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Abstract Herding in financial markets refers to that investors are influenced by others. This study addresses the importance of consistency for herding. It is suggested that, in financial markets perceptions of consistency are based on repeated observations over time. Consistency may then be perceived as the agreement across time between investors' predictions. In addition, consistency may be related to variance over time in each investor's predictions. In an experiment using a Multiple Cue Probability Learning paradigm, 96 undergraduates made multi‐trial predictions of future stock prices given information about the current price and the predictions made by five fictitious others. Consistency was varied between the others' predictions (correlation) and within the others' predictions (variance). The results showed that the predictions were significantly influenced by the others' predictions when these were correlated. No effect of variance was observed. Hence, participants were influenced by the others when they were in agreement, regardless of whether they varied their predictions over trials or not. Copyright © 2008 John Wiley & Sons, Ltd.
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