Asset growth and stock return: evidence in the Brazilian market

Machado, Márcio André Veras; Faff, Robert William

doi:10.1590/1808-057x201805080

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Brasil

Revista Contabilidade & Finanças

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Original Article • Rev. contab. finanç. 29 (78) • Sep-Dec 2018 • https://doi.org/10.1590/1808-057x201805080 copy

Asset growth and stock return: evidence in the Brazilian market

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Empirical evidence suggests that firms which have experienced fast growth, through increased external funding and by making capital investments and acquisitions, tend to show bad operating performance and lower stock returns, whereas firms that have experienced contraction, through divestiture, share repurchase and debt retirement, tend to show good operating performance and higher stock returns. So, this study aimed to analyze the relationship between asset growth and stock return in the Brazilian stock market, and it tested the hypothesis that asset growth is negatively related to future stock return. To do this, the methodology was divided into 3 steps: verifying 1) if asset growth anomaly exists; 2) if this relation may be explained by the investment friction hypothesis and/or by the limits-to-arbitrage hypothesis; and 3) if asset growth is a risk factor or mispricing. In addition, the analysis was carried out both at a portfolio level and an individual assets level. The sample included all the non-financial firms listed at B3 from June 1997 to June 2014. As for the main results, this study found that the asset growth effect exists, both at the portfolio level and the individual assets level, although it is sensitive to the proxy. About the effect’s materiality, this study concluded that the asset growth effect is not economically relevant, since it is not observed in big firms, regardless of the proxy used, a fact that makes it difficult to explore this effect. Another finding is that the asset growth effect may not be related to the limits-to-arbitrage hypothesis and to the financial constraint hypothesis; also, this effect may be considered a risk factor, suggesting that the investment effect documented in the Brazilian stock market may be explained by the rational asset pricing perspective. Therefore, capital market professionals should take into account the asset growth factor in asset pricing models for better investment risk assessment.

Keywords
anomalies; asset growth effect; investment effect; risk factors

	Summary statistics
	Mean	SD		Minimum		25%		Median			75%		Maximum
Size (in million R$)	3563.066	10801.240		0.588		136.953		651.936			2983.516		246964.212
BM	1.297	1.802		0.000		0.423		0.800			1.500		28.800
Mom	0.089	0.549		-2.742		-0.189		0.093			0.359		7.269
E/A	-0.030	6.465		-335.318		0.030		0.088			0.162		7.164
Liq (in million R$)	244.994	1014.264		0.004		1.483		15.485			142.538		16681.179
Volat	0.183	0.131		0.024		0.104		0.147			0.222		1.757
Payout	0.457	9.837		-332.719		0.000		0.245			0.521		272.034
AT (in million R$)	6084.759	27330.566		8.510		449.353		1217.927			3815.646		633173.147
LSZ	0.029	0.136		-0.779		-0.001		0.001			0.040		2.198
CGS	2.284	101.606		-0.991		0.009		0.091			0.215		5303.022
XING	88.436	2322.276		-1878.209		-0.475		0.083			1.040		79847.882
PS	403.707	7534.762		-34882.000		0.042		0.217			0.749		257417.000
FF	136.120	2749.444		-8.821		0.976		1.074			1.193		117947.405
	Correlation
	Size	BM	Mom	E/A	Liq	Volat	Payout	AT	LSZ	CGS	XING	PS	FF
Size	1
BM	-0.108***	1
Mom	0.011	-0.136***	1
E/A	0.101	-0.128	0.106***	1
Liq	0.793***	-0.064***	-0.018	0.052	1
Volat	-0.041**	0.004	-0.045*	-0.018	-0.040**	1
Payout	0.017	-0.018	0.023	0.000	0.039	-0.004	1
AT	0.697***	0.002	-0.017	0.015	0.807***	-0.041*	0.038*	1
LSZ	0.018	-0.034**	-0.012	0.026	0.035	0.000	-0.007	0.042*	1
CGS	0.023	-0.068	0.002	0.059	0.029	0.025	-0.016	-0.002	0.357	1
XING	-0.006	-0.011	0.006	0.000	-0.006	0.017	-0.001	-0.006	-0.005	-0.007	1
PS	0.002	-0.014	-0.004	-0.009	-0.005	0.003	-0.003	-0.005	0.012	0.077	-0.002	1
FF	-0.009	-0.015	-0.009	0.006	-0.007	0.012	0.003	-0.006	0.012	0.028	-0.001	-0.003	1

