IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/96784.html
   My bibliography  Save this paper

Overnight Momentum, Informational Shocks, and Late-Informed Trading in China

Author

Listed:
  • Gao, Ya
  • Han, Xing
  • Li, Youwei
  • Xiong, Xiong

Abstract

Based on high-frequency firm-level data, this paper uncovers new empirical patterns on intraday momentum in China. First, there exists a strong intraday momentum effect at the firm level. Second, the intraday predictability stems mainly from the overnight component rather than the opening half-hour component, which is consistent with the microstructure features of the Chinese market. Third, the intraday predictability attenuates (strengthens) following large positive (negative) informational shocks, implying a striking asymmetric reaction by market participants. Finally, we document that late-informed traders are relatively less experienced or skilful. Overall, the empirical results lend support to the model of late-informed trading.

Suggested Citation

  • Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight Momentum, Informational Shocks, and Late-Informed Trading in China," MPRA Paper 96784, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:96784
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/96784/1/MPRA_paper_96784.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    2. Nijman, Theo & Swinkels, Laurens & Verbeek, Marno, 2004. "Do countries or industries explain momentum in Europe?," Journal of Empirical Finance, Elsevier, vol. 11(4), pages 461-481, September.
    3. Yamamoto, Ryuichi, 2012. "Intraday technical analysis of individual stocks on the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 3033-3047.
    4. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 1-30.
    5. Gao, Lei & Han, Yufeng & Zhengzi Li, Sophia & Zhou, Guofu, 2018. "Market intraday momentum," Journal of Financial Economics, Elsevier, vol. 129(2), pages 394-414.
    6. Menkhoff, Lukas & Sarno, Lucio & Schmeling, Maik & Schrimpf, Andreas, 2012. "Currency momentum strategies," Journal of Financial Economics, Elsevier, vol. 106(3), pages 660-684.
    7. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    8. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.
    9. Xin Huang & George Tauchen, 2005. "The Relative Contribution of Jumps to Total Price Variance," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 456-499.
    10. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    11. Evans, Kevin P., 2011. "Intraday jumps and US macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2511-2527, October.
    12. Michel Beine & Jérôme Lahaye & Sébastien Laurent & Christopher J. Neely & Franz C. Palm, 2007. "Central bank intervention and exchange rate volatility, its continuous and jump components," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(2), pages 201-223.
    13. Jiang, George J. & Oomen, Roel C.A., 2008. "Testing for jumps when asset prices are observed with noise-a "swap variance" approach," Journal of Econometrics, Elsevier, vol. 144(2), pages 352-370, June.
    14. Thomas Renault, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205113, HAL.
    15. Madhavan, Ananth, 1992. "Trading Mechanisms in Securities Markets," Journal of Finance, American Finance Association, vol. 47(2), pages 607-641, June.
    16. Fama, Eugene F. & French, Kenneth R., 2012. "Size, value, and momentum in international stock returns," Journal of Financial Economics, Elsevier, vol. 105(3), pages 457-472.
    17. Vincent Bogousslavsky, 2016. "Infrequent Rebalancing, Return Autocorrelation, and Seasonality," Journal of Finance, American Finance Association, vol. 71(6), pages 2967-3006, December.
    18. Jiang, George J. & Lo, Ingrid & Verdelhan, Adrien, 2011. "Information Shocks, Liquidity Shocks, Jumps, and Price Discovery: Evidence from the U.S. Treasury Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(2), pages 527-551, April.
    19. Han, Xing & Li, Youwei, 2017. "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 212-239.
    20. Steven L. Heston & Robert A. Korajczyk & Ronnie Sadka, 2010. "Intraday Patterns in the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 65(4), pages 1369-1407, August.
    21. Andy C.W. Chui & Sheridan Titman & K.C. John Wei, 2010. "Individualism and Momentum around the World," Journal of Finance, American Finance Association, vol. 65(1), pages 361-392, February.
    22. repec:bla:jfinan:v:59:y:2004:i:2:p:755-793 is not listed on IDEAS
    23. 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.
    24. Clifford S. Asness & Tobias J. Moskowitz & Lasse Heje Pedersen, 2013. "Value and Momentum Everywhere," Journal of Finance, American Finance Association, vol. 68(3), pages 929-985, June.
    25. Dionigi Gerace & Qigui Liu & Gary Gang Tian & Willa Zheng, 2015. "Call Auction Transparency and Market Liquidity: Evidence from China," International Review of Finance, International Review of Finance Ltd., vol. 15(2), pages 223-255, June.
    26. repec:bla:jfinan:v:59:y:2004:i:1:p:227-260 is not listed on IDEAS
    27. Moskowitz, Tobias J. & Ooi, Yao Hua & Pedersen, Lasse Heje, 2012. "Time series momentum," Journal of Financial Economics, Elsevier, vol. 104(2), pages 228-250.
    28. Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten Ørregaard Nielsen, 2010. "Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 233-261.
    29. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    30. Ball, Clifford A & Torous, Walter N, 1985. "On Jumps in Common Stock Prices and Their Impact on Call Option Pricing," Journal of Finance, American Finance Association, vol. 40(1), pages 155-173, March.
    31. Laurent E. Calvet & John Y. Campbell & Paolo Sodini, 2009. "Measuring the Financial Sophistication of Households," American Economic Review, American Economic Association, vol. 99(2), pages 393-398, May.
