Overreaction In Stock Forecasts and Prices
Abstract (Via SSRN)
We study the degree of individual and aggregate market overreaction in a dynamic experimental auction market. In 13 sessions with overall 101 students we find overreaction to new information both in stock price forecasts and transaction prices. Interestingly, market forces do not seem to help in lowering overreaction to new information in our setting. Moreover, we illustrate that subjects are not able to learn from their previous failures and thus do not correct their erroneous beliefs. Hence, overreaction in our setting remains on a stable level although subjects can at least in theory learn from other market participants or from outcome feedback. Lastly, we find first experimental evidence for a positive relation between differences of opinion and trading volume in a continuous auction market with several market participants.
Excerpt (Via SSRN)
This paper extends the individual-level-study by Biais et al. (2008) to a simple experimental trading market. We analyze if subjects are able to update their beliefs according to Bayes rule or if they misreact when they receive new information about a stock and consequently if market prices overreact. Consistent with ndings in Biais et al. (2008) subjects in our setting overreact to new information on an individual level. Additionally, we nd evidence for aggregate overreaction in market prices, consistent with Thomas and Zhang (2008). Interestingly, consistent with propositions in theoretical models (e.g. Odean (1998b) and Biais and Weber (2007)) and ndings in the experimental literature (Gillette et al. (1999)) individual misreaction translates into market outcomes