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Overconfident investors in the LLS agent-based artificial financial market

Overconfident investors in the LLS agent-based artificial financial market
Overconfident investors in the LLS agent-based artificial financial market
Agent-based artificial financial markets are bottom-up models of financial markets which explore the mapping from the micro level of individual investor behavior into the macro level of aggregate market phenomena. It has been recently recognized in the literature that such (agentbased) models are potentially a very suitable tool to generate or test various behavioral hypotheses. One of the psychological biases that received a lot of attention in financial studies, both mainstream and behavioral, is the phenomena of investor overconfidence. This paper studies overconfident investors in the agent-based artificial financial market based on the Levy, Levy, Solomon (2000) model. Overconfidence is modeled as miscalibration, i.e. as underestimated risk of expected returns. We find that overconfident investors create less frequent but more extreme bubbles and crashes when compared to the unbiased efficient market believers of the original model. When investors are modeled to exhibit a biased self-attribution, they quickly move to the state of high overconfidence and remain there. With an unbiased self-attribution, on the other hand, investor overconfidence varies greatly, but around a moderate level of overconfidence
58-65
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. (2009) Overconfident investors in the LLS agent-based artificial financial market. IEEE Symposium on Computational Intelligence for Financial Engineering (CIFEr 2009), Nashville, United States. 30 Mar - 02 Apr 2009. pp. 58-65 . (doi:10.1109/CIFER.2009.4937503).

Record type: Conference or Workshop Item (Paper)

Abstract

Agent-based artificial financial markets are bottom-up models of financial markets which explore the mapping from the micro level of individual investor behavior into the macro level of aggregate market phenomena. It has been recently recognized in the literature that such (agentbased) models are potentially a very suitable tool to generate or test various behavioral hypotheses. One of the psychological biases that received a lot of attention in financial studies, both mainstream and behavioral, is the phenomena of investor overconfidence. This paper studies overconfident investors in the agent-based artificial financial market based on the Levy, Levy, Solomon (2000) model. Overconfidence is modeled as miscalibration, i.e. as underestimated risk of expected returns. We find that overconfident investors create less frequent but more extreme bubbles and crashes when compared to the unbiased efficient market believers of the original model. When investors are modeled to exhibit a biased self-attribution, they quickly move to the state of high overconfidence and remain there. With an unbiased self-attribution, on the other hand, investor overconfidence varies greatly, but around a moderate level of overconfidence

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More information

Published date: 2009
Venue - Dates: IEEE Symposium on Computational Intelligence for Financial Engineering (CIFEr 2009), Nashville, United States, 2009-03-30 - 2009-04-02
Organisations: Transportation Group

Identifiers

Local EPrints ID: 372437
URI: http://eprints.soton.ac.uk/id/eprint/372437
PURE UUID: 02b69f47-a302-449b-9a1e-36d99dabbe9f
ORCID for M. Lovric: ORCID iD orcid.org/0000-0002-8441-7625

Catalogue record

Date deposited: 11 Nov 2016 09:49
Last modified: 14 Mar 2024 18:37

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Contributors

Author: M. Lovric ORCID iD
Author: U. Kaymak
Author: J. Spronk

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