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The financial risk concern in China: A powerful predictor of stock market volatility

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  • Li, Zijun
  • Ma, Feng
  • Zhang, Jixiang
  • Zhou, Xiaozhou

Abstract

This paper constructs the financial risk concern (RC) in China based on four primary types of textual sources. We find that the RC is a powerful negative predictor of future stock market volatility, which predictive power is significantly greater than that of other previously examined macroeconomic, risk and uncertainty variables. In the weekly analysis, we observe a reversal in the impact of risk concern on stock market volatility, shifting from positive to negative, which reflects proactive risk-averse by investors and market self-adaptation. We also demonstrate that risk concern has long-term predictive power. In cross-sectional analysis, we find it has a greater impact during periods of low volatility, and particularly affects state-owned enterprises and downstream industries.

Suggested Citation

  • Li, Zijun & Ma, Feng & Zhang, Jixiang & Zhou, Xiaozhou, 2025. "The financial risk concern in China: A powerful predictor of stock market volatility," Research in International Business and Finance, Elsevier, vol. 80(C).
  • Handle: RePEc:eee:riibaf:v:80:y:2025:i:c:s0275531925003848
    DOI: 10.1016/j.ribaf.2025.103128
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    1. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    2. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    3. Corsi, Fulvio & Pirino, Davide & Renò, Roberto, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Journal of Econometrics, Elsevier, vol. 159(2), pages 276-288, December.
    4. Caldara, Dario & Iacoviello, Matteo & Molligo, Patrick & Prestipino, Andrea & Raffo, Andrea, 2020. "The economic effects of trade policy uncertainty," Journal of Monetary Economics, Elsevier, vol. 109(C), pages 38-59.
    5. A. Garel & A. Petit-Romec & Z. Sautner & A. Wagner, 2024. "Do investors care about biodiversity?," Post-Print hal-04649052, HAL.
    6. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    7. Nour Meddahi, 2002. "A theoretical comparison between integrated and realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 479-508.
    8. Zhi Da & Joseph Engelberg & Pengjie Gao, 2015. "Editor's Choice The Sum of All FEARS Investor Sentiment and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 1-32.
    9. Alexandre Garel & Arthur Romec & Zacharias Sautner & Alexander F Wagner, 2024. "Do investors care about biodiversity?," Review of Finance, European Finance Association, vol. 28(4), pages 1151-1186.
    10. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2022. "Investor Sentiment and Paradigm Shifts in Equity Return Forecasting," Management Science, INFORMS, vol. 68(6), pages 4301-4325, June.
    11. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
    12. Della Corte, Pasquale & Ramadorai, Tarun & Sarno, Lucio, 2016. "Volatility risk premia and exchange rate predictability," Journal of Financial Economics, Elsevier, vol. 120(1), pages 21-40.
    13. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    14. Dashan Huang & Fuwei Jiang & Kunpeng Li & Guoshi Tong & Guofu Zhou, 2022. "Scaled PCA: A New Approach to Dimension Reduction," Management Science, INFORMS, vol. 68(3), pages 1678-1695, March.
    15. Asquith, Paul & Mikhail, Michael B. & Au, Andrea S., 2005. "Information content of equity analyst reports," Journal of Financial Economics, Elsevier, vol. 75(2), pages 245-282, February.
    16. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    17. Michael Roos & Matthias Reccius, 2024. "Narratives in economics," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 303-341, April.
    18. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    19. Ma, Feng & Wu, Hanlin & Zeng, Qing, 2024. "Biodiversity and stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    20. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    21. Xiao, Jihong & Wen, Fenghua & Zhao, Yupei & Wang, Xiong, 2021. "The role of US implied volatility index in forecasting Chinese stock market volatility: Evidence from HAR models," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 311-333.
    22. Qiang Cheng & Fei Du & Brian Yutao Wang & Xin Wang, 2019. "Do Corporate Site Visits Impact Stock Prices?," Contemporary Accounting Research, John Wiley & Sons, vol. 36(1), pages 359-388, March.
    23. Lee, Wayne Y. & Jiang, Christine X. & Indro, Daniel C., 2002. "Stock market volatility, excess returns, and the role of investor sentiment," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2277-2299.
    24. Guo, Hui & Savickas, Robert, 2006. "Idiosyncratic Volatility, Stock Market Volatility, and Expected Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 43-56, January.
