IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v31y2026i1p151-173.html

Information Flows, Stock Market Volatility and the Systemic Risk in Global Finance

Author

Listed:
  • Yen‐Hsiao Chen
  • Jiang Wu
  • Richard McManus
  • Yang Liu

Abstract

Information flows are a theoretical explanation for stock market volatility, but controversy remains regarding how to measure them. Based on cross‐sectional and temporal properties of information flows, we decompose total trading volume into four types: cross‐country shocks and country‐specific shocks due to arrivals of private information, and trading volume shocks and stock volatility shocks due to public information. We then use a Structural Vector Autoregressive model to reconstruct historical trading volume resulted from the four types of information shocks. The evidence shows that the historical trading volumes due to private information flow can explain volatility clustering of stock markets. By analysing sources of information flow, we find private information flow reflects systemic risk in the global financial system. The result conforms to Mixture of Distribution Hypothesis and finds that quality of information content is what differentiates privately informed trading from public information trading. It further suggests the main drivers of stock market volatility are uncertainties about fundamental values of assets and about other investors' behaviours.

Suggested Citation

  • Yen‐Hsiao Chen & Jiang Wu & Richard McManus & Yang Liu, 2026. "Information Flows, Stock Market Volatility and the Systemic Risk in Global Finance," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 31(1), pages 151-173, January.
    • Handle: RePEc:wly:ijfiec:v:31:y:2026:i:1:p:151-173
    DOI: 10.1002/ijfe.3132
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.3132
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ijfe.3132?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. Yen-Hsiao Chen & Lianfeng Quan, 2013. "Rational speculative bubbles in the Asian stock markets: Tests on deterministic explosive bubbles and stochastic explosive root bubbles," Journal of Asset Management, Palgrave Macmillan, vol. 14(3), pages 195-208, June.
    2. James C. Luu & Martin Martens, 2003. "Testing the mixture‐of‐distributions hypothesis using “realized” volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(7), pages 661-679, July.
    3. 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).
    4. Pedro Galeano & Ruey S. Tsay, 2010. "Shifts in Individual Parameters of a GARCH Model," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 122-153, Winter.
    5. Jeff Fleming & Chris Kirby & Barbara Ostdiek, 2006. "Stochastic Volatility, Trading Volume, and the Daily Flow of Information," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1551-1590, May.
    6. Xu, Liao & Gao, Han & Shi, Yukun & Zhao, Yang, 2020. "The heterogeneous volume-volatility relations in the exchange-traded fund market: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 400-408.
    7. Giampiero Gallo & Barbara Pacini, 2000. "The effects of trading activity on market volatility," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 163-175.
    8. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    9. Chuluun, Tuugi, 2017. "Global portfolio investment network and stock market comovement," Global Finance Journal, Elsevier, vol. 33(C), pages 51-68.
    10. 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.
    11. Darolles, Serge & Le Fol, Gaëlle & Mero, Gulten, 2017. "Mixture of distribution hypothesis: Analyzing daily liquidity frictions and information flows," Journal of Econometrics, Elsevier, vol. 201(2), pages 367-383.
    12. Rachael Carroll & Colm Kearney, 2012. "Do trading volumes explain the persistence of GARCH effects?," Applied Financial Economics, Taylor & Francis Journals, vol. 22(23), pages 1993-2008, December.
    13. Niklas Wagner & Terry Marsh, 2005. "Surprise volume and heteroskedasticity in equity market returns," Quantitative Finance, Taylor & Francis Journals, vol. 5(2), pages 153-168.
    14. Bohl, Martin T. & Henke, Harald, 2003. "Trading volume and stock market volatility: The Polish case," International Review of Financial Analysis, Elsevier, vol. 12(5), pages 513-525.
    15. Balcilar, Mehmet & Elsayed, Ahmed H. & Hammoudeh, Shawkat, 2023. "Financial connectedness and risk transmission among MENA countries: Evidence from connectedness network and clustering analysis1," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    16. Rowland K. Atiase & Bipin B. Ajinkya & Alex K. Dontoh & Michael J. Gift, 2011. "The Fundamental Determinants Of Trading Volume Reaction To Financial Information: Evidence And Implications For Empirical Capital Market Research," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 34(1), pages 61-101, March.
    17. Suominen, Matti, 2001. "Trading Volume and Information Revelation in Stock Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(4), pages 545-565, December.
    18. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    19. Shekar Bose & Hafizur Rahman, 2015. "Examining the relationship between stock return volatility and trading volume: new evidence from an emerging economy," Applied Economics, Taylor & Francis Journals, vol. 47(18), pages 1899-1908, April.
    20. Yen-Hsiao Chen & Patricia Fraser, 2010. "What drives stock prices? Fundamentals, bubbles and investor behaviour," Applied Financial Economics, Taylor & Francis Journals, vol. 20(18), pages 1461-1477.
    21. Shi, Yanlin & Ho, Kin-Yip & Liu, Wai-Man, 2016. "Public information arrival and stock return volatility: Evidence from news sentiment and Markov Regime-Switching Approach," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 291-312.
    22. Saswat Patra & Malay Bhattacharyya, 2021. "Does volume really matter? A risk management perspective using cross‐country evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 118-135, January.
