Investor sentiment and stock volatility : New evidence

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Article number102028
Journal / PublicationInternational Review of Financial Analysis
Volume80
Online published24 Jan 2022
Publication statusPublished - Mar 2022

Abstract

This study investigates the predictability of sentiment measure on stock realized volatility. We propose a new investor sentiment index (NISI) based on the partial least squares method. This sentiment index outperforms many existing sentiment indicators in three aspects. First, in-sample result shows that the NISI has greater predictive power relative to the others. Most sentiment indicators show predictability in the non-crisis period only while the NISI is also effective in the crisis period. Furthermore, the NISI exhibits more prominent superiority in longer horizons forecasting. Second, further analysis indicates that the NISI has robust predictability before and after the Chinese stock market turbulence periods while the others not. Importantly, the NISI is still effective significantly after considering leverage effect while most of the others not. Finally, out-of-sample analysis demonstrates that the NISI is more powerful than other sentiment measures. This result is reproducible in different robustness checks.

Research Area(s)

  • Investor sentiment, Leverage effect, Partial least squares, Realized volatility prediction

Citation Format(s)

Investor sentiment and stock volatility: New evidence. / Gong, Xue; Zhang, Weiguo; Wang, Junbo et al.
In: International Review of Financial Analysis, Vol. 80, 102028, 03.2022.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review