On the trend recognition and forecasting ability of professional traders

Empirical research documents that temporary trends in stock price movements exist, so that riding a trend can be a profitable investment strategy. In this paper, we provide a thorough test of the trend recognition and forecasting ability of financial professionals who work in the trading room of a large bank, as well as those of novices (students). In an experimental study using a within–subject design, we analyze two ways of trend prediction that have analogues in the real world: probability estimates and confidence intervals (quantile estimates). We find that, depending on the type of task, either underconfidence (in probability estimates) or overconfidence (in confidence intervals) can be observed in the same trend prediction setting based on the same information. Furthermore, we find that the degree of overconfidence in both tasks is significantly positively correlated for all experimental subjects. These findings not only contribute to the literature on judgmental forecasting, but also have important implications for financial modeling. This paper demonstrates that a theorist has to be careful when deriving assumptions about the behavior of agents in financial markets from psychological findings.