    23. Bollerslev, Tim & Jubinski, Dan, 1999. "Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 9-21, January.
    24. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Intra- and inter-regional return and volatility spillovers across emerging and developed markets: Evidence from stock indices and stock index futures," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 96-114.
    25. Megaritis, Anastasios & Vlastakis, Nikolaos & Triantafyllou, Athanasios, 2021. "Stock market volatility and jumps in times of uncertainty," Journal of International Money and Finance, Elsevier, vol. 113(C).
    26. Slim, Skander & Dahmene, Meriam, 2016. "Asymmetric information, volatility components and the volume–volatility relationship for the CAC40 stocks," Global Finance Journal, Elsevier, vol. 29(C), pages 70-84.
    27. Jan Schneider, 2009. "A Rational Expectations Equilibrium with Informative Trading Volume," Journal of Finance, American Finance Association, vol. 64(6), pages 2783-2805, December.
    28. Darolles, Serge & Fol, Gaëlle Le & Mero, Gulten, 2015. "Measuring the liquidity part of volume," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 92-105.
    29. 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.
    30. Bajzik, Josef, 2021. "Trading volume and stock returns: A meta-analysis," International Review of Financial Analysis, Elsevier, vol. 78(C).
    31. Craig S. Hakkio & William R. Keeton, 2009. "Financial stress: what is it, how can it be measured, and why does it matter?," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q II), pages 5-50.
    32. Arago, Vicent & Nieto, Luisa, 2005. "Heteroskedasticity in the returns of the main world stock exchange indices: volume versus GARCH effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(3), pages 271-284, July.
    33. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    34. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. "Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
    35. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 94-112.
    36. 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.
    37. Hautsch, Nikolaus & Hess, Dieter, 2007. "Bayesian Learning in Financial Markets: Testing for the Relevance of Information Precision in Price Discovery," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(1), pages 189-208, March.
    38. Engle, Robert F & Ito, Takatoshi & Lin, Wen-Ling, 1990. "Meteor Showers or Heat Waves? Heteroskedastic Intra-daily Volatility in the Foreign Exchange Market," Econometrica, Econometric Society, vol. 58(3), pages 525-542, May.
    39. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
    40. Park, Beum-Jo, 2010. "Surprising information, the MDH, and the relationship between volatility and trading volume," Journal of Financial Markets, Elsevier, vol. 13(3), pages 344-366, August.
    41. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    2. 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.
    3. You‐How Go & Wee‐Yeap Lau, 2023. "What do we know about informational efficiency? Three puzzles and the new direction forward," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1489-1525, September.
    4. Kumar, Brajesh & Singh, Priyanka & Pandey, Ajay, 2009. "The Dynamic Relationship between Price and Trading Volume:Evidence from Indian Stock Market," IIMA Working Papers WP2009-12-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    5. 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.
    6. Brajesh Kumar, 2010. "The Dynamic Relationship between Price and Trading Volume: Evidence from Indian Stock Market," Working Papers id:2379, eSocialSciences.
    7. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2019. "Liquidity, surprise volume and return premia in the oil market," Energy Economics, Elsevier, vol. 77(C), pages 93-104.
    8. Carroll, Rachael & Kearney, Colm, 2015. "Testing the mixture of distributions hypothesis on target stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 1-14.
    9. Saswat Patra & Malay Bhattacharyya, 2021. "Does volume really matter? A risk management perspective using cross‐country evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 118-135, January.
    10. Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.
    11. 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.
    12. Jawadi Fredj & Ureche-Rangau Loredana, 2013. "Threshold linkages between volatility and trading volume: evidence from developed and emerging markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 313-333, May.
    13. Eric Girard & Mohammed Omran, 2009. "On the relationship between trading volume and stock price volatility in CASE," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 5(1), pages 110-134, February.
    14. Go, You-How & Lau, Wee-Yeap, 2020. "The impact of global financial crisis on informational efficiency: Evidence from price-volume relation in crude palm oil futures market," Journal of Commodity Markets, Elsevier, vol. 17(C).
    15. Ruwei Zhao & Xiong Xiong & Junjun Ma & Yuzhao Zhang & Yongjie Zhang, 2025. "Baidu News and the return volatility of Chinese commodity futures: evidence for the sequential information arrival hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-24, December.
    16. 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).
    17. You-How Go & Wee-Yeap Lau, 2020. "Does Trading Volume explain the Information Flow of Crude Palm Oil Futures Returns?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 12(2), pages 115-136, December.
    18. Sarika Mahajan & Balwinder Singh, 2008. "An Empirical Analysis of Stock Price-Volume Relationship in Indian Stock Market," Vision, , vol. 12(3), pages 1-13, July.
    19. 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.
    20. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

    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:wly:ijfiec:v:31:y:2026:i:1:p:151-173. 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: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.