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Article type: Research Article
Authors: Lovric, Milana | Kaymak, Uzayb; c; * | Spronk, Jaapd
Affiliations: [a] Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands | [b] Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands | [c] Eindhoven University of Technology, Eindhoven, The Netherlands | [d] Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, The Netherlands
Correspondence: [*] Corresponding author: Uzay Kaymak, Erasmus School of Economics, Erasmus University Rotterdam, Burgemeester Oudlaan 50, 3062PA Rotterdam, The Netherlands. Tel.: +31 10 4081350; Fax: +31 104089162; E-mail: [email protected].
Abstract: Agent-based stock markets as bottom-up models of financial markets allow us to study the link between individual investor behavior and aggregate market phenomena, and as such are a useful tool for investigating the implications of behavioral finance and investor psychology. In this paper we want to disentangle between the effects of investor sentiment and investor overconfidence. While investor optimism or pessimism influences the expectations of future returns, overconfidence is related to the precision of those expectations and is modeled as miscalibration. In an artificial stock market based on the LLS model, we find that more optimistic investors create more pronounced booms and crashes in the market, when compared to the unbiased efficient market believers of the original model. In the case of extreme optimism, the optimistic investors end up dominating the market, while in the case of extreme pessimism, the market reduces to the benchmark model of rational informed investors. The overconfidence of investors is found to exacerbate the effects of investor sentiment.
Keywords: Artificial stock market, agent-based modeling, behavioral finance, overconfidence, investor sentiment, optimism index, fuzzy aggregation
DOI: 10.3233/HSM-2010-0718
Journal: Human Systems Management, vol. 29, no. 2, pp. 89-101, 2010
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