The conditional Fama-French model and endogenous illiquidity: A robust instrumental variables test
Autoři:
François-Éric Racicot aff001; William F. Rentz aff001; David Tessier aff003; Raymond Théoret aff004
Působiště autorů:
Telfer School of Management, University of Ottawa, Ottawa, ON, Canada
aff001; Affiliate Research Fellow, IPAG Business School, Paris, France
aff002; Département des Sciences Administratives, Université du Québec en Outaouais (UQO), Gatineau, QC, Canada
aff003; Ecole des Sciences de la Gestion, Université du Québec à Montréal (ESG-UQAM), Montréal, QC, Canada
aff004; Chaire d’information Financière et Organisationnelle, ESG-UQAM, Montreal, QC, Canada
aff005
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0221599
Souhrn
We investigate conditional specifications of the five-factor Fama-French (FF) model, augmented with traditional illiquidity measures. The motivation for this time-varying methodology is that the traditional static approach of the FF model may be misspecified, especially for the endogenous illiquidity measures. We focus on the time-varying nature of the Jensen performance measure α and the market systematic risk sensitivity β, as these parameters are essentially universal in asset pricing models. To tackle endogeneity and other specification errors, we rely on our robust instrumental variables (RIV) algorithm implemented via a GMM approach. In this dynamic or time-varying conditional context, we generally find that the most significant factor is the market one, but illiquidity may matter depending on which states or estimation methods we consider. In particular, sectors whose returns embed a market illiquidity premium are more exposed to a binding funding constraint in times of crisis, which leads to deleveraging and a resulting decrease in systematic risk.
Klíčová slova:
Social sciences – Economics – Finance – Public finance – Money supply and banking – Financial markets – Economic analysis – Econometrics – Mathematical economics – Research and analysis methods – Mathematical and statistical techniques – Statistical methods – Instrumental variable analysis – Simulation and modeling – Kalman filter – Physical sciences – Mathematics – Statistics – Applied mathematics – Algorithms – Probability theory – Probability distribution – Skewness
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