Published April 2014
| Accepted Version + Submitted
Journal Article
Open
Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility
Chicago
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Abstract
We conduct a study in which subjects trade stocks in an experimental market while we measure their brain activity using functional magnetic resonance imaging. All of the subjects trade in a suboptimal way. We use the neural data to test a "realization utility" explanation for their behavior. We find that activity in two areas of the brain that are important for economic decision-making exhibit activity consistent with the predictions of realization utility. These results provide support for the realization utility model. More generally, they demonstrate that neural data can be helpful in testing models of investor behavior.
Additional Information
© 2014 American Finance Association. Issue published online: 17 MAR 2014; Article first published online: 17 MAR 2014; Accepted manuscript online: 18 NOV 2013 06:05AM EST; Manuscript Accepted: 17 SEP 2013; Manuscript Received: 18 JUL 2011. We are grateful for comments from seminar participants at Brigham Young University, Indiana University, New York University, Stanford University, the University of California at Berkeley, the University of Connecticut, the University of Notre Dame, the University of Southern California, the University of Texas at Austin, Washington University, the Fall 2010 NBER Behavioral Finance meeting, the 2010 Society for Neuroeconomics meeting, the 2010 Miami Finance Conference, the 2011 BEAM Conference, the 2011 WFA conference, and the 2012 NBER-Oxford Saïd-CFS-EIEF Conference on Household Finance. Financial support from the National Science Foundation (Camerer, Frydman, Rangel), the Betty and Gordon Moore Foundation (Camerer, Rangel), and the Lipper Foundation (Rangel) is gratefully acknowledged. Additional Supporting Information may be found in the online version of this article at the publisher's web site.Attached Files
Accepted Version - nihms667203.pdf
Submitted - ssrn-id1892338.pdf
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nihms667203.pdf
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Additional details
- PMCID
- PMC4357577
- Eprint ID
- 45177
- DOI
- 10.1111/jofi.12126
- Resolver ID
- CaltechAUTHORS:20140424-083206634
- NSF
- Gordon and Betty Moore Foundation
- Lipper Foundation
- Created
-
2014-04-25Created from EPrint's datestamp field
- Updated
-
2021-11-10Created from EPrint's last_modified field
- Other Numbering System Name
- SSRN
- Other Numbering System Identifier
- 1892338