On the Trend Recognition and Forecasting Ability of Professional Traders

Decision Analysis, Vol. 4, No. 4, pp. 176-193, 2007

Posted: 16 Jan 2008

See all articles by Markus Glaser

Markus Glaser

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management)

Martin Weber

University of Mannheim - Department of Banking and Finance

Thomas Langer

University of Muenster - Finance Center

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Abstract

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.

Keywords: trend recognition, forecasting, conservatism, overconfidence, professionals, financial modeling

JEL Classification: C9, G1

Suggested Citation

Glaser, Markus and Weber, Martin and Langer, Thomas, On the Trend Recognition and Forecasting Ability of Professional Traders. Decision Analysis, Vol. 4, No. 4, pp. 176-193, 2007, Available at SSRN: https://ssrn.com/abstract=1084403

Markus Glaser (Contact Author)

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management) ( email )

Schackstra├če 4
Munich, 80539
Germany

Martin Weber

University of Mannheim - Department of Banking and Finance ( email )

D-68131 Mannheim
Germany
+49 621 181 1532 (Phone)
+49 621 181 1534 (Fax)

Thomas Langer

University of Muenster - Finance Center ( email )

Universitatsstr. 14-16
Muenster, 48143
Germany
+49 251 83 22033 (Phone)

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