Investors’ trading on past returns and their trading impact on stock returns

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Abstract This paper extends the return-volume literature by examining the dynamic, bidirectional implications of seven largely unexplored trading theories: analyst optimism, social interaction, style trading, investor disagreement, and investor attention (both firm-specific and market-specific for the latter two). Following Chordia et al. (2011), we use firm-level data to capture heterogeneity that market-index data may obscure. Our main findings are as follows. First, return-volume relations exhibit substantial heterogeneity in both directions. Second, investors trade more actively following high returns at the stock, style, and market levels and respond more aggressively to positive returns than to negative ones. Third, investor sentiment amplifies these patterns: trading on past high returns is more frequent during high-sentiment periods. Finally, we introduce a novel decomposition of trading volume into three past return-driven components, which exert upward price pressure on the traded stocks. Stocks subject to greater price pressure tend to be overpriced. These results provide empirical support for the theories of analyst optimism, style trading, firm-specific disagreement, and firm-specific attention. JEL classification: C32, G12
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Investors’ trading on past returns and their trading impact on stock returns | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Investors’ trading on past returns and their trading impact on stock returns Wen-I Chuang, Yun-Huan Lee, Rauli Susmel, Tsung-Li Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8614861/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper extends the return-volume literature by examining the dynamic, bidirectional implications of seven largely unexplored trading theories: analyst optimism, social interaction, style trading, investor disagreement, and investor attention (both firm-specific and market-specific for the latter two). Following Chordia et al. (2011), we use firm-level data to capture heterogeneity that market-index data may obscure. Our main findings are as follows. First, return-volume relations exhibit substantial heterogeneity in both directions. Second, investors trade more actively following high returns at the stock, style, and market levels and respond more aggressively to positive returns than to negative ones. Third, investor sentiment amplifies these patterns: trading on past high returns is more frequent during high-sentiment periods. Finally, we introduce a novel decomposition of trading volume into three past return-driven components, which exert upward price pressure on the traded stocks. Stocks subject to greater price pressure tend to be overpriced. These results provide empirical support for the theories of analyst optimism, style trading, firm-specific disagreement, and firm-specific attention. JEL classification: C32, G12 Trading behavior Causal return-volume relations Investor sentiment Overpricing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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