We investigate how online investor sentiment impacts stock risk, measured as Value-at-Risk (VaR). We extrapolate online investor sentiment from information on the stock forum on the 100 constituent stocks of the Shenzhen index using a self-written code to collect daily online postings from 2016 to 2022. Then, we rely on algorithms to classify them. Using quantile regressions and controlling for firm-specific factors and COVID-19, we document that stronger sentiment increases VaR while decreasing VaR on a lagged 7-day horizon. As we move to a longer horizon (20 days), the effect vanishes as more information becomes incorporated into the stock prices.

Bouteska, A., Cardillo, G., Harasheh, M. (2023). Is it all about noise? Investor sentiment and risk nexus: evidence from China. FINANCE RESEARCH LETTERS, 57, 1-6 [10.1016/j.frl.2023.104197].

Is it all about noise? Investor sentiment and risk nexus: evidence from China

Cardillo, Giovanni
;
Harasheh, Murad
2023

Abstract

We investigate how online investor sentiment impacts stock risk, measured as Value-at-Risk (VaR). We extrapolate online investor sentiment from information on the stock forum on the 100 constituent stocks of the Shenzhen index using a self-written code to collect daily online postings from 2016 to 2022. Then, we rely on algorithms to classify them. Using quantile regressions and controlling for firm-specific factors and COVID-19, we document that stronger sentiment increases VaR while decreasing VaR on a lagged 7-day horizon. As we move to a longer horizon (20 days), the effect vanishes as more information becomes incorporated into the stock prices.
2023
Bouteska, A., Cardillo, G., Harasheh, M. (2023). Is it all about noise? Investor sentiment and risk nexus: evidence from China. FINANCE RESEARCH LETTERS, 57, 1-6 [10.1016/j.frl.2023.104197].
Bouteska, Ahmed; Cardillo, Giovanni; Harasheh, Murad
File in questo prodotto:
File Dimensione Formato  
2_Manuscript_gio_Mur_v3 (002).pdf

embargo fino al 09/07/2025

Tipo: Postprint
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale - Non opere derivate (CCBYNCND)
Dimensione 205.5 kB
Formato Adobe PDF
205.5 kB Adobe PDF   Visualizza/Apri   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/935313
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 7
social impact