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This thesis aims at investigating the market anomaly quality as defined by Asness,
Frazzini and Pedersen (2017) in their “Quality Minus Junk” factor. The undertaken study
refines the quality stocks definition and its complexity. The concept of the quality anomaly has
been for years arduous to portray, as its meaning is highly subjective and differs from one
academician to another. Quality is occasionally not seen as a “pure anomaly” since it consists
of an aggregation of numerous factors and ratios. This memoir is willing to enlighten this
interpretation puzzle.
The basic concepts of market theories and portfolio management are introduced and
discussed, just like the evolution of pricing models. The most distinguished anomalies, other
than quality, are acquainted as a preface for the quality concept debate. Hence, the QMJ factor
(Asness, Frazzini, & Pedersen, 2017) is analyzed in its three components; profitability, growth
and safety. A replica of its ratios is built using SAS software with the goal to simulate
Fama/French styled long-short portfolios based on a CRSP/Compustat dataset. The computed
portfolios are regressed on QMJ and analyzed using SAS Miner software, along with
descriptive statistics, correlations, cumulated returns and Sharpe ratios.
The results show that the growth component may be entirely dismissed without
damaging the model. The safety factors greatly matter in the regressions and strengthen their
roles into quality. Return on equity, return on assets and cash flows are profitability ratios that
are significant in the definition as well. While the signals of gross profits are remarkably
persistent and drove the quality performance in all empirical analyses. Hence, the source of
quality is identified by these late six final ratios, cutting the complexity of the definition by
more than two.

quality --- factor investing --- portfolio simulation --- qmj --- gross profit --- market anomaly --- Sciences économiques & de gestion > Finance