    25. Christian Conrad & Karin Loch, 2015. "Anticipating Long‐Term Stock Market Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1090-1114, November.
    26. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    27. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    28. Andersen, Torben G & Bollerslev, Tim, 1997. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
    29. David Ardia & Keven Bluteau & Kris Boudt & Koen Inghelbrecht, 2023. "Climate Change Concerns and the Performance of Green vs. Brown Stocks," Management Science, INFORMS, vol. 69(12), pages 7607-7632, December.
    30. Feng Ma & Yangli Guo & Julien Chevallier & Dengshi Huang, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," Post-Print halshs-04250304, HAL.
    31. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    32. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    33. Hong, Xin & Zhuang, Zhuang & Kang, Di & Wang, Zhibin, 2019. "Do corporate site visits impact hedge fund performance?," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 113-128.
    34. Edmans, Alex & Fernandez-Perez, Adrian & Garel, Alexandre & Indriawan, Ivan, 2022. "Music sentiment and stock returns around the world," Journal of Financial Economics, Elsevier, vol. 145(2), pages 234-254.
    35. 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.
    36. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    37. Chan, Choon Chat & Fong, Wai Mun, 2006. "Realized volatility and transactions," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2063-2085, July.
    38. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    39. Hites Ahir & Nicholas Bloom & Davide Furceri, 2022. "The world uncertainty index," POID Working Papers 031, Centre for Economic Performance, LSE.
    40. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    41. Paye, Bradley S., 2012. "‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables," Journal of Financial Economics, Elsevier, vol. 106(3), pages 527-546.
    42. repec:hal:journl:peer-00741630 is not listed on IDEAS
    43. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    44. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A comprehensive look at financial volatility prediction by economic variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
    45. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    46. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Wang, Jianqiong, 2020. "Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models," Energy, Elsevier, vol. 212(C).
    47. 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.
    48. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    49. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
    50. Chao Liang & Feng Ma & Lu Wang & Qing Zeng, 2021. "The information content of uncertainty indices for natural gas futures volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1310-1324, November.
    51. Mele, Antonio, 2007. "Asymmetric stock market volatility and the cyclical behavior of expected returns," Journal of Financial Economics, Elsevier, vol. 86(2), pages 446-478, November.
    52. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    53. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2022. "Investor Attention and Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 57(2), pages 455-484, March.
    54. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    55. Cederburg, Scott & O’Doherty, Michael S. & Wang, Feifei & Yan, Xuemin (Sterling), 2020. "On the performance of volatility-managed portfolios," Journal of Financial Economics, Elsevier, vol. 138(1), pages 95-117.
    56. 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.
    57. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    58. Qiang Ji & Dayong Zhang & Yuqian Zhao, 2022. "Intra-day co-movements of crude oil futures: China and the international benchmarks," Annals of Operations Research, Springer, vol. 313(1), pages 77-103, June.
    59. Degiannakis, Stavros & Filis, George, 2022. "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, vol. 123(C).
    60. Obaid, Khaled & Pukthuanthong, Kuntara, 2022. "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, vol. 144(1), pages 273-297.
    61. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," The Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
    62. Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
    63. Pesaran, M. Hashem & Timmermann, Allan, 2009. "Testing Dependence Among Serially Correlated Multicategory Variables," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 325-337.
    64. Bee, Marco & Dupuis, Debbie J. & Trapin, Luca, 2016. "Realizing the extremes: Estimation of tail-risk measures from a high-frequency perspective," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 86-99.
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