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

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  • 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
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    References listed on IDEAS

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    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
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    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. 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.
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    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.

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    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

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