IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v88y2023icp1087-1103.html
   My bibliography  Save this article

Predicting stock market returns using aggregate credit risk

Author

Listed:
  • Li, Tangrong
  • Sun, Xuchu

Abstract

We investigate how credit risk predicts stock returns in the time-series at the aggregate level in the Chinese market. We find that the aggregate credit risk, measured by the option-based structural model, is a strong positive predictor of future stock market excess returns at various horizons. The predictive power remains significant even after controlling for a number of widely-researched predictors or under out-of-sample tests. The positive relationship between aggregate credit risk and expected stock market returns accords with the risk-return tradeoff theory. We also find that the predictive power comes from the discount rate channel. A higher level of aggregate credit risk is related to a higher discount rate of future cash flows, and thus generates higher expected returns.

Suggested Citation

  • Li, Tangrong & Sun, Xuchu, 2023. "Predicting stock market returns using aggregate credit risk," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 1087-1103.
    • Handle: RePEc:eee:reveco:v:88:y:2023:i:c:p:1087-1103
    DOI: 10.1016/j.iref.2023.07.039
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056023002502
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.iref.2023.07.039?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. 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.
    2. Kothari, S.P. & Lewellen, Jonathan & Warner, Jerold B., 2006. "Stock returns, aggregate earnings surprises, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 79(3), pages 537-568, March.
    3. Bao, Jack & Hou, Kewei & Zhang, Shaojun, 2023. "Systematic default and return predictability in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 149(3), pages 349-377.
    4. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    5. Bauer, Julian & Agarwal, Vineet, 2014. "Are hazard models superior to traditional bankruptcy prediction approaches? A comprehensive test," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 432-442.
    6. Bernal, Oscar & Gnabo, Jean-Yves & Guilmin, Grégory, 2014. "Assessing the contribution of banks, insurance and other financial services to systemic risk," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 270-287.
    7. Ferreira, Miguel A. & Santa-Clara, Pedro, 2011. "Forecasting stock market returns: The sum of the parts is more than the whole," Journal of Financial Economics, Elsevier, vol. 100(3), pages 514-537, June.
    8. 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.
    9. Giesecke, Kay & Weber, Stefan, 2004. "Cyclical correlations, credit contagion, and portfolio losses," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 3009-3036, December.
    10. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-386.
    11. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
    12. 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.
    13. 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.
    14. Sudheer Chava & Amiyatosh Purnanandam, 2010. "Is Default Risk Negatively Related to Stock Returns?," The Review of Financial Studies, Society for Financial Studies, vol. 23(6), pages 2523-2559, June.
    15. Hirshleifer, David & Hou, Kewei & Teoh, Siew Hong, 2009. "Accruals, cash flows, and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 91(3), pages 389-406, March.
    16. Li, Yan & Ng, David T. & Swaminathan, Bhaskaran, 2013. "Predicting market returns using aggregate implied cost of capital," Journal of Financial Economics, Elsevier, vol. 110(2), pages 419-436.
    17. Sudheer Chava & Dmitry Livdan & Amiyatosh Purnanandam, 2009. "Do Shareholder Rights Affect the Cost of Bank Loans?," The Review of Financial Studies, Society for Financial Studies, vol. 22(8), pages 2973-3004, August.
    18. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    19. Kevin Aretz & Chris Florackis & Alexandros Kostakis, 2018. "Do Stock Returns Really Decrease with Default Risk? New International Evidence," Management Science, INFORMS, vol. 64(8), pages 3821-3842, August.
    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. Nazish Shahid, 2025. "Algorithmically Efficient Identification of Volatile KSE-30 Equities and Their Role in Optimized Portfolio Allocation," SN Operations Research Forum, Springer, vol. 6(1), pages 1-16, March.
    2. Jakub Waikat & Amel Jelidi & Sandro Lic & Georgios Sopidis & Olaf Kähler & Anna Maly & Jesús Pestana & Ferdinand Fuhrmann & Fredi Belavić, 2024. "First Measurement Campaign by a Multi-Sensor Robot for the Lifecycle Monitoring of Transformers," Energies, MDPI, vol. 17(5), pages 1-26, February.

    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. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    2. Biao Guo & Hai Lin, 2020. "Volatility and jump risk in option returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1767-1792, November.
    3. Li, Jun & Wang, Huijun & Yu, Jianfeng, 2018. "Aggregate Expected Investment Growth and Stock Market Returns," ADBI Working Papers 808, Asian Development Bank Institute.
    4. Chen, Yong & Da, Zhi & Huang, Dayong, 2022. "Short selling efficiency," Journal of Financial Economics, Elsevier, vol. 145(2), pages 387-408.
    5. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    6. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    7. Faria, Gonçalo & Verona, Fabio, 2018. "The equity risk premium and the low frequency of the term spread," Research Discussion Papers 7/2018, Bank of Finland.
    8. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
    9. Park, Dojoon & Hahn, Jaehoon & Eom, Young Ho, 2024. "Predicting the equity premium with financial ratios: A comprehensive look over a long period in Korea," Pacific-Basin Finance Journal, Elsevier, vol. 84(C).
    10. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    11. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    12. repec:zbw:bofrdp:2018_007 is not listed on IDEAS
    13. Faias, José Afonso, 2023. "Predicting the equity risk premium using the smooth cross-sectional tail risk: The importance of correlation," Journal of Financial Markets, Elsevier, vol. 63(C).
    14. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    15. Lin, Hai & Wang, Junbo & Wu, Chunchi, 2014. "Predictions of corporate bond excess returns," Journal of Financial Markets, Elsevier, vol. 21(C), pages 123-152.
    16. Hai Lin & Xinyuan Tao & Junbo Wang & Chunchi Wu, 2020. "Credit Spreads, Business Conditions, and Expected Corporate Bond Returns," JRFM, MDPI, vol. 13(2), pages 1-34, January.
    17. repec:zbw:bofrdp:2017_001 is not listed on IDEAS
    18. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    19. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    20. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    21. 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.
    22. Ma, Feng & Wang, Ruoxin & Lu, Xinjie & Wahab, M.I.M., 2021. "A comprehensive look at stock return predictability by oil prices using economic constraint approaches," International Review of Financial Analysis, Elsevier, vol. 78(C).

    More about this item

    Keywords

    Return predictability; Credit risk; Discount rate; Asset allocation;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • 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:reveco:v:88:y:2023:i:c:p:1087-1103. 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/inca/620165 .

    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.