IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v171y2025ics037842662400270x.html
   My bibliography  Save this article

Diamond cuts diamond: News co-mention momentum spillover prevails in China

Author

Listed:
  • Ge, Shuyi
  • Li, Shaoran
  • Zheng, Hanyu

Abstract

We conduct a comprehensive study on momentum spillovers in the Chinese stock market using various types of economic linkages, with particular attention to momentum spillover via news co-mention linkages. We utilize millions of Chinese business news articles and develop a flexible and innovative algorithm to identify linkages among listed firms. We find that news co-mention momentum spillover is stronger than others, unifying various forms of momentum spillover effects in the Chinese market and replacing the role of analyst co-coverage in the U.S. News co-mention identifies a wide range of economically important linkages, particularly recovering more cross-industry linkages than other link identification methods, which contributes to its strong performance.

Suggested Citation

  • Ge, Shuyi & Li, Shaoran & Zheng, Hanyu, 2025. "Diamond cuts diamond: News co-mention momentum spillover prevails in China," Journal of Banking & Finance, Elsevier, vol. 171(C).
    • Handle: RePEc:eee:jbfina:v:171:y:2025:i:c:s037842662400270x
    DOI: 10.1016/j.jbankfin.2024.107356
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037842662400270X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbankfin.2024.107356?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andy C W Chui & Avanidhar Subrahmanyam & Sheridan Titman, 2022. "Momentum, Reversals, and Investor Clientele [Illiquidity and stock returns: Cross-section and time-series effects]," Review of Finance, European Finance Association, vol. 26(2), pages 217-255.
    2. Leippold, Markus & Wang, Qian & Zhou, Wenyu, 2022. "Machine learning in the Chinese stock market," Journal of Financial Economics, Elsevier, vol. 145(2), pages 64-82.
    3. Lior Menzly & Oguzhan Ozbas, 2010. "Market Segmentation and Cross‐predictability of Returns," Journal of Finance, American Finance Association, vol. 65(4), pages 1555-1580, August.
    4. Lee, Charles M.C. & Sun, Stephen Teng & Wang, Rongfei & Zhang, Ran, 2019. "Technological links and predictable returns," Journal of Financial Economics, Elsevier, vol. 132(3), pages 76-96.
    5. Jordi Mondria & Xavier Vives & Liyan Yang, 2022. "Costly Interpretation of Asset Prices," Management Science, INFORMS, vol. 68(1), pages 52-74, January.
    6. Tobias J. Moskowitz & Mark Grinblatt, 1999. "Do Industries Explain Momentum?," Journal of Finance, American Finance Association, vol. 54(4), pages 1249-1290, August.
    7. Du, Qianqian & Liang, Dawei & Chen, Zilin & Tu, Jun, 2022. "Concept links and return momentum," Journal of Banking & Finance, Elsevier, vol. 134(C).
    8. Christopher A Parsons & Riccardo Sabbatucci & Sheridan Titman, 2020. "Geographic Lead-Lag Effects," The Review of Financial Studies, Society for Financial Studies, vol. 33(10), pages 4721-4770.
    9. Hutton, Amy P. & Marcus, Alan J. & Tehranian, Hassan, 2009. "Opaque financial reports, R2, and crash risk," Journal of Financial Economics, Elsevier, vol. 94(1), pages 67-86, October.
    10. repec:bla:jfinan:v:59:y:2004:i:5:p:2145-2176 is not listed on IDEAS
    11. 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.
    12. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    13. Kewei Hou & Chen Xue & Lu Zhang, 2020. "Replicating Anomalies," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2019-2133.
    14. Lauren Cohen & Andrea Frazzini, 2008. "Economic Links and Predictable Returns," Journal of Finance, American Finance Association, vol. 63(4), pages 1977-2011, August.
    15. Burt, Aaron & Hrdlicka, Christopher, 2021. "Where Does the Predictability from Sorting on Returns of Economically Linked Firms Come From?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(8), pages 2634-2658, December.
    16. Hoberg, Gerard & Phillips, Gordon M., 2018. "Text-Based Industry Momentum," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(6), pages 2355-2388, December.