	High AG	Q2	Q3	Q4	Low AG	Spread (Low AG - High AG)
XING	0.015	0.013	0.013	0.013	0.013	-0.002
CGS	0.013	0.016	0.010	0.012	0.017	0.003
FF	0.013	0.018	0.011	0.010	0.014	0.001
LSZ	0.012	0.012	0.013	0.010	0.020	0.009*
PS	0.012	0.013	0.018	0.014	0.014	0.003

	High AG	Q2	Q3	Q4	Low AG	L-H
	Big size
LSZ	0.014**	0.009	0.015**	0.008	0.0208*	0.006
CGS	0.011*	0.013**	0.017**	0.006	0.016***	0.005
XING	0.012	0.014**	0.014**	0.013**	0.011	-0.001
PS	0.014**	0.012*	0.014**	0.014**	0.013**	-0.001
FF	0.009	0.017***	0.012*	0.011	0.011*	0.002
	Medium size
LSZ	0.011*	0.009	0.018*	0.013**	0.021*	0.010*
CGS	0.007	0.021***	0.010	0.013**	0.018***	0.011***
XING	0.012*	0.015**	0.008	0.016***	0.017***	0.005
PS	0.007	0.018***	0.012**	0.011*	0.018***	0.011**
FF	0.012*	0.016**	0.014**	0.015***	0.011	-0.001
	Small size
LSZ	0.010	0.014**	0.008	0.021**	0.011	0.001
CGS	0.010	0.008	0.011*	0.019***	0.009	-0.002
XING	0.023***	0.010*	0.002	0.010	0.014	-0.009
PS	0.008	0.013**	0.014**	0.010	0.014	0.005
FF	0.017***	0.006	0.019***	0.010*	0.001	-0.017*

Proxy	3-factor	4-factor	5-factor
All
XING	0.000	0.000	-0.002
CGS	0.005	0.006	0.007*
FF	0.003	0.006	0.006
LSZ	0.008*	0.009*	0.008*
PS	0.008	0.007	0.007
Big size
XING	0.006	0.003	0.004
CGS	0.004	0.005	0.007
FF	0.002	0.005	0.005
LSZ	0.009	0.009	0.009
PS	0.000	0.001	-0.003
Medium size
XING	0.008	0.004	0.007
CGS	0.011***	0.009**	0.013***
FF	-0.002	-0.002	0.000
LSZ	0.012**	0.009*	0.011**
PS	0.015*	0.010	0.016*
Small size
XING	-0.004	-0.008	-0.006
CGS	0.001	-0.006	0.006
FF	-0.009	-0.013***	-0.007
LSZ	0.000	-0.005	0.000
PS	0.009	0.007	0.008

