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Predicting stock market returns using aggregate credit risk

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  • 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
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    References listed on IDEAS

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    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

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