    17. Liu, Jianan & Stambaugh, Robert F. & Yuan, Yu, 2019. "Size and value in China," Journal of Financial Economics, Elsevier, vol. 134(1), pages 48-69.
    18. Kent Daniel & David Hirshleifer & Lin Sun, 2020. "Short- and Long-Horizon Behavioral Factors," The Review of Financial Studies, Society for Financial Studies, vol. 33(4), pages 1673-1736.
    19. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    20. Huang, Shiyang & Lee, Charles M.C. & Song, Yang & Xiang, Hong, 2022. "A frog in every pan: Information discreteness and the lead-lag returns puzzle," Journal of Financial Economics, Elsevier, vol. 145(2), pages 83-102.
    21. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    22. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    23. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    24. 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.
    25. Kewei Hou, 2007. "Industry Information Diffusion and the Lead-lag Effect in Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1113-1138.
    26. Hou, Kewei & Qiao, Fang & Zhang, Xiaoyan, 2023. "Finding Anomalies in China," Working Paper Series 2023-02, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    27. Hung, Weifeng & Lin, Ching-Ting & Yang, J. Jimmy, 2022. "Aggregate 52-week high, limited attention, and time-varying momentum profits," Journal of Banking & Finance, Elsevier, vol. 141(C).
    28. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    29. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    30. Gençay, Ramazan & Signori, Daniele & Xue, Yi & Yu, Xiao & Zhang, Keyi, 2015. "Economic links and credit spreads," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 157-169.
    31. Assaf Eisdorfer & Kenneth Froot & Gideon Ozik & Ronnie Sadka, 2022. "Competition Links and Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 35(9), pages 4300-4340.
    32. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    33. Han, Chunmao & Zhang, Wei, 2024. "Trading volume, anomaly returns and noise trader risk in China," Pacific-Basin Finance Journal, Elsevier, vol. 84(C).
    34. Kent Daniel & David Hirshleifer & Lin Sun, 2020. "Short- and Long-Horizon Behavioral Factors," Review of Finance, European Finance Association, vol. 33(4), pages 1673-1736.
    35. Bailey, Warren & Cai, Jun & Cheung, Yan Leung & Wang, Fenghua, 2009. "Stock returns, order imbalances, and commonality: Evidence on individual, institutional, and proprietary investors in China," Journal of Banking & Finance, Elsevier, vol. 33(1), pages 9-19, January.
    36. Ali, Usman & Hirshleifer, David, 2020. "Shared analyst coverage: Unifying momentum spillover effects," Journal of Financial Economics, Elsevier, vol. 136(3), pages 649-675.
    37. Cao, Jie & Chordia, Tarun & Lin, Chen, 2016. "Alliances and Return Predictability," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(5), pages 1689-1717, October.
    38. Chong-En Bai & Jiangyong Lu & Zhigang Tao, 2006. "The Multitask Theory of State Enterprise Reform: Empirical Evidence from China," American Economic Review, American Economic Association, vol. 96(2), pages 353-357, May.
    39. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    40. Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019. "Predicting Returns With Text Data," NBER Working Papers 26186, National Bureau of Economic Research, Inc.
    41. Huang, Shiyang & Lin, Tse-Chun & Xiang, Hong, 2021. "Psychological barrier and cross-firm return predictability," Journal of Financial Economics, Elsevier, vol. 142(1), pages 338-356.
    42. Fuxiu Jiang & Kenneth A Kim, 2020. "Corporate Governance in China: A Survey [The role of boards of directors in corporate governance: a conceptual framework and survey]," Review of Finance, European Finance Association, vol. 24(4), pages 733-772.
    43. Li Pan & Ya Tang & Jianguo Xu, 2016. "Speculative Trading and Stock Returns," Review of Finance, European Finance Association, vol. 20(5), pages 1835-1865.
