HEC-Ecole de gestion de l'Université de Liège
HEC-Ecole de gestion de l'Université de Liège

Quantitative analyses on portfolios simulations : how complex should the quality stocks definition be ?

Delhez, Rémy-Baptiste ULiège
Promotor(s) : Antonelli, Cédric ULiège
Date of defense : 4-Sep-2017/11-Sep-2017 • Permalink :
Title : Quantitative analyses on portfolios simulations : how complex should the quality stocks definition be ?
Translated title : [fr] Analyses quantitatives sur simulations de portefeuilles: A quel point la définition d'une action de qualité doit-elle être élaborée?
Author : Delhez, Rémy-Baptiste ULiège
Date of defense  : 4-Sep-2017/11-Sep-2017
Advisor(s) : Antonelli, Cédric ULiège
Committee's member(s) : Fays, Boris ULiège
Ganter, Julien 
Language : English
Number of pages : 81
Keywords : [en] quality
[en] factor investing
[en] portfolio simulation
[en] qmj
[en] gross profit
[en] market anomaly
Discipline(s) : Business & economic sciences > Finance
Target public : Researchers
Professionals of domain
General public
Institution(s) : Université de Liège, Liège, Belgique
Degree: Master en sciences de gestion, à finalité spécialisée en Banking and Asset Management
Faculty: Master thesis of the HEC-Ecole de gestion de l'Université de Liège


[en] 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.



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  • Delhez, Rémy-Baptiste ULiège Université de Liège > Master sc. gest., à fin.


Committee's member(s)

  • Fays, Boris ULiège Université de Liège - ULg > HEC Liège : UER > Analyse financière et finance d'entreprise
    ORBi View his publications on ORBi
  • Ganter, Julien KPMG
  • Total number of views 71
  • Total number of downloads 408

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