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Investor memory of past performance is positively biased and predicts overconfidence

We document a memory-based mechanism associated with investor overconfidence. In Studies 1 and 2, investors were asked to recall their most important trades in the recent past and then reported investing confidence and trading frequency. After the study, they looked up and reported the actual return...

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Detalles Bibliográficos
Autores principales: Walters, Daniel J., Fernbach, Philip M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433511/
https://www.ncbi.nlm.nih.gov/pubmed/34475206
http://dx.doi.org/10.1073/pnas.2026680118
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author Walters, Daniel J.
Fernbach, Philip M.
author_facet Walters, Daniel J.
Fernbach, Philip M.
author_sort Walters, Daniel J.
collection PubMed
description We document a memory-based mechanism associated with investor overconfidence. In Studies 1 and 2, investors were asked to recall their most important trades in the recent past and then reported investing confidence and trading frequency. After the study, they looked up and reported the actual returns of these trades. In both studies, investors were biased to recall returns as higher than achieved, and larger memory biases were associated with greater overconfidence and trading frequency. The design of Study 2 allowed us to separately investigate the effects of two types of memory biases: distortion and selective forgetting. Both types of bias were present and were independently associated with overconfidence and trading frequency. Study 3 was an incentive-compatible experiment in which overconfidence and trading frequency were reduced when participants looked up previous consequential trades compared to when they reported them from memory.
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spelling pubmed-84335112021-09-28 Investor memory of past performance is positively biased and predicts overconfidence Walters, Daniel J. Fernbach, Philip M. Proc Natl Acad Sci U S A Social Sciences We document a memory-based mechanism associated with investor overconfidence. In Studies 1 and 2, investors were asked to recall their most important trades in the recent past and then reported investing confidence and trading frequency. After the study, they looked up and reported the actual returns of these trades. In both studies, investors were biased to recall returns as higher than achieved, and larger memory biases were associated with greater overconfidence and trading frequency. The design of Study 2 allowed us to separately investigate the effects of two types of memory biases: distortion and selective forgetting. Both types of bias were present and were independently associated with overconfidence and trading frequency. Study 3 was an incentive-compatible experiment in which overconfidence and trading frequency were reduced when participants looked up previous consequential trades compared to when they reported them from memory. National Academy of Sciences 2021-09-07 2021-09-02 /pmc/articles/PMC8433511/ /pubmed/34475206 http://dx.doi.org/10.1073/pnas.2026680118 Text en Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Social Sciences
Walters, Daniel J.
Fernbach, Philip M.
Investor memory of past performance is positively biased and predicts overconfidence
title Investor memory of past performance is positively biased and predicts overconfidence
title_full Investor memory of past performance is positively biased and predicts overconfidence
title_fullStr Investor memory of past performance is positively biased and predicts overconfidence
title_full_unstemmed Investor memory of past performance is positively biased and predicts overconfidence
title_short Investor memory of past performance is positively biased and predicts overconfidence
title_sort investor memory of past performance is positively biased and predicts overconfidence
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433511/
https://www.ncbi.nlm.nih.gov/pubmed/34475206
http://dx.doi.org/10.1073/pnas.2026680118
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