2021
DOI: 10.1111/fire.12282
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The more we know, the less we agree: A test of the trading horizon heterogeneity theory

Abstract: We examine the Kondor theoretical explanation of an enduring puzzle: trading volumes and stock return volatility peak after the release of public information. Using a comprehensive data set of institutional holdings and earnings announcements, we find supporting evidence that the proportion of short-term investors is positively associated with post-announcement spikes in trading volume and return volatility. This finding survives in the identification test based on the annual reconstitutions of the Russell 100… Show more

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Cited by 6 publications
(3 citation statements)
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“…Although the relationship between institutional investor horizons and corporate decision‐making has been investigated in the US and European markets (Dai et al, 2022; Döring et al, 2021; Harford et al, 2018), the influence of institutional investor horizons in Asia‐Pacific markets has not been fully explored. This article seeks to fill this gap by investigating how institutional investor horizons impact investment efficiency in China.…”
Section: Introductionmentioning
confidence: 99%
“…Although the relationship between institutional investor horizons and corporate decision‐making has been investigated in the US and European markets (Dai et al, 2022; Döring et al, 2021; Harford et al, 2018), the influence of institutional investor horizons in Asia‐Pacific markets has not been fully explored. This article seeks to fill this gap by investigating how institutional investor horizons impact investment efficiency in China.…”
Section: Introductionmentioning
confidence: 99%
“…11 Related, Dai et al (2022) show that trading volume increases after the release of public information.…”
Section: Introductionmentioning
confidence: 99%
“…A growing number of publications that investigate the influence of policy changes use RD with time as the running variable (e.g.,Burger et al, 2014;Davis & Kahn, 2010). For an application to finance published in this journal, seeDai et al (2022).5 Randomizing participants to treatments makes a causal interpretation straightforward. This is an advantage of experiments on IPO pricing (e.g.,Weber et al, 2018;Füllbrunn et al, 2020).…”
mentioning
confidence: 99%