Abstract
Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return 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 that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant.
Highlights
In recent decades the efficient market hypothesis (EMH) has been generally assumed to be true in finance [1]
The EMH is based on three arguments, (i) that investors are rational, perfectly consistent and coherent as they critically examine their options, and possess enormous computational power, (ii) that some investors are irrational but because their actions are random they cancel themselves out and do not affect asset prices, and (iii) that when irrational investors begin to act in concert they are stopped by rational arbitrageurs who eliminate their influence on asset prices [1]
One of the creators of the EMH, stated “there is no other proposition in economics which has more solid empirical evidence supporting it than the efficient market hypothesis” [3]
Summary
In recent decades the efficient market hypothesis (EMH) has been generally assumed to be true in finance [1]. Tversky and Kahneman [5] point out that trader actions can indicate a departure from the conventional rational decision model in several fundamental areas, including their attitudes towards risk, their mental accounting, and when they exhibit overconfidence Awareness of these psychological factors and of the reality that arbitrage is limited has produced a new approach to the study of financial markets: behavioral finance (BF). Our goal here 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 that the level of agent confidence evolves during the simulation time. For the formation of expectations regarding the price and future dividend of the stock traded, Ei,t(pt+1 + dt+1), the fundamentalists assume certain rules based on the dividend at time t and estimate that growth will be at a constant rate g, i.e., Eðdtþ1Þ 1⁄4 dtð þ gÞ ð8Þ and. After the level of agent confidence is updated, Ci,t+1 it is mapped at the original interval [0, 1[ using the inverse transformation function as described by Lovric [16], oci;tþ1 1⁄4 TÀ 1ðCi;tþ1Þ 1⁄4
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