ACCRUALS AND MOMENTUM

• Date: 01 March 2020
• Published date: 01 March 2020
• DOI: http://doi.org/10.1111/jfir.12201
• Author: Ming Gu,Yangru Wu

The Journal of Financial Research Vol. XLIII, No. 1 Pages 63–93 Spring 2020

DOI: 10.1111/jfir.12201

ACCRUALS AND MOMENTUM

Ming Gu

Xiamen University, China

Yangru Wu

Rutgers University

Abstract

We view accruals as a natural candidate to link to momentum in the context of the

overreaction explanation. Accruals can proxy for ambiguity about the implications of new

information for a firm’s value and can vary with the business cycle. Thus, higher accruals

can lead to greater behavioral biases in the cross‐sectional and time‐series dimensions and,

hence, stronger momentum. Our results show that momentum profitability is mostly

concentrated in firms with high accruals. The previously documented cross‐sectional

characteristics of momentum and market states do not subsume the effect o f accruals on

momentum. We also find that most of the momentum returns among high‐accrual firms

are attributable to high discretionary accruals.

JEL Classification: G1, M4

I. Introduction

Jegadeesh and Titman (1993) first document that momentum strategies of buying past

winner stocks and selling past loser stocks generate statistically significant and

economically large profits. Fama and French (1996) show that their three‐factor model

(Fama and French 1993) does not explain momentum. Fama and French (2008)

highlight momentum’s pervasive effects and demonstrate that it is strong and robust in

all size groups, cross‐sectional regressions, and tests based on different sorting

methods. A variety of risk‐based explanations have been proposed to unravel this

anomaly. Several works demonstrate the significance of momentum for stocks with

certain characteristics in both cross‐sectional and time‐series analyses.

1

We appreciate helpful suggestions and valuable comments from Andres Almazan, Phil Davies, Vivian

Fang, Fangjian Fu, Rients Galema, Lixiong Guo, Armen Hovakimian, Chuan Yang Hwang, David Lesmond,

Ronald Masulis, Tavy Ronen, Rene Stulz, Sheridan Titman, Michela Verardo, Kevin Wang, Frank Zhang, the

editor, the anonymous referee, and participants at the American Finance Association meeting (Chicago), the

doctoral tutorial of the European Finance Association meeting (Stockholm), the Financial Management

Association meeting (Denver), and the Rutgers University seminar. Part of this work was completed while Wu

visited the Central University of Finance and Economics. All remaining errors are our own.

1

Risk‐based explanations include Berk, Green, and Naik (1999), Grundy and Martin (2001), Johnson

(2002), Ahn, Conrad, and Dittmar (2003), Grinblatt and Moskowitz (2004), Korajczyk and Sadka (2004),

Lesmond, Schill, and Zhou (2004), and Wang and Wu (2011). Characteristics‐based analyses include Asness

(1997), Hong, Lim, and Stein (2000), Lee and Swaminathan (2000), Chordia and Shivakumar (2002), Cooper,

Gutierrez, and Hameed (2004), Zhang (2006), Sadka (2006), Sagi and Seasholes (2007), Avramov et al. (2007),

Garlappi and Yan (2011), Antoniou, Doukas, and Subrahmanyam (2013), Wang and Xu (2015), and

Avramov, Cheng, and Hameed (2016).

63

© 2019 The Southern Finance Association and the Southwestern Finance Association

In this article, we link an important firm characteristic, accruals, to momentum

in the context of the overreaction explanation. We find that momentum profitability is

statistically significant and economically large among high‐accrual firms, but is

nonexistent or much weaker for firms with low and medium levels of accruals.

2

The

previously documented cross‐sectional characteristics of momentum and market states

do not subsume the effect of accruals on momentum. Furthermore, most of the

momentum returns among high‐accrual firms are attributable to high discretionary

accruals.

A number of studies (e.g., DeLong et al. 1990; Chan, Jegadeesh, and

Lakonishok 1996; Barberis, Shleifer, and Vishny 1998; Hong and Stein 1999;

Hirshleifer 2001; Daniel, Hirshleifer, and Subrahmanyam 1998, 2001) develop

behavioral models to explain momentum and other financial “anomalies.”For

example, Daniel, Hirshleifer, and Subrahmanyam (1998) model overconfidence as

investors’exaggeration of their information‐processing abilities. Overconfidence

is generally supported by bias in self‐attribution, which means that investors credit

their own talents and abilities for past successes and blame their failures on bad

luck. The authors that self‐attributed investors are overconfident about their stock‐

selection skills and overestimate the precision of their signals. Specifically, such

investors overweigh the value of their private signals and place inadequate weight

on public signals. With greater value ambiguity, investors trade more aggressively

on their private signals.

3

If momentum comes from investors’overconfidence and

self‐attribution, we should expect stronger momentum among firms whose

businesses are harder to value.

Several studies examine implications of the overreaction hypothesis from both

the cross‐sectional and time‐series perspectives. At the cross‐section, Jiang, Lee, and

Zhang (2005) document that momentum strategies work better among firms with

young age, high trading volume, high volatility, and long duration cash flows. Chui,

Titman, and Wei (2010) demonstrate that an individualism index featuring investor

overconfidence helps explain cross‐country differences in momentum. At the time

series, Chordia and Shivakumar (2002) and Cooper, Gutierrez, and Hameed (2004)

argue that during expansionary/bullish states, overconfidence should be stronger, thus

leading to greater momentum. We investigate how accrual‐related information

contributes to behavioral explanations for momentum. We argue that accruals work

as a natural candidate to link to momentum in the context of the overreaction

hypothesis because accruals can enhance behavioral biases in the cross‐sectional and

time‐series dimensions.

2

In this article, we study the effect of accruals on momentum in the cross‐section. Specifically, following

the literature on cross‐sectional study of momentum, we employ accruals as the sorting variable and study

momentum in each accruals group. We leave the time‐series dimension of accrual‐based momentum for future

research.

3

Jiang, Lee, and Zhang (2005) refer to value ambiguity as the degree to which a firm’s value can be

reasonably estimated by even the most knowledgeable investors at reasonable costs. Building on this concept, we

argue that the overconfidence bias is accentuated in high‐ambiguity settings.

64 The Journal of Financial Research