Sentiment Shocks, Asymmetric Volatility, and Market Segmentation: Evidence from AH Dual-Listed Pairs

Abstract

This paper examines whether investor sentiment shocks affect conditional volatility asymmetrically in China’s equity markets, using a sample of 32 AH dual-listed firm-market pairs over 2018–2024. We augment the standard GJR-GARCH(1,1) model with positive and negative sentiment indices derived from the Loughran-McDonald financial dictionary — Chinese-language news for A-shares (SCN) and English-language news for H-shares (SHK) — as exogenous variance regressors. Estimating the GJR-GARCH-X model via maximum likelihood with Student-t innovations for 15 A-share and 17 H-share series, we find strong evidence of sentiment-driven volatility. For A-shares, the negative sentiment coefficient (δ−) is statistically significant in 13 of 15 cases (87%), with a mean magnitude of 0.260, compared with only 7 of 17 H-share series (41%). The sentiment-augmented model yields ΔAIC < 0 (improved fit over the baseline |δ+| for the majority of pairs, confirming sentiment asymmetry — negative news amplifies volatility more than positive news dampens it. Sector analysis reveals that energy and banking A-shares exhibit the strongest sentiment sensitivity, while construction and telecom firms show negligible effects. H-shares display significantly weaker sentiment incorporation, consistent with the hypothesis that Hong Kong’s more informationally efficient market prices sentiment shocks faster. Mean GARCH persistence is high in both markets (A: 0.979, H: 0.980), indicating long-lived volatility clustering. Our findings have implications for volatility forecasting, risk management, and the ongoing debate on A-share market efficiency.

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