    44. Liu, Beibei & Tan, Keqi & Wong, Sonia M.L. & Yip, Rita W.Y., 2022. "Intra-industry information transfer in emerging markets: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 140(C).
    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. Lee, Charles M.C. & Shi, Terrence Tianshuo & Sun, Stephen Teng & Zhang, Ran, 2024. "Production complementarity and information transmission across industries," Journal of Financial Economics, Elsevier, vol. 155(C).
    2. Xin Chen & Wei He & Libin Tao & Jianfeng Yu, 2023. "Attention and Underreaction-Related Anomalies," Management Science, INFORMS, vol. 69(1), pages 636-659, January.
    3. Avramov, D. & Ge, S. & Li, S. & Linton, O. B., 2025. "Dual Industry Effects and Cross-Stock Predictability," Janeway Institute Working Papers 2506, Faculty of Economics, University of Cambridge.
    4. Cao, Zhengyu & Wang, Rundong & Xiao, Xinrong & Yin, Chengxi, 2023. "Disseminating information across connected firms — Analyst site visits can help," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 510-531.
    5. Chen, Zilin & Chu, Liya & Liang, Dawei & Tu, Jun, 2022. "Far away from home: Investors’ underreaction to geographically dispersed information," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    6. Du, Qianqian & Liang, Dawei & Chen, Zilin & Tu, Jun, 2022. "Concept links and return momentum," Journal of Banking & Finance, Elsevier, vol. 134(C).
    7. Avramov, D. & Ge, S. & Li, S. & Linton, O. B., 2025. "Dual Industry Effects and Cross-Stock Predictability," Cambridge Working Papers in Economics 2512, Faculty of Economics, University of Cambridge.
    8. Yan, Jingda & Yu, Jialin, 2023. "Cross-stock momentum and factor momentum," Journal of Financial Economics, Elsevier, vol. 150(2).
    9. Ying, Jie, 2024. "Gradual information diffusion across commonly owned firms," Journal of Financial Economics, Elsevier, vol. 156(C).
    10. Huang, Shiyang & Lin, Tse-Chun & Xiang, Hong, 2021. "Psychological barrier and cross-firm return predictability," Journal of Financial Economics, Elsevier, vol. 142(1), pages 338-356.
    11. Jin, Zuben, 2024. "Business aspects in focus, investor underreaction and return predictability," Journal of Corporate Finance, Elsevier, vol. 84(C).
    12. Lin, Mei-Chen, 2024. "Shared analyst coverage, 52-week high, and cross-firm return predictability," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    13. 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.
    14. Peng, Ya & Zhang, Xueyong, 2024. "Economic policy uncertainty in OFDI host countries and the cross-section of stock returns," Journal of International Money and Finance, Elsevier, vol. 149(C).
    15. Hollstein, Fabian, 2022. "The world of anomalies: Smaller than we think?," Journal of International Money and Finance, Elsevier, vol. 129(C).
    16. Bagnara, Matteo, 2024. "The economic value of cross-predictability: A performance-based measure," SAFE Working Paper Series 424, Leibniz Institute for Financial Research SAFE.
    17. Lee, Charles M.C. & Sun, Stephen Teng & Wang, Rongfei & Zhang, Ran, 2019. "Technological links and predictable returns," Journal of Financial Economics, Elsevier, vol. 132(3), pages 76-96.
    18. Lin, Mei-Chen, 2024. "Salience, psychological anchors, and stock return predictability," Pacific-Basin Finance Journal, Elsevier, vol. 88(C).
    19. Yi, Biao & Guo, Shuxin, 2022. "Common analyst links and predictable returns: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    20. Hanauer, Matthias X. & Jansen, Maarten & Swinkels, Laurens & Zhou, Weili, 2024. "Factor models for Chinese A-shares," International Review of Financial Analysis, Elsevier, vol. 91(C).

    More about this item

    Keywords

    Economic linkage; Big textual data; Momentum spillover; News co-mention; Limited attention;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • 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:eee:jbfina:v:171:y:2025:i:c:s037842662400270x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbf .

    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.