Investor Overconfidence and Trading Volume
The proposition that investors are overconfident about their valuation and trading skills can explain high observed trading volume. With biased self-attribution, the level of investor overconfidence and thus trading volume varies with past returns. We test the trading volume predictions of formal ov...
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Veröffentlicht in: | The Review of financial studies 2006-12, Vol.19 (4), p.1531-1565 |
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creator | Statman, Meir Thorley, Steven Vorkink, Keith |
description | The proposition that investors are overconfident about their valuation and trading skills can explain high observed trading volume. With biased self-attribution, the level of investor overconfidence and thus trading volume varies with past returns. We test the trading volume predictions of formal overconfidence models and find that share turnover is positively related to lagged returns for many months. The relationship holds for both market-wide and individual security turnover, which we interpret as evidence of investor overconfidence and the disposition effect, respectively. Security volume is more responsive to market return shocks than to security return shocks, and both relationships are more pronounced in small-cap stocks and in earlier periods where individual investors hold a greater proportion of shares. |
doi_str_mv | 10.1093/rfs/hhj032 |
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With biased self-attribution, the level of investor overconfidence and thus trading volume varies with past returns. We test the trading volume predictions of formal overconfidence models and find that share turnover is positively related to lagged returns for many months. The relationship holds for both market-wide and individual security turnover, which we interpret as evidence of investor overconfidence and the disposition effect, respectively. Security volume is more responsive to market return shocks than to security return shocks, and both relationships are more pronounced in small-cap stocks and in earlier periods where individual investors hold a greater proportion of shares.</description><identifier>ISSN: 0893-9454</identifier><identifier>EISSN: 1465-7368</identifier><identifier>DOI: 10.1093/rfs/hhj032</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>Coefficients ; Confidence ; Data analysis ; Econometrics ; Economic psychology ; Financial research ; Financial securities ; Hypotheses ; Institutional investments ; Investment analysis ; Investment policy ; Investors ; Loss ; Mathematical models ; Overconfidence ; P values ; Regression analysis ; Scholarships & fellowships ; Securities markets ; Securities returns ; Securities trading volume ; Self-perception ; Small cap investments ; Standard deviation ; Standard error ; Stock exchange ; Stock prices ; Stocks ; Studies ; Time series ; U.S.A ; Variable coefficients ; Vector autoregression ; Volatility</subject><ispartof>The Review of financial studies, 2006-12, Vol.19 (4), p.1531-1565</ispartof><rights>Copyright 2006 The Society for Financial Studies</rights><rights>Copyright Oxford University Press(England) Winter 2006</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c372t-ccfd525c3cacf6b548ce21cc7f0415da109bf454be6d1fec3f70a350929677ae3</citedby><cites>FETCH-LOGICAL-c372t-ccfd525c3cacf6b548ce21cc7f0415da109bf454be6d1fec3f70a350929677ae3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/4123481$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/4123481$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,27901,27902,57992,58225</link.rule.ids></links><search><creatorcontrib>Statman, Meir</creatorcontrib><creatorcontrib>Thorley, Steven</creatorcontrib><creatorcontrib>Vorkink, Keith</creatorcontrib><title>Investor Overconfidence and Trading Volume</title><title>The Review of financial studies</title><description>The proposition that investors are overconfident about their valuation and trading skills can explain high observed trading volume. With biased self-attribution, the level of investor overconfidence and thus trading volume varies with past returns. We test the trading volume predictions of formal overconfidence models and find that share turnover is positively related to lagged returns for many months. The relationship holds for both market-wide and individual security turnover, which we interpret as evidence of investor overconfidence and the disposition effect, respectively. 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With biased self-attribution, the level of investor overconfidence and thus trading volume varies with past returns. We test the trading volume predictions of formal overconfidence models and find that share turnover is positively related to lagged returns for many months. The relationship holds for both market-wide and individual security turnover, which we interpret as evidence of investor overconfidence and the disposition effect, respectively. Security volume is more responsive to market return shocks than to security return shocks, and both relationships are more pronounced in small-cap stocks and in earlier periods where individual investors hold a greater proportion of shares.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><doi>10.1093/rfs/hhj032</doi><tpages>35</tpages></addata></record> |
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source | Jstor Complete Legacy; Oxford University Press Journals All Titles (1996-Current); Business Source Complete |
subjects | Coefficients Confidence Data analysis Econometrics Economic psychology Financial research Financial securities Hypotheses Institutional investments Investment analysis Investment policy Investors Loss Mathematical models Overconfidence P values Regression analysis Scholarships & fellowships Securities markets Securities returns Securities trading volume Self-perception Small cap investments Standard deviation Standard error Stock exchange Stock prices Stocks Studies Time series U.S.A Variable coefficients Vector autoregression Volatility |
title | Investor Overconfidence and Trading Volume |
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