—In this paper, empirical tests, based on the fuzzy
clustering means algorithm for the analysis of overreaction and
underreaction hypothesis in the American stock market are
presented. Such methodology is strongly connected with two
heuristics of behavioral finance theory: representativeness
heuristic and anchoring heuristic. The proposed methodology is
used to form portfolios through financial ratios of public
companies and the results obtained are consistent with the
strong influence of overreaction in the American stock market.
The analysis is applied for stocks from oil and gas, textile and,
steel and iron sectors, with financial indexes ranging from 1999
—Behavioral Finance, Fuzzy Clustering Means,
Renato Aparecido Aguiar is with the Centro Universitário da FEI, Dept of
Electrical Engineering (e-mail: firstname.lastname@example.org).
Roberto Moura Sales is with the Escola Politécnica da USP, Dept of
Electrical Engineering (e-mail: email@example.com).
Cite:Renato Aparecido Aguiar and Roberto Moura Sales, "Overreact Analysis in the American Stock Market: A Fuzzy C-means Algorithm Approach," International Journal of Trade, Economics and Finance vol.1, no.4, pp. 325-330, 2010.