 Noise trading, institutional trading, and opinion divergence: Evidence on intraday data in the Chinese stock marketYingyi Hu, Tiao Zhao and Lin Zhang International Review of Economics & Finance, 2020, vol. 68, issue C, 74-89 Abstract: This study proposes a measure of opinion divergence based on the trading process and investigates the effect of noise trading and institutional trading on the influence of opinion divergence on stock returns using intraday data. The results show that, although for 5-min intervals, the divergence of opinion is not negatively related to future stock returns, for 10-min intervals and beyond, divergence of opinion becomes negatively related to future stock returns, as proposed by Miller (1977). By differentiating the measure of divergence of opinion from the measure of noise trading and institutional trading, we provide solid evidence that institutional trading affects the relation between divergence of opinion and future stock returns, on which noise trading does not seem to have any effect. However, the effect of institutional trading is mainly due to the fact that stocks with high institutional trading have low divergence of opinion, rather than being a result of sophistication and good stock-picking skills among institutional traders. Keywords: Asset pricing; Heterogeneous belief; Institutional trading; Noise trading (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:68:y:2020:i:c:p:74-89 DOI: 10.1016/j.iref.2020.03.012 Access Statistics for this article International Review of Economics & Finance is currently edited by H. Beladi and C. Chen More articles in International Review of Economics & Finance from Elsevier |
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