu, Richard, 1994. "The Returns and Forecasting Ability of Large Traders in the Frozen Pork Bellies Futures Market," The Journal of Business, University of Chicago Press, vol. 67(3), pages 459-473, July.
    23. Changyun Wang, 2003. "Investor sentiment, market timing, and futures returns," Applied Financial Economics, Taylor & Francis Journals, vol. 13(12), pages 891-898.
    24. Natividad Blasco & Pilar Corredor & Rafael Santamaria, 2009. "Information spillovers between derivative markets with differences in transaction costs and liquidity," Applied Economics Letters, Taylor & Francis Journals, vol. 16(10), pages 1039-1047.
    25. Chung, San-Lin & Hung, Chi-Hsiou & Yeh, Chung-Ying, 2012. "When does investor sentiment predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 217-240.
    26. Harris, Lawrence E & Gurel, Eitan, 1986. "Price and Volume Effects Associated with Changes in the S&P 500 List: New Evidence for the Existence of Price Pressures," Journal of Finance, American Finance Association, vol. 41(4), pages 815-829, September.
    27. Anders Wilhelmsson, 2006. "Garch forecasting performance under different distribution assumptions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 561-578.
    28. Alexander F. Wolff, 2013. "Investor sentiment and stock prices in the subprime mortgage crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 23(16), pages 1301-1309, August.
    29. Bessembinder, Hendrik, 1992. "Systematic Risk, Hedging Pressure, and Risk Premiums in Futures Markets," The Review of Financial Studies, Society for Financial Studies, vol. 5(4), pages 637-667.
    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. Adam Clements & Neda Todorova, 2014. "The impact of information flow and trading activity on gold and oil futures volatility," NCER Working Paper Series 102, National Centre for Econometric Research.
    2. 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.
    3. Zhang, Xiaotao & Zhao, Yuepeng & Wang, Ziqiao, 2024. "Do loosened trading rules restore the stock index futures price discovery ability in China?," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 389-397.
    4. Adam E. Clements & Neda Todorova, 2016. "Information Flow, Trading Activity and Commodity Futures Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 88-104, January.
    5. Lai, Ya-Wen & Lin, Chiou-Fa & Tang, Mei-Ling, 2017. "Mispricing and trader positions in the S&P 500 index futures market," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 250-265.
    6. Paweł Jakubowski & Robert Ślepaczuk & Franciszek Windorbski, 2023. "REnsembling ARIMAX Model in Algorithmic Investment Strategies on Commodities Market," Working Papers 2023-20, Faculty of Economic Sciences, University of Warsaw.

    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. Lee A. Smales, 2022. "Trading Behavior in Agricultural Commodity Futures around the 52-Week High," Commodities, MDPI, vol. 1(1), pages 1-15, June.
    2. Dirk G. Baur & Lee A. Smales, 2022. "Trading behavior in bitcoin futures: Following the “smart money”," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1304-1323, July.
    3. Guillermo Llorente & Jiang Wang, 2020. "Trading and information in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(8), pages 1231-1263, August.
    4. Mutafoglu, Takvor H. & Tokat, Ekin & Tokat, Hakki A., 2012. "Forecasting precious metal price movements using trader positions," Resources Policy, Elsevier, vol. 37(3), pages 273-280.
    5. Changyun Wang, 2003. "The behavior and performance of major types of futures traders," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(1), pages 1-31, January.
    6. Georg Lehecka, 2015. "Do hedging and speculative pressures drive commodity prices, or the other way round?," Empirical Economics, Springer, vol. 49(2), pages 575-603, September.
    7. Aaron Tornell & Chunming Yuan, 2012. "Speculation and hedging in the currency futures markets: Are they informative to the spot exchange rates," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(2), pages 122-151, February.
    8. Shimeng Shi, 2022. "Bitcoin futures risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2190-2217, December.
    9. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    10. Algieri, Bernardina, 2012. "Price Volatility, Speculation and Excessive Speculation in Commodity Markets: sheep or shepherd behaviour?," Discussion Papers 124390, University of Bonn, Center for Development Research (ZEF).
    11. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predictability of crypto returns: The impact of trading behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    12. Adam E. Clements & Neda Todorova, 2016. "Information Flow, Trading Activity and Commodity Futures Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 88-104, January.
    13. Lu Wang & Feng Ma & Guoshan Liu & Qiaoqi Lang, 2023. "Do extreme shocks help forecast oil price volatility? The augmented GARCH‐MIDAS approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2056-2073, April.
    14. Babajide Fowowe, 2014. "Paper oil and physical oil: has speculative pressure in oil futures increased volatility in spot oil prices?," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(3), pages 356-372, September.
    15. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
    16. 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.
    17. Yu-Lun Chen & Yin-Feng Gau & Wen-Ju Liao, 2016. "Trading activities and price discovery in foreign currency futures markets," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 793-818, May.
    18. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    19. Lai, Ya-Wen & Lin, Chiou-Fa & Tang, Mei-Ling, 2017. "Mispricing and trader positions in the S&P 500 index futures market," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 250-265.
    20. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predicting inflation expectations: A habit-based explanation under hedging," International Review of Financial Analysis, Elsevier, vol. 89(C).

    More about this item

    Keywords

    Institutional traders; S&P500 futures; Open interest; COT report; Market efficiency;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets

    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:eee:intfin:v:27:y:2013:i:c:p:177-201. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/intfin .

    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.