Predicting stock market returns using aggregate credit risk

Tangrong Li and Xuchu Sun

International Review of Economics & Finance, 2023, vol. 88, issue C, 1087-1103

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.

Keywords: Return predictability; Credit risk; Discount rate; Asset allocation (search for similar items in EconPapers)
JEL-codes: G11 G14 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:88:y:2023:i:c:p:1087-1103

DOI: 10.1016/j.iref.2023.07.039

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