IDEAS home Printed from https://ideas.repec.org/a/zbw/ifweej/201926.html
   My bibliography  Save this article

The difference in the intraday return-volume relationships of spot and futures: A quantile regression approach

Author

Listed:
  • Lee, Jaeram
  • Lee, Geul
  • Ryu, Doojin

Abstract

This study illuminates the difference in the intraday return-volume relationships of spot and index futures. The quantile regression analyses show that the widening effect of the spot trading volume on the distribution of spot returns disappears within a short period of time, whereas that of the futures trading volume on the distribution of spot returns remains over the relatively long term. The short-term effect of the spot volume and the long-term effect of the futures volume are consistent for trading volume shocks. The findings suggest that the spot volume is primarily induced by the demand for hedging or differences of opinion, whereas the futures volume contains information about price movements.

Suggested Citation

  • Lee, Jaeram & Lee, Geul & Ryu, Doojin, 2019. "The difference in the intraday return-volume relationships of spot and futures: A quantile regression approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-38.
    • Handle: RePEc:zbw:ifweej:201926
    DOI: 10.5018/economics-ejournal.ja.2019-26
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.5018/economics-ejournal.ja.2019-26
    Download Restriction: no
    File URL: https://www.econstor.eu/bitstream/10419/194569/1/1662463766.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.5018/economics-ejournal.ja.2019-26?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
    ---><---

    References listed on IDEAS

    as
    1. Diks Cees & Panchenko Valentyn, 2005. "A Note on the Hiemstra-Jones Test for Granger Non-causality," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-9, June.
    2. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    3. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    4. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2019. "Forecasting the KOSPI200 spot volatility using various volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 156-166.
    5. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    6. Hee‐Joon Ahn & Jangkoo Kang & Doojin Ryu, 2008. "Informed trading in the index option market: The case of KOSPI 200 options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(12), pages 1118-1146, December.
    7. Chung, Kee H. & Park, Seongkyu “Gilbert” & Ryu, Doojin, 2016. "Trade duration, informed trading, and option moneyness," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 395-411.
    8. Badshah, Ihsan & Frijns, Bart & Knif, Johan & Tourani-Rad, Alireza, 2016. "Asymmetries of the intraday return-volatility relation," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 182-192.
    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. Doojin Ryu & Jinyoung Yu, 2022. "Sentiment‐dependent impact of funding liquidity shocks on futures market liquidity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 61-76, January.
    2. Osuji E. & Evans O., 2020. "Tourism Effects of Pandemics: New Insights from Novel Coronavirus," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 70(3-4), pages 56-65, July-Dece.
    3. Daehyeon PARK & Doojin RYU, 2021. "Forecasting Stock Market Dynamics using Bidirectional Long Short-Term Memory," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 22-34, June.
    4. Hyuna Ham & Hoon Cho & Hyeongjun Kim & Doojin Ryu, 2019. "Time‐series momentum in China's commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1515-1528, December.
    5. Daehyeon Park & Jiyeon Park & Doojin Ryu, 2020. "Volatility Spillovers between Equity and Green Bond Markets," Sustainability, MDPI, vol. 12(9), pages 1-12, May.

    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, Jaeram & Lee, Geul & Ryu, Doojin, 2018. "Difference in the intraday return-volume relationships of spots and futures: A quantile regression approach," Economics Discussion Papers 2018-68, Kiel Institute for the World Economy (IfW Kiel).
    2. Doojin RYU & Hyein SHIM, 2017. "Intraday Dynamics of Asset Returns, Trading Activities, and Implied Volatilities: A Trivariate GARCH Framework," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 45-61, June.
    3. Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.
    4. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    5. Shyh-Wei Chen, 2008. "Untangling the nexus of stock price and trading volume: evidence from the Chinese stock market," Economics Bulletin, AccessEcon, vol. 7(15), pages 1-16.
    6. repec:ebl:ecbull:v:7:y:2008:i:15:p:1-16 is not listed on IDEAS
    7. Michelle B Graczyk & Sílvio M Duarte Queirós, 2017. "Intraday seasonalities and nonstationarity of trading volume in financial markets: Collective features," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    8. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "How does trading volume affect financial return distributions?," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 190-206.
    9. Abhinava Tripathi, 2021. "The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 7-19, January.
    10. Elina Pradkhan, 2016. "Information Content of Trading Activity in Precious Metals Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 421-456, May.
    11. Loredana Ureche-Rangau & Quiterie de Rorthays, 2009. "More on the volatility-trading volume relationship in emerging markets: The Chinese stock market," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 779-799.
    12. Holmes, Phil & Rougier, Jonathan, 2005. "Trading volume and contract rollover in futures contracts," Journal of Empirical Finance, Elsevier, vol. 12(2), pages 317-338, March.
    13. Kausik Chaudhuri & Alok Kumar, 2015. "A Markov-Switching Model for Indian Stock Price and Volume," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 14(3), pages 239-257, December.
    14. Yao, Yi & Yang, Rong & Liu, Zhiyuan & Hasan, Iftekhar, 2013. "Government intervention and institutional trading strategy: Evidence from a transition country," Global Finance Journal, Elsevier, vol. 24(1), pages 44-68.
    15. Alizadeh, Amir H. & Tamvakis, Michael, 2016. "Market conditions, trader types and price–volume relation in energy futures markets," Energy Economics, Elsevier, vol. 56(C), pages 134-149.
    16. David McMillan & Alan Speight, 2002. "Return-volume dynamics in UK futures," Applied Financial Economics, Taylor & Francis Journals, vol. 12(10), pages 707-713.
    17. repec:dau:papers:123456789/5069 is not listed on IDEAS
    18. Chou, Ke-Hsin & Day, Min-Yuh & Chiu, Chien-Liang, 2023. "Do bitcoin news information flow and return volatility fit the sequential information arrival hypothesis and the mixture of distribution hypothesis?," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 365-385.
    19. Sun, Changyou, 2013. "Price variation and volume dynamics of securitized timberlands," Forest Policy and Economics, Elsevier, vol. 27(C), pages 44-53.
    20. Farag, Hisham & Cressy, Robert, 2011. "Do regulatory policies affect the flow of information in emerging markets?," Research in International Business and Finance, Elsevier, vol. 25(3), pages 238-254, September.
    21. Park, Beum-Jo, 2022. "The COVID-19 pandemic, volatility, and trading behavior in the bitcoin futures market," Research in International Business and Finance, Elsevier, vol. 59(C).
    22. Rashid, Abdul, 2007. "Stock prices and trading volume: An assessment for linear and nonlinear Granger causality," Journal of Asian Economics, Elsevier, vol. 18(4), pages 595-612, August.

    More about this item

    Keywords

    index futures; information channel; intraday information content; option- implied volatility; quantile regression; return-volume relationship;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:zbw:ifweej:201926. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iwkiede.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.