    32. Jiang, George J. & Zhu, Kevin X., 2017. "Information Shocks and Short-Term Market Underreaction," Journal of Financial Economics, Elsevier, vol. 124(1), pages 43-64.
    33. Pritamani, Mahesh & Singal, Vijay, 2001. "Return predictability following large price changes and information releases," Journal of Banking & Finance, Elsevier, vol. 25(4), pages 631-656, April.
    34. Park, Tae-Jun & Lee, Youngjoo & Song, Kyojik “Roy”, 2014. "Informed trading before positive vs. negative earnings surprises," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 228-241.
    35. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    36. repec:bla:jfinan:v:59:y:2004:i:3:p:1345-1365 is not listed on IDEAS
    37. Sagi, Jacob S. & Seasholes, Mark S., 2007. "Firm-specific attributes and the cross-section of momentum," Journal of Financial Economics, Elsevier, vol. 84(2), pages 389-434, May.
    38. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    39. Avramov, Doron & Hore, Satadru, 2017. "Cross-sectional factor dynamics and momentum returns," Journal of Financial Markets, Elsevier, vol. 32(C), pages 69-96.
    40. Min, Byoung-Kyu & Kim, Tong Suk, 2016. "Momentum and downside risk," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 104-118.
    41. Barroso, Pedro & Santa-Clara, Pedro, 2015. "Momentum has its moments," Journal of Financial Economics, Elsevier, vol. 116(1), pages 111-120.
    42. Jiang, George J. & Lo, Ingrid, 2014. "Private information flow and price discovery in the U.S. treasury market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 118-133.
    43. Martijn Cremers & Michael Halling & David Weinbaum, 2015. "Aggregate Jump and Volatility Risk in the Cross-Section of Stock Returns," Journal of Finance, American Finance Association, vol. 70(2), pages 577-614, April.
    44. Elaut, Gert & Frömmel, Michael & Lampaert, Kevin, 2018. "Intraday momentum in FX markets: Disentangling informed trading from liquidity provision," Journal of Financial Markets, Elsevier, vol. 37(C), pages 35-51.
    45. Novy-Marx, Robert, 2012. "Is momentum really momentum?," Journal of Financial Economics, Elsevier, vol. 103(3), pages 429-453.
    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. Lin, Chaonan & Chang, Hui-Wen & Chou, Robin K., 2023. "Overnight versus intraday returns of anomalies in China," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    2. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2021. "Investor heterogeneity and momentum-based trading strategies in China," International Review of Financial Analysis, Elsevier, vol. 74(C).
    3. Kallinterakis, Vasileios & Karaa, Rabaa, 2023. "From dusk till dawn (and vice versa): Overnight-versus-daytime reversals and feedback trading," International Review of Financial Analysis, Elsevier, vol. 85(C).
    4. Zhu, Qi & Jin, Sisi & Huang, Yuxuan & Yan, Cheng, 2022. "Oil price uncertainty and stock price informativeness: Evidence from listed U.S. companies," Energy Economics, Elsevier, vol. 113(C).
    5. Ham, Hyuna & Ryu, Doojin & Webb, Robert I., 2022. "The effects of overnight events on daytime trading sessions," International Review of Financial Analysis, Elsevier, vol. 83(C).
    6. Yue, Tian & Li, Tianjiao & Ruan, Xinfeng, 2023. "Does short-term momentum exist in China?," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    7. Wang, Cheng & Bouri, Elie & Xu, Yahua & Zhang, Dingsheng, 2023. "Intraday and overnight tail risks and return predictability in the crude oil market: Evidence from oil-related regular news and extreme shocks," Energy Economics, Elsevier, vol. 127(PB).
    8. Wen, Zhuzhu & Bouri, Elie & Xu, Yahua & Zhao, Yang, 2022. "Intraday return predictability in the cryptocurrency markets: Momentum, reversal, or both," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    9. Muzhao Jin & Fearghal Kearney & Youwei Li & Yung Chiang Yang, 2020. "Intraday time‐series momentum: Evidence from China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(4), pages 632-650, April.
    10. Zhang, Wei & Wang, Pengfei & Li, Yi, 2021. "Bond intraday momentum," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    11. Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021. "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, vol. 96(C), pages 209-219.
    12. Cheema, Muhammad A. & Chiah, Mardy & Man, Yimei, 2022. "Overnight returns, daytime reversals, and future stock returns: Is China different?," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    13. Yahui An & Lin Huang & Youwei Li, 2022. "The Asymmetric Overnight Return Anomaly in the Chinese Stock Market," JRFM, MDPI, vol. 15(11), pages 1-20, November.
    14. Wouassom, Alain & Muradoğlu, Yaz Gülnur & Tsitsianis, Nicholas, 2022. "Global momentum: The optimal trading approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    15. Onishchenko, Olena & Zhao, Jing & Kuruppuarachchi, Duminda & Roberts, Helen, 2021. "Intraday time-series momentum and investor trading behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    16. Chu, Xiaojun & Wan, Xinmin & Qiu, Jianying, 2023. "The relative importance of overnight sentiment versus trading-hour sentiment in volatility forecasting," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    17. Ao Kong & Robert Azencott & Hongliang Zhu & Xindan Li, 2024. "Pattern Recognition in Microtrading Behaviors Preceding Stock Price Jumps: A Study Based on Mutual Information for Multivariate Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1401-1429, April.
    18. Zhang, Xiaotao & Li, Guoran & Li, Yishuo & Zou, Gaofeng & Wu, Ji George, 2023. "Which is more important in stock market forecasting: Attention or sentiment?," International Review of Financial Analysis, Elsevier, vol. 89(C).

