TITLE:
Anchoring Heuristics, Investor Sentiment and Stylized Facts in the Stock Market: An Agent Based Model
AUTHORS:
Hermes Yukio Higachi, Ana Cristina Cruz de Faria, Adriana Sbicca, Jefferson Kato
KEYWORDS:
Anchoring Heuristic, Investor Sentiment, Stock Market Stylized Facts, Agent-Based Model
JOURNAL NAME:
Theoretical Economics Letters,
Vol.10 No.1,
February
27,
2020
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.