Can systematic skewness factors predict future interest rates: Evidence from China

Xinyao Liang and Yichen Sun

PLOS ONE, 2026, vol. 21, issue 2, 1-19

Abstract: This study uses the numerical changes of the systematic skewness factors to reflect investors’ preferences for the systematic skewness of stocks. As systematic skewness describes the correlation between individual stock returns and market volatility, stocks with positive systematic skewness can obtain positive returns during periods of market volatility. Thus, investors’ preferences for the systematic skewness of stocks can reflect their hedging demands. By examining the predictive power of systematic skewness factors on future interest rates, we found that systematic skewness factors have a significant predictive power on future interest rates. This indicates that investors’ hedging demands influence adjustments to interest rates by China’s monetary authorities. Moreover, for both short‑term and long‑term interest rates, prediction errors based on systematic skewness factors are consistently lower than those from an AR model and the extended Taylor‑rule model proposed by Ma et al. (2025). Systematic skewness can serve as an asymmetric pricing signal in the market for extreme interest rate risks. Its increase often indicates a rise in investors’ anxiety over liquidity tightening, thereby providing central banks with a forward-looking sentiment monitoring window independent of traditional economic indicators.

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0334345 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 34345&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0334345

DOI: 10.1371/journal.pone.0334345

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().