Anchoring Heuristics, Investor Sentiment and Stylized Facts in the Stock Market: An Agent Based Model

Abstract

The objective of this paper is to contribute to a theoretical explanation based on Behavioral Finance of three stylized facts of stock market actions which are considered puzzles by Efficient Market Hypothesis (EMH): an excess of volatility in relation to fundamentals, heavy tail distributions of returns, and volatility clustering. Using an agent-based model (ABM), this paper examines the dynamics of fluctuations in the rate of return of shares in an artificial financial environment for three simulation scenarios: 1 ) 100% of fundamental agents, 2 ) 75% fundamental and 25% chart agents using anchoring heuristics (eight rules of share price forecasts) and 3 ) the same composition of agents of scenario 2, in which the chart agents suffer from excess of confidence or pessimism in terms of their expectations. The presence of chart agents in scenario 2 is necessary and sufficient to generate and explain the excess of price volatility and the rate of return of shares. In scenario 3, the sentiment of heterogeneous chart agents explains the heavy tail distributions of share returns and volatility clusters. Also, the linear auto-correlation of absolute rates of return decays slowly to become insignificant in large lags, while the log values of the linear auto-correlation function of rates of returns decays quickly to become insignificant in small lags. The model simultaneously shows the emergence of three of the main stylized facts of the stock market, increasing the micro-diversity of chart agents and the realism of the expectation formation rules.