IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v88y2026ics1544612325025577.html

Is systematic tail risk priced in China?

Author

Listed:
  • Zhao, Shuran
  • Gao, Ruiqing

Abstract

This paper studies the impact of systematic tail risk on cross-sectional expected stock returns in the Chinese stock market. We propose a new measure of systematic tail risk, which identifies the common components of individual stock tail risk through a Quantile Factor Model (QFM). Furthermore, we measure the monthly systematic tail risk beta, which is defined as the sensitivity of stock returns to systematic tail risk, and find that stocks with high past systematic tail risk betas achieve higher excess returns than those with low betas. A value-weighted hedging strategy based on systematic tail risk beta yields approximately 1.16 % monthly returns. This premium cannot be explained by traditional factor models or other firm-level characteristics influencing tail behavior. The positive relationship between systematic tail risk beta and stock returns is stronger during high market volatility, market downturns, and low investor confidence indices.

Suggested Citation

  • Zhao, Shuran & Gao, Ruiqing, 2026. "Is systematic tail risk priced in China?," Finance Research Letters, Elsevier, vol. 88(C).
  • Handle: RePEc:eee:finlet:v:88:y:2026:i:c:s1544612325025577
    DOI: 10.1016/j.frl.2025.109308
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612325025577
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2025.109308?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Estrada, Javier, 2002. "Systematic risk in emerging markets: the," Emerging Markets Review, Elsevier, vol. 3(4), pages 365-379, December.
    2. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    3. Adrian, Tobias & Shin, Hyun Song, 2010. "Liquidity and leverage," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 418-437, July.
    4. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    5. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    6. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    7. 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.
    8. Liang Chen & Juan J. Dolado & Jesús Gonzalo, 2021. "Quantile Factor Models," Econometrica, Econometric Society, vol. 89(2), pages 875-910, March.
    9. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    10. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    11. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    12. van Oordt, Maarten R. C. & Zhou, Chen, 2016. "Systematic Tail Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(2), pages 685-705, April.
    13. De Jonghe, Olivier, 2010. "Back to the basics in banking? A micro-analysis of banking system stability," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 387-417, July.
    14. Markus K. Brunnermeier & Lasse Heje Pedersen, 2009. "Market Liquidity and Funding Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2201-2238, June.
    15. Caio Almeida & Kym Ardison & René Garcia & Jose Vicente, 2017. "Rejoinder on: Nonparametric Tail Risk, Stock Returns, and the Macroeconomy," Journal of Financial Econometrics, Oxford University Press, vol. 15(3), pages 418-426.
    16. Chabi-Yo, Fousseni & Huggenberger, Markus & Weigert, Florian, 2022. "Multivariate crash risk," Journal of Financial Economics, Elsevier, vol. 145(1), pages 129-153.
    17. Bawa, Vijay S. & Lindenberg, Eric B., 1977. "Capital market equilibrium in a mean-lower partial moment framework," Journal of Financial Economics, Elsevier, vol. 5(2), pages 189-200, November.
    18. Whitney Newey & Kenneth West, 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.
    19. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    20. Hogan, William W. & Warren, James M., 1974. "Toward the Development of an Equilibrium Capital-Market Model Based on Semivariance," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 9(1), pages 1-11, January.
    21. 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.
    22. Turan G. Bali & Nusret Cakici & Robert F. Whitelaw, 2014. "Hybrid Tail Risk and Expected Stock Returns: When Does the Tail Wag the Dog?," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 4(2), pages 206-246.
    23. Florian Weigert, 2016. "Crash Aversion and the Cross-Section of Expected Stock Returns Worldwide," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 6(1), pages 135-178.
    24. Chabi-Yo, Fousseni & Ruenzi, Stefan & Weigert, Florian, 2018. "Crash Sensitivity and the Cross Section of Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1059-1100, June.
