Predicting Chinese bond risk premium with machine learning

Jia Zhai, Jiahui Xi, Conghua Wen and Lu Zong

The European Journal of Finance, 2025, vol. 31, issue 7, 919-955

Abstract: This paper investigates whether bond yield curve and macroeconomic factors have nonlinear relationships with bond risk premia in the Chinese bond market. We apply machine learning approaches to forecast Chinese treasury bond one-year holding period excess returns. Our results show that the bond yield curve has significant nonlinear predictive relationships with bond risk premia. We find evidence that ‘monetary policy’ and ‘tax’ macroeconomic groups have stronger nonlinear relationships with risk premia while ‘invest’ macroeconomic factors matter more for bonds with longer maturities. This paper provides statistical evidence for a significant relationship between expected bond risk premia and several economic drivers including range of forecast of GDP and bond volatility variables. We further document the economic values of our forecasting results by showing they can generate statistically higher certain equivalent values than those from the benchmark forecast.

Date: 2025
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DOI: 10.1080/1351847X.2024.2446719

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