    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. Simarjeet Singh & Nidhi Walia, 2022. "Momentum investing: a systematic literature review and bibliometric analysis," Management Review Quarterly, Springer, vol. 72(1), pages 87-113, February.
    2. Wen, Zhuzhu & Gong, Xu & Ma, Diandian & Xu, Yahua, 2021. "Intraday momentum and return predictability: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 95(C), pages 374-384.
    3. Li, Zeming & Sakkas, Athanasios & Urquhart, Andrew, 2022. "Intraday time series momentum: Global evidence and links to market characteristics," Journal of Financial Markets, Elsevier, vol. 57(C).
    4. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, January.
    5. Gao, Ya & Guo, Bin & Xiong, Xiong, 2021. "Signed momentum in the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    6. Docherty, Paul & Hurst, Gareth, 2018. "Return dispersion and conditional momentum returns: International evidence," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 263-278.
    7. Xu, Yahua & Bouri, Elie & Saeed, Tareq & Wen, Zhuzhu, 2020. "Intraday return predictability: Evidence from commodity ETFs and their related volatility indices," Resources Policy, Elsevier, vol. 69(C).
    8. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2021. "Investor heterogeneity and momentum-based trading strategies in China," International Review of Financial Analysis, Elsevier, vol. 74(C).
    9. Shah Saeed Hassan Chowdhury & Rashida Sharmin & M Arifur Rahman, 2019. "Presence and Sources of Contrarian Profits in the Bangladesh Stock Market," Global Business Review, International Management Institute, vol. 20(1), pages 84-104, February.
    10. Stephen A. Gorman & Frank J. Fabozzi, 2021. "The ABC’s of the alternative risk premium: academic roots," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 405-436, October.
    11. Pätäri, Eero & Karell, Ville & Luukka, Pasi & Yeomans, Julian S, 2018. "Comparison of the multicriteria decision-making methods for equity portfolio selection: The U.S. evidence," European Journal of Operational Research, Elsevier, vol. 265(2), pages 655-672.
    12. Wen, Zhuzhu & Bouri, Elie & Xu, Yahua & Zhao, Yang, 2022. "Intraday return predictability in the cryptocurrency markets: Momentum, reversal, or both," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    13. Blanco, Ivan & De Jesus, Miguel & Remesal, Alvaro, 2023. "Overlapping momentum portfolios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 1-22.
    14. Martin H. Schmidt, 2017. "Trading strategies based on past returns: evidence from Germany," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(2), pages 201-256, May.
    15. Cui, Xin & Sensoy, Ahmet & Nguyen, Duc Khuong & Yao, Shouyu & Wu, Yiyao, 2022. "Positive information shocks, investor behavior and stock price crash risk," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 493-518.
    16. Dong, Liang & Dai, Yiqing & Haque, Tariq & Kot, Hung Wan & Yamada, Takeshi, 2022. "Coskewness and reversal of momentum returns: The US and international evidence," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 241-264.
    17. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    18. Chen, Zhuo & Lu, Andrea, 2017. "Slow diffusion of information and price momentum in stocks: Evidence from options markets," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 98-108.
    19. Yuan, Xianghui & Li, Xiang, 2022. "Delta-hedging demand and intraday momentum: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    20. Victoria Dobrynskaya, 2017. "Dynamic Momentum and Contrarian Trading," HSE Working papers WP BRP 61/FE/2017, National Research University Higher School of Economics.

    More about this item

    Keywords

    intraday momentum; overnight return; price jump; late-informed trading;
    All these keywords.

    JEL classification:

    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:96784. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.