2020
DOI: 10.1002/ijfe.2291
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Investor types' trading around theshort‐termreversal pattern

Abstract: Using exact and complete Korean data of investor trading, we provide an anatomy of investor types' trading throughout the short-horizon overshootingand-reversal pattern in stock returns. We document two forms of non-optimal trading behaviour associated with the pattern: First, institutional investors' chasing of return shocks at the overshooting point, particularly in the large-cap segment. Second, individual investors' buying of winner stocks in the small-cap segment, consistent with an attention-driven specu… Show more

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Cited by 9 publications
(10 citation statements)
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“…The aggregate Russian individual investor bought the dip during the crash in March–April 2020, in unprecedented amounts. Such buying can be accounted for by individual investors’ regular contrarian trading documented in other markets (e.g., Kaniel et al, 2008 , Barrot et al, 2016 , Onishchenko and Ülkü, 2020 ), which we confirm on Russian data using a vector autoregression (VAR) analysis. However, the aggregate Russian individual investor made a key exception to contrarianism by remaining as net buyers, instead of contrarian profit-taking, until the market fully recovered.…”
Section: Introductionsupporting
confidence: 68%
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“…The aggregate Russian individual investor bought the dip during the crash in March–April 2020, in unprecedented amounts. Such buying can be accounted for by individual investors’ regular contrarian trading documented in other markets (e.g., Kaniel et al, 2008 , Barrot et al, 2016 , Onishchenko and Ülkü, 2020 ), which we confirm on Russian data using a vector autoregression (VAR) analysis. However, the aggregate Russian individual investor made a key exception to contrarianism by remaining as net buyers, instead of contrarian profit-taking, until the market fully recovered.…”
Section: Introductionsupporting
confidence: 68%
“…For example, recent studies on the US individual investors are limited to a short proprietary sample provided by the NYSE ( Kaniel et al, 2008 , Kaniel et al, 2012 ) -raising questions about out-of-sample validity – or attempts to infer retail trading from statistical approximations ( Boehmer et al, 2021 ) – needing checks for validity on actual data. In contrast, several Asian exchanges have made available long time-series of exact and complete daily aggregate trading data by investor types, enabling researchers to generate concrete evidence (e.g., Kamesaka et al, 2003 , Chiang et al, 2012 , Phansatan et al, 2012 , Ülkü and Weber, 2013 , Ikizlerli et al, 2019 , Onishchenko and Ülkü, 2020 ). However, the fact that most of the existing literature is confined to Asian data leaves a gap regarding whether the findings on Asian markets are representative of investors from other national cultures.…”
Section: Introductionmentioning
confidence: 99%
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