On the Trend Recognition and Forecasting Ability of Professional Traders

49 Pages Posted: 18 Jun 2007 Last revised: 21 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

Multiple version iconThere are 3 versions of this paper

Date Written: November 15, 2007

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 and 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 do 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 (November 15, 2007). Available at SSRN: https://ssrn.com/abstract=993415 or http://dx.doi.org/10.2139/ssrn.993415

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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