Using an agent based model we examine the dynamics of stock price fluctuations and their return rates in an artificial financial market composed of fundamentalists and chartists with and without confidence. Our goal is to create an agent based model in which the agents exhibit confidence in their decision making in accordance with the behavioral finance approach, and we assume the level of agent confidence evolves during the simulation time. A small number of papers in the literature incorporate psychological biases into the agents, such as: Takahashi and Terano (2003), Lovric (2011), and Bertella et al. (2014). Our study is similar to this last work, but it differs in the way we model confidence and how we verify the robustness of our model. We find that chartists who are confident generate higher price and return rate volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index - both generated by our model - are cointegrated and the stock price affects confidence index but confidence index does not affect stock price. To estimate the robustness of our model, we compare its results in two cases: (i) the S&P 500 index and the stock market confidence calculated by Yale School of Management, and (ii) the growth rate of both the S&P 500 and its confidence index. As in our model, Engle-Granger and Johansen tests indicate there is cointegration between stock prices and stock market confidence indices, and between price growth and confidence growth rate. Besides, the Granger causality test indicates that price or its growth rate affects confidence and its growth rate whose results corroborate the predictions of our model.

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