TITLE:
Risk Factors and Stock Price Performance of U.S. Sectors: A Quintile Approach
AUTHORS:
Panagiotis G. Artikis, Lydia G. Diamantopoulou, Christos G. Kampouris
KEYWORDS:
Asset Pricing, Industry Indices, Cyclical vs Non-Cyclical, U.S. Stock Market, Factor Model, Quantile Regression
JOURNAL NAME:
Theoretical Economics Letters,
Vol.12 No.3,
June
28,
2022
ABSTRACT: The present paper examines the ability of factor
pricing models to explain the returns of U.S. stock market sectors. Using
monthly data for ten U.S. sectors, from October 1989 to December 2020, classified
according to the Global Industry Classification Standards (GICS), we find that
asset pricing characteristics vary by industry, however, there are distinct
patterns in terms of risk factor loadings and their respective significance
depending on whether industries are classified as cyclical or defensive. This
suggests that within industries’ classification sectors might be, at least at
some level, homogenous. Our analysis also reveals that four sectors exhibit an
off-pattern behavior, namely Finance, Information Technology, Consumer Staples
and Energy. The time period consists of our analysis is quite diverse and
includes periods of booming markets, but also extreme recession periods. Thus,
we employ quantile regressions to investigate the validity of the models under
extreme conditions. Our basic conclusions do not seem to be affected by
fat-tails and conditional on the quantile the best performing model may vary,
in some sectors.