[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v11y2018i4p76-d179490.html
   My bibliography  Save this article

Stock Market Volatility and Trading Volume: A Special Case in Hong Kong With Stock Connect Turnover

Author

Listed:
  • Brian Sing Fan Chan

    (CASH Algo Finance Group Limited, Hong Kong, China)

  • Andy Cheuk Hin Cheng

    (CASH Algo Finance Group Limited, Hong Kong, China)

  • Alfred Ka Chun Ma

    (CASH Algo Finance Group Limited, Hong Kong, China)

Abstract
The cross-boundary Shanghai-Hong Kong and Shenzhen-Hong Kong Stock Connect provides a special data set to study the dynamic relationships among volatility, trading volume and turnover among three stock markets, namely Shanghai, Shenzhen, and Hong Kong. We employ the Granger Causality test with the vector autoregressive model (VAR) to examine whether Stock Connect turnover contributes to future realized volatility and market volume of these three markets. Our results support the evidence of causality from Stock Connect turnover to market volatility and trading volume. The finding of this causality is consistent with the implication of the sequential information arrival model in the literature.

Suggested Citation

  • Brian Sing Fan Chan & Andy Cheuk Hin Cheng & Alfred Ka Chun Ma, 2018. "Stock Market Volatility and Trading Volume: A Special Case in Hong Kong With Stock Connect Turnover," JRFM, MDPI, vol. 11(4), pages 1-17, October.
  • Handle: RePEc:gam:jjrfmx:v:11:y:2018:i:4:p:76-:d:179490
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/11/4/76/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/11/4/76/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Qiyu & Chong, Terence Tai-Leung, 2018. "Co-integrated or not? After the Shanghai–Hong Kong and Shenzhen–Hong Kong Stock Connection Schemes," Economics Letters, Elsevier, vol. 163(C), pages 167-171.
    2. Huo, Rui & Ahmed, Abdullahi D., 2017. "Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect," Economic Modelling, Elsevier, vol. 61(C), pages 260-272.
    3. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    5. Burdekin, Richard C.K. & Siklos, Pierre L., 2018. "Quantifying the impact of the November 2014 Shanghai-Hong Kong Stock Connect," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 156-163.
    6. Lee, Bong-Soo & Rui, Oliver M., 2002. "The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence," Journal of Banking & Finance, Elsevier, vol. 26(1), pages 51-78, January.
    7. Darrat, Ali F. & Rahman, Shafiqur & Zhong, Maosen, 2003. "Intraday trading volume and return volatility of the DJIA stocks: A note," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 2035-2043, October.
    8. 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.
    9. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    10. 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.
    11. Yang-Chao Wang & Jui-Jung Tsai & Qiaoqiao Li, 2017. "Policy Impact on the Chinese Stock Market: From the 1994 Bailout Policies to the 2015 Shanghai-Hong Kong Stock Connect," IJFS, MDPI, vol. 5(1), pages 1-19, January.
    12. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    13. Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.
    14. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," The Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
    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. Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.
    2. Cathy W.S. Chen & Mike K.P. So & Thomas C. Chiang, 2016. "Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach," The Japanese Economic Review, Japanese Economic Association, vol. 67(1), pages 96-124, March.
    3. 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.
    4. 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.
    5. 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.
    6. Shen, Dehua & Li, Xiao & Zhang, Wei, 2018. "Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis," Economic Modelling, Elsevier, vol. 69(C), pages 127-133.
    7. Sinha, Pankaj & Agnihotri, Shalini, 2014. "Investigating impact of volatility persistence, market asymmetry and information inflow on volatility of stock indices using bivariate GJR-GARCH," MPRA Paper 58303, University Library of Munich, Germany.
    8. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    9. 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.
    10. Gurleen Sahota & Balwinder Singh, 2016. "The Empirical Investigation of Causal Relationship between Intraday Return and Volume in Indian Stock Market," Vision, , vol. 20(3), pages 199-210, September.
    11. 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).
    12. Panpan Wang & Tsungwu Ho & Yishi Li, 2020. "The Price-Volume Relationship of the Shanghai Stock Index: Structural Change and the Threshold Effect of Volatility," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    13. Alizadeh, Amir H., 2013. "Trading volume and volatility in the shipping forward freight market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 250-265.
    14. Koubaa, Yosra & Slim, Skander, 2019. "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, vol. 82(C), pages 168-184.
    15. Ngene, Geoffrey M. & Mungai, Ann Nduati, 2022. "Stock returns, trading volume, and volatility: The case of African stock markets," International Review of Financial Analysis, Elsevier, vol. 82(C).
    16. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    17. Anirut Pisedtasalasai & Abeyratna Gunasekarage, 2007. "Causal and Dynamic Relationships among Stock Returns, Return Volatility and Trading Volume: Evidence from Emerging markets in South-East Asia," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(4), pages 277-297, December.
    18. 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.
    19. Pankaj Sinha & Shalini Agnihotri, 2016. "Investigating Impact of Volatility Persistence and Information Inflow on Volatility of Stock Indices Using Bivarite GJR-GARCH," Global Business Review, International Management Institute, vol. 17(5), pages 1145-1161, October.
    20. Henryk Gurgul & Roland Mestel & Robert Syrek, 2008. "Polish Stock Market and some foreign markets - dependence analysis by copulas," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 18(2), pages 17-35.

    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:gam:jjrfmx:v:11:y:2018:i:4:p:76-:d:179490. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.