Modeling loss aversion and biased self-attribution using fuzzy aggregation
Modeling loss aversion and biased self-attribution using fuzzy aggregation
In this paper we use an agent-based stock market to study how investor performance and market predictions influence investor sentiment and confidence. Investor sentiment is modeled using a generalized average operator, which has been proposed in the fuzzy literature as an index of optimism. Our simulations show the impact of loss aversion on investor optimism, and the emergence of investor overconfidence through biased self-attribution. Computational models of financial markets show potential for studying the dynamics of investor psychology with respect to various market feedbacks, while the fuzzy aggregation operator used provides a convenient way of modeling those psychological effects
2297-2304
Lovric, M.
64a3c876-4d8f-442f-9062-6dc491c773d1
Kaymak, U.
baac9f6c-c524-4367-b671-e9854a0f1e6a
Spronk, J.
e9b58abe-e9f9-4f89-b4e4-cb4f622c0390
Lovric, M.
64a3c876-4d8f-442f-9062-6dc491c773d1
Kaymak, U.
baac9f6c-c524-4367-b671-e9854a0f1e6a
Spronk, J.
e9b58abe-e9f9-4f89-b4e4-cb4f622c0390
Lovric, M., Kaymak, U. and Spronk, J.
(2010)
Modeling loss aversion and biased self-attribution using fuzzy aggregation.
World Congress on Computational Intelligence (WCCI 2010), Barcelona, Spain.
18 - 23 Jul 2010.
.
(doi:10.1109/FUZZY.2010.5584899).
Record type:
Conference or Workshop Item
(Paper)
Abstract
In this paper we use an agent-based stock market to study how investor performance and market predictions influence investor sentiment and confidence. Investor sentiment is modeled using a generalized average operator, which has been proposed in the fuzzy literature as an index of optimism. Our simulations show the impact of loss aversion on investor optimism, and the emergence of investor overconfidence through biased self-attribution. Computational models of financial markets show potential for studying the dynamics of investor psychology with respect to various market feedbacks, while the fuzzy aggregation operator used provides a convenient way of modeling those psychological effects
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e-pub ahead of print date: 2010
Venue - Dates:
World Congress on Computational Intelligence (WCCI 2010), Barcelona, Spain, 2010-07-18 - 2010-07-23
Organisations:
Transportation Group
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Local EPrints ID: 375067
URI: http://eprints.soton.ac.uk/id/eprint/375067
PURE UUID: 3e2d07c3-f650-4ae6-a0fc-17f5e051c546
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Date deposited: 11 Nov 2016 10:19
Last modified: 14 Mar 2024 19:18
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Author:
U. Kaymak
Author:
J. Spronk
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