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Systemic Default and Return Predictability in the Stock and Bond Markets

Author

Listed:
  • Bao, Jack

    (Federal Reserve Board)

  • Hou, Kewei

    (OH State University)

  • Zhang, Shaojun A.

    (University of Hong Kong)

Abstract

Using a structural model of default, we construct a measure of systemic default defined as the probability that many firms default at the same time. Our estimation accounts for correlations in defaults between firms through common exposures to shocks. The systemic default measure spikes during recession periods and is strongly correlated with traditional credit-related macroeconomic measures such as the default spread and VIX. Furthermore, our measure predicts future equity and corporate bond index returns, particularly at the one-year horizon, and even after controlling for many traditional return predictors such as the dividend yield, default spread, inflation, and tail risk. These predictability results are robust to out-of-sample tests.

Suggested Citation

  • Bao, Jack & Hou, Kewei & Zhang, Shaojun A., 2016. "Systemic Default and Return Predictability in the Stock and Bond Markets," Working Paper Series 2016-2, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    • Handle: RePEc:ecl:ohidic:2016-2
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    Cited by:

    1. Wang, Qiyu & Yang, Junhong & Chong, Terence Tai-Leung, 2025. "Creditable bonds’ multifunctional roles during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
    2. Zhang, Jixiang & Zeng, Qing & Bouri, Elie & Gozgor, Giray, 2025. "Newly-constructed Chinese geopolitical risk index and trade stock returns," Research in International Business and Finance, Elsevier, vol. 74(C).
    3. Chen, Shaoying & Tong, Zhiwei & Yang, Yang, 2025. "Portfolio default losses driven by idiosyncratic risks," European Journal of Operational Research, Elsevier, vol. 320(3), pages 765-776.
    4. Li, Xin & Xu, Zihan & Mei, Dexiang & Wang, Yu, 2025. "Optimal share repurchase decision model for retailers under supply chain collaboration," International Review of Financial Analysis, Elsevier, vol. 103(C).
    5. Nina Boyarchenko & Leonardo Elias, 2024. "The Global Credit Cycle," Staff Reports 1094, Federal Reserve Bank of New York.
    6. George P. Gao & Xiaomeng Lu & Zhaogang Song, 2019. "Tail Risk Concerns Everywhere," Management Science, INFORMS, vol. 65(7), pages 3111-3130, July.
    7. 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.
    8. In-Mu Haw & Wenming Wang & Wenlan Zhang & Xu Zhang, 2022. "Capturing the straw in the wind: do short sellers trade on customer information?," Review of Quantitative Finance and Accounting, Springer, vol. 58(4), pages 1363-1394, May.
    9. Yi Lu & Aifan Ling & Chaoqun Wang & Yaxin Xu, 2025. "Why Bonds Fail Differently? Explainable Multimodal Learning for Multi-Class Default Prediction," Papers 2509.10802, arXiv.org.
    10. Artem Stopochkin & Inessa Sytnik & Janusz Wielki & Nataliia Zemlianska, 2021. "Methodology for Building Trader's Investment Strategy Based on Assessment of the Market Value of the Company," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 913-935.
    11. Pang, Xiaochuan & Zhu, Shushang & Cui, Xueting & Ma, Jiali, 2023. "Systemic risk of optioned portfolio: Controllability and optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    12. 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.
    13. Noh, Joonki & Zhou, Dexin, 2022. "Executives’ Blaming external factors and market reactions: Evidence from earnings conference calls," Journal of Banking & Finance, Elsevier, vol. 134(C).
    14. Kabiri, Ali & Malone, Vlad & Roland, Isabelle Angeline Madeleine & Spatareanu, Mariana, 2020. "Bank default risk propagation along supply chains: evidence from the UK," LSE Research Online Documents on Economics 121832, London School of Economics and Political Science, LSE Library.
    15. Bouri, Elie & Demir, Ender, 2025. "Bitcoin-to-gold ratio and stock market returns," Finance Research Letters, Elsevier, vol. 81(C).

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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