Panel A - All firms
	1	2	3	4	5	6
Intercept	0.3630**	0.3498**	0.3731**	0.3649**	0.3646**	0.3760**
VM	-0.0223**	-0.0206**	-0.0227**	-0.0218**	-0.0222**	-0.0240**
BM	-0.1036***	-0.1059***	-0.1057***	-0.1068***	-0.0942***	-0.1003***
MOM	0.3527***	0.3561***	0.3537***	0.3515***	0.3723***	0.3473***
E/A	0.0813	0.0934	0.0733	0.0850	0.0664	0.1157
CGS		-0.0714**
FF			-0.0023
LSZ				-0.3047***
PS					-0.0001
XING						0.0004
R²	0.2901	0.2970	0.2947	0.2966	0.3023	0.2902
Panel B - Small-sized firms
Intercept	0.3285	0.296	0.2138	0.2966	0.3023	0.2902	0.3405	0.3537	0.3933***
VM	-0.0176	-0.0130	-0.0149	-0.0182	-0.0179	-0.0249
BM	-0.0869**	-0.0898**	-0.1059***	-0.0906**	-0.0804**	-0.0744*
MOM	0.4033***	0.4198***	0.3989***	0.4192***	0.4723***	0.3968***
E/A	0.0417	0.0619	-0.0185	0.0196	-0.1420	0.0348
CGS		-0.1482
FF			0.1040
LSZ				-0.2752
PS					-0.0016
XING						-0.0003
R²	0.3778	0.4036	0.3944	0.4009	0.4271	0.3913
Panel C - Medium-sized firms
Intercept	0.4733**	0.4132**	0.4945**	0.4009	0.4271	0.3913	0.4968**	0.3983	0.4357***
VM	-0.0335***	-0.0280**	-0.0355***	-0.0350**	-0.0246	-0.0305*
BM	-0.1428***	-0.1507***	-0.1441***	-0.1476***	-0.1470***	-0.1243***
MOM	0.3620***	0.3475***	0.3556***	0.3566***	0.3638***	0.3709***
E/A	0.0072	0.0400	-0.0002	-0.0123	-0.1230	0.1130
CGS		-0.1339*
FF			0.0031
LSZ				-0.3353**
PS					0.0004
XING						0.0009
R²	0.3306	0.3557	0.3449	0.3474	0.369	0.3552
Panel D - Big firms
Intercept	0.1307	0.2215	0.0485	0.3474	0.369	0.3552	0.1537	0.0361	0.1942
VM	-0.0027	-0.0077	0.0027	-0.0023	0.0036	-0.0086
BM	-0.1082*	-0.1170*	-0.1176*	-0.1170*	-0.1019*	-0.0977*
MOM	0.3907***	0.3913***	0.3728***	0.4112***	0.4482***	0.3856**
E/A	-0.4510*	-0.4737	-0.4675*	-0.5432	-0.4967*	-0.3249*
CGS		-0.1497
FF			0.0019
LSZ				-0.5966
PS					-0.0010
XING						-0.0042
R²	0.3995	0.3893	0.3826	0.3811	0.4071	0.3960

Panel A - Financial constraint proxies
Small Size	-0.1143
BIG Size	-0.2504
Small - BIG Size	0.1361
Low Payout	-0.4473*
High Payout	-0.4830*
Low - High Payout	0.0337
Panel B - Limits-to-arbitrage proxies
Low Vol	-0.2185
High Vol	-0.8144***
Low - High Vol	0.5959
Low Liquidity	-0.6398**
High Liquidity	-0.0271
Low - High Liquidity	-0.3683

Panel A: Step 1			Panel B: Step 2
	Coef.	t-stat		Coef.	t-stat
Intercept	0.012	7.145	λ₀	-0.005	-0.461
MRP	0.962	31.205	λ₁	0.004	0.330
SMB	0.422	3.864	λ₂	0.003	0.660
HML	0.016	0.313	λ₃	0.009	1.007
RMW	0.000	-0.001	λ₄	0.000	-0.048
AG	0.051	0.535	λ₅	0.006	1.614
R2 adjust	0.620		R2 adjust	0.440

Universidade de São Paulo, Faculdade de Economia, Administração e Contabilidade, Departamento de Contabilidade e Atuária Av. Prof. Luciano Gualberto, 908 - prédio 3 - sala 118, 05508 - 010 São Paulo - SP - Brasil, Tel.: (55 11) 2648-6320, Tel.: (55 11) 2648-6321, Fax: (55 11) 3813-0120 - São Paulo - SP - Brazil
E-mail: recont@usp.br

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[1] Correspondence address: Márcio André Veras Machado Universidade Federal da Paraíba, Centro de Ciências Sociais Aplicadas, Departamento de Administração. Campus I - Via Expressa Padre Zé, 289 - CEP 58051-900 Cidade Universitária - Castelo Branco III - João Pessoa - PB - Brazil