Differential Interpretations and Trading Volume

Bamber, Linda Smith; Barron, Orie E.; Stöber, Thomas

doi:10.2139/ssrn.193012

Cited by 69 publications

(78 citation statements)

References 5 publications

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“…'' 47 There are other studies which show empirically that differences in opinion creates trading volume (see also the survey by Hong and Stein [2007]). Bamber et al [1999] and Antweiler and Frank [2004] are two examples. Bamber et al [1999] measure differential interpretations using data on analysts' revisions of forecasts of annual earnings after the announcement of quarterly earnings.…”

Section: Discussionmentioning

confidence: 99%

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Overconfidence and trading volume

Glaser

Weber

2007

Geneva Risk Insur Rev

559

267

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Theoretical models predict that overconfident investors will trade more than rational investors. We directly test this hypothesis by correlating individual overconfidence scores with several measures of trading volume of individual investors. Approximately 3,000 online broker investors were asked to answer an internet questionnaire which was designed to measure various facets of overconfidence (miscalibration, volatility estimates, better than average effect). The measures of trading volume were calculated by the trades of 215 individual investors who answered the questionnaire. We find that investors who think that they are above average in terms of investment skills or past performance (but who did not have above average performance in the past) trade more. Measures of miscalibration are, contrary to theory, unrelated to measures of trading volume. This result is striking as theoretical models that incorporate overconfident investors mainly motivate this assumption by the calibration literature and model overconfidence as underestimation of the variance of signals. In connection with other recent findings, we conclude that the usual way of motivating and modeling overconfidence which is mainly based on the calibration literature has to be treated with caution. Moreover, our way of empirically evaluating behavioral finance models-the correlation of economic and psychological variables and the combination of psychometric measures of judgment biases (such as overconfidence scores) and field data-seems to be a promising way to better understand which psychological phenomena actually drive economic behavior.

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Section: Discussionmentioning

confidence: 99%

“…Bamber et al [1999] and Antweiler and Frank [2004] are two examples. Bamber et al [1999] measure differential interpretations using data on analysts' revisions of forecasts of annual earnings after the announcement of quarterly earnings. They find that differential interpretations explain a significant amount of trading.…”

Section: Discussionmentioning

confidence: 99%

Overconfidence and trading volume

Glaser

Weber

2007

Geneva Risk Insur Rev

559

267

View full text Add to dashboard Cite

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“…Probably the most widely discussed fact in this respect is the systematic and significant increase in the trading volumes following earnings announcements. Previous research identifies three major sources of these abnormally high trading volumes, all stemming from some form of heterogeneity among investors: (i) differences in information (e.g., Varian 1989;Holthausen and Verrecchia 1990;Kim and Verrecchia 1991, 1994Barron et al 2005); (ii) differing risk preferences (e.g., Beaver 1968;Verrecchia 1981), and (iii) differences in opinion, that is, differential interpretation of the earnings news (e.g., Harris and Raviv 1993;Kandel and Pearson 1995;Bamber et al 1997Bamber et al , 1999Garfinkel and Sokobin 2006;Hong and Stein 2007;Bamber et al 2011). Israeli (2015 demonstrates that trading volume reactions to earnings announcements provide information about future returns that cannot be deduced from the price reactions or the magnitudes of earnings surprises.…”

Section: Stock Trading Volumes and Their Connection To Stock Returnsmentioning

confidence: 99%

The Effect of Stock Return Sequences on Trading Volumes

Kudryavtsev

2017

IJFS

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The present study explores the effect of the gambler's fallacy on stock trading volumes. I hypothesize that if a stock's price rises (falls) during a number of consecutive trading days, then the gambler's fallacy may cause at least some of the investors to expect that the stock's price "has" to subsequently fall (rise), and thus, to increase their willingness to sell (buy) the stock, resulting in a stronger degree of disagreement between the investors and a higher-than-usual stock trading volume on the first day when the stock's price indeed falls (rises). Employing a large sample of daily price and trading volume data, I document that following relatively long sequences of the same-sign stock returns, on the days when the sign is reversed, the trading activity in the respective stocks is abnormally high. Moreover, average abnormal trading volumes gradually and significantly increase with the length of the preceding return sequence. The effect is slightly more pronounced following the sequences of negative stock returns, and remains significant after controlling for other potentially influential factors, including contemporaneous and lagged actual and absolute stock returns, historical stock returns and volatilities, and company-specific events, such as earnings announcements and dividend payments.

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“…Research finds that analyst following, i.e., analyst research, and the quality of firms' financial disclosures are complements (e.g., Lang and Lundholm, 1996). Analyst research increases in corporate disclosure quality either because demand for analyst services increases in the level of corporate disclosure that users interpret differentially (Merton, 1987, Harris and Raviv, 1993, Kandel and Pearson, 1995, and Bamber, Barron, and Stober, 1999, or because analysts' costs decrease in disclosure quality (e.g., Bhushan, 1989a, and). Evidence also shows that analyst research influences the informational efficiency of capital markets.…”

Section: Introductionmentioning

confidence: 99%

Determinants of the informativeness of analyst research

Frankel

Kothari

Weber

2006

Journal of Accounting and Economics

541

165

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Analyst research helps prices reflect information about a security's fundamentals. However, analysts' private incentives potentially contribute to misleading research and it is possible that the market fixates on such misleading and/or optimistic reports. We examine cross-sectional determinants of the informativeness of analyst reports, i.e., their effect on security prices, controlling for endogeneity among the factors affecting informativeness. Analysts are more informative when the potential brokerage profits are higher (e.g., high trading volume and high volatility) and when they reveal 'bad news.' Analyst informativeness is reduced in circumstances of increased information processing costs. We fail to find evidence that informativeness of analyst reports is due to market's fixation or over-or under-reaction to analyst reports.We are grateful to Wayne Guay for helpful comments.

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Differential Interpretations and Trading Volume

Cited by 69 publications

References 5 publications

Overconfidence and trading volume

Overconfidence and trading volume

The Effect of Stock Return Sequences on Trading Volumes

Determinants of the informativeness of analyst research

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