    25. Yaron Levi & Ivo Welch & Andrew Karolyi, 2020. "Symmetric and Asymmetric Market Betas and Downside Risk," The Review of Financial Studies, Society for Financial Studies, vol. 33(6), pages 2772-2795.
    26. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    27. Huaigang Long & Adam Zaremba & Yuexiang Jiang, 2019. "Beware of the crash risk: Tail beta and the cross-section of stock returns in China," Applied Economics, Taylor & Francis Journals, vol. 51(44), pages 4870-4881, September.
    28. Lettau, Martin & Maggiori, Matteo & Weber, Michael, 2014. "Conditional risk premia in currency markets and other asset classes," Journal of Financial Economics, Elsevier, vol. 114(2), pages 197-225.
    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. Keith K.F. Law & W.K. Li & Philip L.H. Yu, 2021. "An alternative nonparametric tail risk measure," Quantitative Finance, Taylor & Francis Journals, vol. 21(4), pages 685-696, April.
    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. Ruenzi, Stefan & Ungeheuer, Michael & Weigert, Florian, 2020. "Joint Extreme events in equity returns and liquidity and their cross-sectional pricing implications," Journal of Banking & Finance, Elsevier, vol. 115(C).
    2. Qiao, Tongshuai & Zhao, Yang & Han, Liyan & Li, Donghui, 2025. "Multivariate crash risk in China," Journal of Banking & Finance, Elsevier, vol. 171(C).
    3. Atilgan, Yigit & Bali, Turan G. & Demirtas, K. Ozgur & Gunaydin, A. Doruk, 2020. "Left-tail momentum: Underreaction to bad news, costly arbitrage and equity returns," Journal of Financial Economics, Elsevier, vol. 135(3), pages 725-753.
    4. Chabi-Yo, Fousseni & Huggenberger, Markus & Weigert, Florian, 2022. "Multivariate crash risk," Journal of Financial Economics, Elsevier, vol. 145(1), pages 129-153.
    5. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "Realized semibetas: Disentangling “good” and “bad” downside risks," Journal of Financial Economics, Elsevier, vol. 144(1), pages 227-246.
    6. 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.
    7. Liu, Jinjing, 2023. "A novel downside beta and expected stock returns," International Review of Financial Analysis, Elsevier, vol. 85(C).
    8. Cakici, Nusret & Zaremba, Adam, 2023. "Recency bias and the cross-section of international stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    9. Khasawneh, Maher & McMillan, David G. & Kambouroudis, Dimos, 2024. "Left-tail risk and UK stock return predictability: Underreaction, overreaction, and arbitrage difficulties," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    10. Qin, Yiyi & Cai, Jun & Wang, James J.D. & Webb, Robert I., 2023. "Gold-mining stocks, risk factors, and tail patterns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    11. Lu, Zhongjin & Murray, Scott, 2019. "Bear beta," Journal of Financial Economics, Elsevier, vol. 131(3), pages 736-760.
    12. Harris, Richard D.F. & Nguyen, Linh H. & Stoja, Evarist, 2019. "Systematic extreme downside risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 128-142.
    13. Wang, Chen & Xiong, Xiong & Shen, Dehua, 2022. "Tail risks, firm characteristics, and stock returns," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    14. Cao, Ji & Rieger, Marc Oliver & Zhao, Lei, 2023. "Safety first, loss probability, and the cross section of expected stock returns," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 345-369.
    15. Qiao, Tongshuai & Ding, Wenjie & Han, Liyan & Li, Donghui, 2024. "RMB exchange rate volatility and the cross-section of Chinese A-share returns," Journal of International Money and Finance, Elsevier, vol. 142(C).
    16. Sean A. Anthonisz & Tālis J. Putniņš, 2017. "Asset Pricing with Downside Liquidity Risks," Management Science, INFORMS, vol. 63(8), pages 2549-2572, August.
    17. González-Sánchez, Mariano, 2022. "Factorial asset pricing models using statistical anomalies," Research in International Business and Finance, Elsevier, vol. 60(C).
    18. George P. Gao & Xiaomeng Lu & Zhaogang Song, 2019. "Tail Risk Concerns Everywhere," Management Science, INFORMS, vol. 65(7), pages 3111-3130, July.
    19. Ji Cao & Marc Oliver Rieger & Lei Zhao, 2019. "Safety First, Loss Probability, and the Cross Section of Expected Stock Returns," Working Paper Series 2019-02, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    20. Bi, Jia & Zhu, Yifeng, 2020. "Value at risk, cross-sectional returns and the role of investor sentiment," Journal of Empirical Finance, Elsevier, vol. 56(C), pages 1-18.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:finlet:v:88:y:2026:i:c:s1544612325025577. 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/frl .

    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.