IDEAS home Printed from https://ideas.repec.org/a/bla/acctfi/v57y2017i5p1287-1313.html
   My bibliography  Save this article

Does the T + 1 rule really reduce speculation? Evidence from Chinese Stock Index ETF

Author

Listed:
  • Xinyun Chen
  • Yan Liu
  • Tao Zeng

Abstract

Stock market in China is subject to the T + 1 rule, which requires investors to hold the asset for at least 1 day before selling. This rule was initially imposed in the mid‐1990s, replacing the previous T + 0 rule, to prevent excessive speculative trading. Given the considerable changes in China's financial market over the past 20 years, it is controversial whether the T + 1 rule should be replaced by the T + 0 rule in today's market. In this paper, we empirically test the effect of the T + 1 rule on market speculation. To identify potentially different impacts of the T + 1 and T + 0 rule, we choose a unique pair of CSI 300 ETFs, one subject to the T + 1 rule while the other to the T + 0 rule. Based on an error correction model, we develop an empirical methodology to test intraday speculation in the ETF price. Our empirical results show that, at least under current market condition, the T + 1 rule reduces the price efficiency and spurs more speculation when the market liquidity is not in a shortage.

Suggested Citation

  • Xinyun Chen & Yan Liu & Tao Zeng, 2017. "Does the T + 1 rule really reduce speculation? Evidence from Chinese Stock Index ETF," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1287-1313, December.
    • Handle: RePEc:bla:acctfi:v:57:y:2017:i:5:p:1287-1313
    DOI: 10.1111/acfi.12330
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/acfi.12330
    Download Restriction: no
    File URL: https://libkey.io/10.1111/acfi.12330?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. Joel Hasbrouck, 2003. "Intraday Price Formation in U.S. Equity Index Markets," Journal of Finance, American Finance Association, vol. 58(6), pages 2375-2400, December.
    2. Wei Xiong & Jialin Yu, 2011. "The Chinese Warrants Bubble," Working Papers 1398, Princeton University, Department of Economics, Econometric Research Program..
    3. Wei Xiong & Jialin Yu, 2011. "The Chinese Warrants Bubble," American Economic Review, American Economic Association, vol. 101(6), pages 2723-2753, October.
    4. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    5. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    6. Jose A. Scheinkman & Wei Xiong, 2003. "Overconfidence and Speculative Bubbles," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1183-1219, December.
    7. Deng, Ai & Perron, Pierre, 2008. "The Limit Distribution Of The Cusum Of Squares Test Under General Mixing Conditions," Econometric Theory, Cambridge University Press, vol. 24(3), pages 809-822, June.
    8. Jianping Mei & Jose A. Scheinkman & Wei Xiong, 2009. "Speculative Trading and Stock Prices: Evidence from Chinese A-B Share Premia," Annals of Economics and Finance, Society for AEF, vol. 10(2), pages 225-255, November.
    9. Stephen Morris, 1996. "Speculative Investor Behavior and Learning," The Quarterly Journal of Economics, Oxford University Press, vol. 111(4), pages 1111-1133.
    10. Xiao, Zhijie & Phillips, Peter C. B., 2002. "A CUSUM test for cointegration using regression residuals," Journal of Econometrics, Elsevier, vol. 108(1), pages 43-61, May.
    11. Jose A. Scheinkman, 2013. "Speculation, Trading and Bubbles Third Annual Arrow Lecture," Working Papers 1458, Princeton University, Department of Economics, Econometric Research Program..
    12. Guo, Ming & Li, Zhan & Tu, Zhiyong, 2012. "A unique “T+1 trading rule” in China: Theory and evidence," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 575-583.
    13. Kramer, Walter & Ploberger, Werner & Alt, Raimund, 1988. "Testing for Structural Change in Dynamic Models," Econometrica, Econometric Society, vol. 56(6), pages 1355-1369, November.
    14. Nivine Richie & Robert T. Daigler & Kimberly C. Gleason, 2008. "The limits to stock index arbitrage: Examining S&P 500 futures and SPDRS," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(12), pages 1182-1205, December.
    15. Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2013. "ETF arbitrage: Intraday evidence," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3486-3498.
    16. Vasilev, Aleksandar & Maksumov, Rashid, 2010. "Critical analysis of Chapter 23 of Keynes’s Notes on Mercantilism in The General Theory of Employment, Interest and Money (1936)," EconStor Research Reports 155318, ZBW - Leibniz Information Centre for Economics.
    17. Chang, Eric C. & Luo, Xingguo & Shi, Lei & Zhang, Jin E., 2013. "Is warrant really a derivative? Evidence from the Chinese warrant market," Journal of Financial Markets, Elsevier, vol. 16(1), pages 165-193.
    18. J. Michael Harrison & David M. Kreps, 1978. "Speculative Investor Behavior in a Stock Market with Heterogeneous Expectations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 92(2), pages 323-336.
    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. Jianlei Han & Jing He & Zheyao Pan & Jing Shi, 2018. "Twenty Years of Accounting and Finance Research on the Chinese Capital Market," Abacus, Accounting Foundation, University of Sydney, vol. 54(4), pages 576-599, December.
    2. Yi Jiang & Stewart Jones, 2018. "Corporate distress prediction in China: a machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(4), pages 1063-1109, December.
    3. Hua Wang & Liao Xu, 2019. "Do exchange‐traded fund flows increase the volatility of the underlying index? Evidence from the emerging market in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1525-1548, March.
    4. Xiong Xiong & Chunchun Luo & Ye Zhang & Shen Lin, 2019. "Do stock bulletin board systems (BBS) contain useful information? A viewpoint of interaction between BBS quality and predicting ability," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1385-1411, March.
    5. Zhuwei Li & Xuejiao Lu & Yuan Fu, 2022. "Interaction influence of trading rules on the quality of stock markets: the price limit rule and day trading rule from the Shanghai and Shenzhen Stock exchanges," Applied Economics, Taylor & Francis Journals, vol. 54(56), pages 6467-6479, December.
    6. Jilong Chen & Liao Xu & Yang Zhao, 2020. "Do ETF flows increase market efficiency? Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(5), pages 4795-4819, December.
    7. Bao, Zhengyang & Kalaycı, Kenan & Leibbrandt, Andreas & Oyarzun, Carlos, 2020. "Do regulations work? A comprehensive analysis of price limits and trading restrictions in experimental asset markets with deterministic and stochastic fundamental values," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 59-84.

