Modeling loss aversion and biased self-attribution using a fuzzy aggregation operator

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.