The objective of this paper is to contribute to atheoretical explanation based on Behavioral Finance of three stylized facts ofstock market actions which are considered puzzles by Efficient MarketHypothesis (EMH): an excess of volatility in relation to fundamentals, heavytail distributions of returns, and volatility clustering. Using an agent-basedmodel (ABM), this paper examines the dynamics of fluctuations in the rate ofreturn of shares in an artificial financial environment for three simulationscenarios: 1) 100%of fundamental agents, 2) 75%fundamental and 25% chart agents using anchoring heuristics (eight rules ofshare price forecasts) and 3) thesame composition of agents of scenario 2, in which the chart agents suffer fromexcess of confidence or pessimism in terms of their expectations. The presenceof chart agents in scenario 2 is necessary and sufficient to generate and explainthe excess of price volatility and the rate of return of shares. In scenario 3,the sentiment of heterogeneous chart agents explains the heavy taildistributions of share returns and volatility clusters. Also, the linearauto-correlation of absolute rates of return decays slowly to becomeinsignificant in large lags, while the log values of the linear auto-correlationfunction of rates of returns decays quickly to become insignificant in smalllags. The model simultaneously shows the emergence of three of the mainstylized facts of the stock market, increasing the micro-diversity of chartagents and the realism of the expectation formation rules.
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