Review of Financial Studies Vol. 35 No. 11 2022

Decision Weights for Experimental Asset Prices Based on Visual Salience

Devdeepta Bose¹; Henning Cordes²; Sven Nolte³; Judith C. Schneider⁴; Colin F. Camerer¹

¹ California Institute of Technology , USA · ² University of Münster , Germany · ³ Institute for Management Research, Radboud University Nijmegen , The Netherlands · ⁴ Institute for Risk and Insurance, Leibniz University Hannover , Germany

Abstract

We apply a machine-learning algorithm, calibrated using general human vision, to predict the visual salience of prices of stock price charts. We hypothesize that the visual salience of adjacent prices increases the decision weights on returns computed from those prices. We analyze the inferred impact of these weights in two experimental studies that use either historical price charts or simpler artificial sequences. We find that decision weights derived from visual salience are associated with experimental investments. The predictability is not subsumed by statistical features and goes beyond established models.

DOI

10.1093/rfs/hhac027

Volume

35

Issue

11

Pages

5094-5126

Language

en

Sources

bibtex:phds-export.bib crossref openalex

Cite

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