Publication:
The quality premium with leverage and liquidity constraints

Consultable a partir de

2023-05-01

Date

2021

Authors

Rubio Irigoyen, Gonzalo

Director

Publisher

Elsevier
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión aceptada / Onetsi den bertsioa

Project identifier

AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-095072-B-I00/ES/
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-104304GB-I00/ES/

Abstract

This research analyzes the causes of the quality premium, one of the most intriguing and successful investment strategies in equity markets. While previous research has argued that psychological biases explain the performance of the quality minus junk factor, our paper analyzes a leverage constraint explanation within a rational risk-based framework. The quality factor is multidimensional in nature, which suggests that a combination of risk, frictions, and behavioral biases is a reasonable explanation. Once we incorporate margin requirements and liquidity restrictions, we find that tighter conditions result in a higher intercept and a lower slope for the empirically implemented capital asset pricing model when using 10 quality-sorted portfolios. Our paper shows that, indeed, not only behavioral biases explain quality, but also market frictions account for its performance.

Keywords

Margin requirements, Quality premium, Funding constraints, Liquidity constraints, Security market line

Department

Enpresen Kudeaketa / Institute for Advanced Research in Business and Economics - INARBE / Gestión de Empresas

Faculty/School

Degree

Doctorate program

Editor version

Funding entities

The authors acknowledge financial support from the Ministry of Science, Innovation, and Universities through grant PGC2018-095072B-I00. In addition, Gonzalo Rubio acknowledges financial support from Generalitat Valencia grant Prometeo/2017/158, and Ana González Urteaga acknowledges financial support from the Ministry of Science and Innovation through grant PID2019-104304-GB-I00/AEI/10.13039/501100011033 and UPNA Research Grant for Young Researchers, Edition 2018.

© 2021 Elsevier Inc. This manuscript version is made available under the CC-BY-NC-ND 4.0

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