2014
DOI: 10.1016/j.intfin.2013.12.001
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Institutional trading and attention bias

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Cited by 9 publications
(8 citation statements)
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“…It is, therefore, unlikely that Dutch pension funds' trading has contributed to the turmoil in countries, such as Greece, Spain, Italy, Cyprus, and Ireland. The absence of return reversals following pension fund trading is consistent with our hypothesis that pension fund's trading reflects the way information is impounded into security prices (DeLong et al, 1990;Choe et al, 1999;Wermers, 1999;Sias, 2004;Hung, 2014). However, there are some indications of destabilization for quintiles 2, 5, 2 and 1.…”
Section: Stabilizing or Destabilizingsupporting
confidence: 85%
See 1 more Smart Citation
“…It is, therefore, unlikely that Dutch pension funds' trading has contributed to the turmoil in countries, such as Greece, Spain, Italy, Cyprus, and Ireland. The absence of return reversals following pension fund trading is consistent with our hypothesis that pension fund's trading reflects the way information is impounded into security prices (DeLong et al, 1990;Choe et al, 1999;Wermers, 1999;Sias, 2004;Hung, 2014). However, there are some indications of destabilization for quintiles 2, 5, 2 and 1.…”
Section: Stabilizing or Destabilizingsupporting
confidence: 85%
“…In this paragraph, we investigate whether herd behavior may have a stabilizing or destabilizing effect on financial markets conducting a return reversal analysis. The absence of price reversals following pension fund trading is consistent with the incorporation of information into security prices (DeLong et al, 1990;Choe et al, 1999;Wermers, 1999;Sias, 2004;Hung, 2014). Thus, when we find that returns continue in the same direction, this means that prices correctly reflect the fundamental value.…”
Section: Stabilizing or Destabilizingsupporting
confidence: 83%
“…Institutional investors are classified into three main groups: DIs (including insurance companies, mutual funds, commercial banks, and other investment companies), qualified FI investors (including offshore and onshore FI investors), and SDs. We examine each kind of institutional trading around price manipulation events by replicating all methodologies applied by Hung (2014) and Thu Luu and Duong Dang (2023). Specifically, we examine NTV : NTVi, k, titalicBuy0.25emitalicVolumei, k, tβˆ’italicSell0.25emitalicVolumei, k, tOutstandingsharesi, titalic, ${{NTV}}_{i,\unicode{x02007}k,\unicode{x02007}t}\frac{{{Buy}{Volume}}_{i,\unicode{x02007}k,\unicode{x02007}t}-{{Sell}{Volume}}_{i,\unicode{x02007}k,\unicode{x02007}t}}{{{Outstanding}{shares}}_{i,\unicode{x02007}t}}{,}$where, Buy volume i, k, t (Sell volume i, k, t ) is the cumulative amount for institution k of stock i on Day t .…”
Section: Data and Methodologiesmentioning
confidence: 99%
“…Herd behaviour can arise from the simultaneous release of new information that pension funds may interpret in the same way, so that they undertake the same buy and sell actions. If herding does indeed arise because of the release of new information, then, on average, no return reversals will take place in the following quarters (Hung et al, 2014). However, if pension funds follow each other without any underlying justification, this behaviour can lead to price imbalances and abnormal volatility (Note 15).…”
Section: Stabilising or Destabilising Behaviourmentioning
confidence: 99%