    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. Wei Xiong, 2013. "Bubbles, Crises, and Heterogeneous Beliefs," NBER Working Papers 18905, National Bureau of Economic Research, Inc.
    2. Liu, Clark & Wang, Shujing & Wei, K.C. John, 2021. "Demand shock, speculative beta, and asset prices: Evidence from the Shanghai-Hong Kong Stock Connect program," Journal of Banking & Finance, Elsevier, vol. 126(C).
    3. Feng, Xunan & Johansson, Anders C., 2016. "Judging a Book by Its Cover: Analysts and Attention-Driven Price Patterns in China’s IPO Market," Stockholm School of Economics Asia Working Paper Series 2016-39, Stockholm School of Economics, Stockholm China Economic Research Institute.
    4. Wang, Peipei & Wen, Yuanji & Singh, Harminder, 2017. "The high-volume return premium: Does it exist in the Chinese stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 46(PB), pages 323-336.
    5. Yu-Jane Liu & Zheng Zhang & Longkai Zhao, 2015. "Speculation Spillovers," Management Science, INFORMS, vol. 61(3), pages 649-664, March.
    6. Penasse, J.N.G. & Renneboog, L.D.R., 2014. "Bubbles and Trading Frenzies : Evidence from the Art Market," Other publications TiSEM bf0d8984-df7f-4f02-afc7-3, Tilburg University, School of Economics and Management.
    7. Liao, Jingchi & Peng, Cameron & Zhu, Ning, 2021. "Extrapolative bubbles and trading volume," LSE Research Online Documents on Economics 118887, London School of Economics and Political Science, LSE Library.
    8. Werner, Jan, 2022. "Speculative trade under ambiguity," Journal of Economic Theory, Elsevier, vol. 199(C).
    9. Kirchler, Michael & Bonn, Caroline & Huber, Jürgen & Razen, Michael, 2015. "The “inflow-effect”—Trader inflow and price efficiency," European Economic Review, Elsevier, vol. 77(C), pages 1-19.
    10. Jose A. Scheinkman, 2013. "Speculation, Trading and Bubbles Third Annual Arrow Lecture," Working Papers 1458, Princeton University, Department of Economics, Econometric Research Program..
    11. Julien Pénasse & Luc Renneboog & José A Scheinkman & Stijn Van Nieuwerburgh, 2021. "When a Master Dies: Speculation and Asset Float [Optimal financial crises]," The Review of Financial Studies, Society for Financial Studies, vol. 34(8), pages 3840-3879.
    12. Julien Pénasse & Luc Renneboog, 2022. "Speculative Trading and Bubbles: Evidence from the Art Market," Management Science, INFORMS, vol. 68(7), pages 4939-4963, July.
    13. Brunnermeier, Markus K. & Oehmke, Martin, 2013. "Bubbles, Financial Crises, and Systemic Risk," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1221-1288, Elsevier.
    14. Utz Weitzel & Christoph Huber & Jürgen Huber & Michael Kirchler & Florian Lindner & Julia Rose & Lauren Cohen, 2020. "Bubbles and Financial Professionals [Margin, short sell, and lotteries in experimental asset markets]," The Review of Financial Studies, Society for Financial Studies, vol. 33(6), pages 2659-2696.
    15. Liao, Jingchi & Peng, Cheng & Zhu, Ning, 2019. "Price and volume dynamics in bubbles," LSE Research Online Documents on Economics 102057, London School of Economics and Political Science, LSE Library.
    16. Andrade, Sandro C. & Bian, Jiangze & Burch, Timothy R., 2013. "Analyst Coverage, Information, and Bubbles," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(5), pages 1573-1605, October.
    17. Pavlidis, Efthymios G. & Vasilopoulos, Kostas, 2020. "Speculative bubbles in segmented markets: Evidence from Chinese cross-listed stocks," Journal of International Money and Finance, Elsevier, vol. 109(C).
    18. Wei Xiong & Jialin Yu, 2011. "The Chinese Warrants Bubble," American Economic Review, American Economic Association, vol. 101(6), pages 2723-2753, October.
    19. Michael Kirchler & Caroline Bonn & Jürgen Huber & Michael Razen, 2014. "The "Inflow-Effect" - Trader Inflow and Bubble Formation in Asset Markets," Working Papers 2014-22, Faculty of Economics and Statistics, Universität Innsbruck.
    20. Liao, Jingchi & Peng, Cameron & Zhu, Ning, 2022. "Extrapolative bubbles and trading volume," LSE Research Online Documents on Economics 110514, London School of Economics and Political Science, LSE Library.

    More about this item

    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:bla:acctfi:v:57:y:2017:i:5:p:1287-1313. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/aaanzea.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.