Does Investment Horizon Matter? Disentangling the Effect of Institutional Herding on Stock Prices

Abstract

This study finds that, over short horizons, herding by short‐term institutions promotes price discovery. In contrast, herding by long‐term institutions drives stock prices away from fundamentals over the same periods. Furthermore, while the positive predictability of short‐term institutional herding for stock prices is more pronounced for small stocks and stocks with high growth opportunities, the negative association between long‐term institutional herding and stock prices is stronger for stocks whose valuations are highly uncertain and subjective. Finally, we show that the destabilizing effect of institutional herding persistence documented in the recent literature is entirely driven by persistent herding by long‐term institutions.

Passive Institutional Ownership, R2 Trends, and Price Informativeness

“…Crawford, Roulstone andSo (2012, p. 1536) explain that market capitalization proxies for "various dimensions of the firm's information environment, including media exposure and the overall level of investor interest." This classification has proven to be robust in the literature and is used in scores of studies across a broad range of disciplines including accounting (e.g., Collins, Collins, Gong and Hribar, 2003;Ke and Petroni, 2004;Ke and Ramalingegowda, 2005;Ramalingegowda and Yu, 2012;Bentley, Omer and Sharp, 2013), finance (e.g., Gong, Louis and Sun, 2008;Cai, Garner and Walking, 2009;Field and Lowry, 2009;Joe, Louis and Robinson, 2009;Yan and Zhang, 2009;Burns, Kedia and Lipson, 2010;Cremers and Pareek, 2015;Yüksel, 2015), management (e.g., Connelly, Tihanyi, Certo and Hitt, 2010;Eccles, Ioannou and Serafeim, 2014), and marketing (e.g., Luo, Zhang, Zhang and Aspara, 2014). A k-means cluster analysis is then executed on the factor scores to group institutions into their appropriate category.…”

“…While this method requires some initial cluster seeds, the large number of observations makes the cluster formation insensitive to both the initial seeds and to the order in which the observations are clustered (Hair, Black, Babin, Anderson and Tatham, 2006). This classification has proven to be robust in the literature and is used in scores of studies across a broad range of disciplines including accounting (e.g., Collins, Collins, Gong and Hribar, 2003;Ke and Petroni, 2004;Ke and Ramalingegowda, 2005;Ramalingegowda and Yu, 2012;Bentley, Omer and Sharp, 2013), finance (e.g., Gong, Louis and Sun, 2008;Cai, Garner and Walking, 2009;Field and Lowry, 2009;Joe, Louis and Robinson, 2009;Yan and Zhang, 2009;Burns, Kedia and Lipson, 2010;Cremers and Pareek, 2015;Yüksel, 2015), management (e.g., Connelly, Tihanyi, Certo and Hitt, 2010;Eccles, Ioannou and Serafeim, 2014), and marketing (e.g., Luo, Zhang, Zhang and Aspara, 2014). firm's equity is also related to market frictions and correlated trading, as stocks from large firms tend to be more liquid and belong to multiple indexes that are owned by ETFs. The average (median) firm in the full sample has capitalization of $3,068 ($293.29) million, while the average firm in the survivor sample is about twice that size, with average (median) capitalization of $6,279 ($865.2) million.…”

Disagreement between hedge funds and other institutional investors and the cross‐section of expected stock returns

“…For this reason, one strand of the literature has focused specifically on the informational content of hedge funds' trading. While there are a few earlier studies that provide weak support for the informativeness of hedge funds' trades (e.g., Amin & Kat, 2003;Asness et al, 2001;Griffin & Xu, 2009), a growing number of recent studies present stronger evidence of informed trading by hedge funds (e.g., Agarwal et al, 2013;Chen et al, 2022;Grinblatt et al, 2020;Jiao, 2013;Jiao et al, 2016;Sias et al, 2016;Yuksel, 2015). 1 Motivated by the significant differences in the performance of hedge funds and other institutions (hereafter referred to as non-hedge funds), this paper examines to what extent disagreements between hedge funds and nonhedge funds play a role in their stock trade performances.…”

“…For this reason, one strand of the literature has focused specifically on the informational content of hedge funds’ trading. While there are a few earlier studies that provide weak support for the informativeness of hedge funds’ trades (e.g., Amin & Kat, 2003; Asness et al., 2001; Griffin & Xu, 2009), a growing number of recent studies present stronger evidence of informed trading by hedge funds (e.g., Agarwal et al., 2013; Chen et al., 2022; Grinblatt et al., 2020; Jiao, 2013; Jiao et al., 2016; Sias et al., 2016; Yuksel, 2015).…”

Sell‐side analyst recommendation revisions and hedge fund trading before and after regulation fair disclosure

“…This finding is similar to a recent paper byGrinblatt, Jostova, Petrasek, and Philipov (2020), who show that hedge funds trade in a contrarian manner with respect to public signals received from stock returns. Likewise, Jame (2018) finds that liquidity-providing hedge funds (i.e., short-term contrarian strategies) earn significantly higher returns.7 Likewise,Yuksel (2015) shows that over short horizons, herding by short-term institutions promotes price discovery, whereas herding by long-term institutions drives stock prices away from their fundamental values.…”