Fund management fees: the role of industry competition and investor sentiment

Silva, Sabrina Espinele da; Pereira, Leticia Fernandes; Iquiapaza, Robert Aldo

doi:10.1590/1808-057x20231737.en

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Revista Contabilidade & Finanças

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Original Article • Rev. contab. finanç. 34 (92) • 2023 • https://doi.org/10.1590/1808-057x20231737.en copy

Fund management fees: the role of industry competition and investor sentiment

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

This article analyzes the influence of industry competition and investor sentiment on the likelihood of change in investment fund management fees in Brazil. Due to the wide variety of existing funds, with various characteristics and objectives, there may be significant differences in the fees observed. Thus, it is worth analyzing the factors that influence the amount of fund management fees charged, since the literature highlights that the payment of fees is related to fund performance. Also, it is observed that the Brazilian fund industry, despite having a large number of available funds, is still concentrated in few management firms, which is an indication that there is a low competition level. In practical terms, this investigation may be useful to investors in the fund selection process, since the management fee represents one of the main costs an investor faces when investing in this industry. The results point out the importance of adopting greater transparency in the disclosure of fees by financial institutions, since there are indications that the amounts charged are influenced by the characteristics of funds and investors. The methodology adopted involves Logit/Probit regression models, which had changes in the management fee as an explained variable and, as explanatory variables, the proxies of competition and investor sentiment, in addition to other control variables. It was observed that the investor sentiment proxy was significant in explaining the probability of change in management fees, mainly for setting higher fees. However, no statistical significance was observed for industry competition. This research innovates by analyzing the role of industry competition and investor sentiment on the probability of changing management fees, thus contributing to fill a gap found in the Brazilian national literature.

Keywords:
mutual funds; management fees; competition; investor sentiment; funds industry

Variable	Calculation	Bibliographic source	Database
Management fee (TxAdm)	Expressed as a percentage per semester (126 days) of shareholders' net assets.	CVM (2014Comissão de Valores Mobiliários. (2014). Instrução CVM n. 555, de 17 de dezembro de 2014, com as alterações introduzidas pelas Instruções CVM n. 563/1, 564/15 e 572/15. Dispõe sobre a constituição, a administração, o funcionamento e a divulgação de informações dos fundos de investimento. CVM.) Silva et al. (2018Silva, S. E., Roma, C. M. S., & Iquiapaza, R. A. (2018). A taxa de administração sinaliza o desempenho dos fundos de investimento em ações no Brasil? Revista de Educação e Pesquisa em Contabilidade , 12(3), 286-302.)	SI-ANBIMA 4.3.
Concentration Index (HHI)	${H H I}_{j, t} = - \sum_{i = 1}^{N_{j, t}} S_{i, j, t}^{2}$ where: S_i,j,t is the total net assets of the fund family i in the class j, in the period t, divided by the total net assets of all funds operating in the class j; N_j,t is the number of fund families in the class j in the period t.	Feldman et al. (2020Feldman, D., Saxena, K., & Xu, J. (2020). Is the active fund management industry concentrated enough? Journal of Financial Economics, 136(1), 23-43. https://doi.org/10.1016/j.jfineco.2019.08.009 https://doi.org/10.1016/j.jfineco.2019.0... ) Ferreira et al. (2019Ferreira, M. A., Keswani, A., Miguel, A. F., & Ramos, S. B. (2019). What determines fund performance persistence? International evidence. Financial Review, 54(4), 679-708.) Parida e Tang (2017Parida, S., & Tang, Z. (2017). Price competition in the mutual fund industry. Economic Modelling, 70, 29-39. https://doi.org/10.1016/j.econmod.2017.10.005 https://doi.org/10.1016/j.econmod.2017.1... )	Own estimation. Information on family size and fund classes taken from the system SI-ANBIMA 4.3.
Investor sentiment (SENT)	Building a proxy to capture investor sentiment, by performing an ACP of the following variables: NIPO, AD, PDIV, and PINDIV. The calculation methodology for each of them is shown in Section 3.3.2. Alternatively, investor sentiment was captured using the Consumer Confidence Index (CCI), as follows: ${S E N T}_{i, t} = l n ({C C I}_{i, t})$ where: CCI is the Consumer Confidence Index.	Lemmon (2006Lemmon, M. (2006). Consumer confidence and asset prices: Some empirical evidence. The Review of Financial Studies , 19(4), 1499-1529.) Marschner and Ceretta (2021Marschner, P. F.., & Ceretta, P. S. (2021). Sentimento do investidor, incerteza econômica e política monetária no Brasil. Revista Contabilidade & Finanças, 32(87), 528-540.) Miranda and Machado (2018Miranda, K. F., Machado, M. A. V., & Macedo, L. A. F. (2018). Investor sentiment and earnings management: Does analysts’ monitoring matter? Revista de Administração Mackenzie, 19(4), 1-29.) Schmeling (2009Schmeling, M. (2009). Investor sentiment and stock returns: Some international evidence. Journal of Economic Theory, 16, 394-408.)	Own estimation. Estimation information was collected from the databases Economatica, CVM, B3, and IPEADATA.
Performance (Alfa)	$r_{i, t} - r_{f, t} = α_{i} + b_{i} (r_{m, t} - r_{f, t}) + s i {S M B}_{t} + y i {H M L}_{t} + p_{i} {W M L}_{t} + ε_{i t}$ where: r_i,t - r_f,t is the excess return on the fund i, in the period t; r_m,t - r_f,t is the excess market return in the period t; α_i is the performance of the fund i in the period, given by the intercept of the regression; b_i , s_i , y_i , p_i are the beta coefficients of the regression over the period; SMB_t is the size factor; HML_t is the book-to-market factor; WML_t is the moment factor; ε_i,t is the error term.	Bu (2020Bu, Q. (2020b). Mutual fund alpha: Is It managerial or emotional ? Journal of Behavioral Finance, 22(1), 46-55. https://doi.org/10.1080/15427560.2020.1716361 https://doi.org/10.1080/15427560.2020.17... a) Fernandes et al. (2018Fernandes, A. R. D. J., Fonseca, S. E., & Iquiapaza, R. A. (2018). Performance measurement models and their influence on net fundraising of investment funds. Revista Contabilidade & Financas, 29(78), 435-451. https://doi.org/10.1590/1808-057x201805330 https://doi.org/10.1590/1808-057x2018053... ) Gil-Bazo and Ruiz-Verdú (2009Gil-Bazo, J., & Ruiz-Verdú, P. (2009). The relation between price and performance in the mutual fund industry. Journal of Finance, 64(5), 2153-2183.) Silva et al. (2020Silva, S. E., Roma, C. M. S., & Iquiapaza, R. A. (2020). Portfolio turnover and performance of equity investment funds in Brazil. Revista Contabilidade & Financas , 31(83), 332-347. https://www.scielo.br/j/rcf/a/XPkcBx6J4XKT5KyfCQxJnBb/?format=pdf⟨=en https://www.scielo.br/j/rcf/a/XPkcBx6J4X... ) Vidal et al. (2015Vidal, M., Vidal-García, J., Lean, H. H., & Uddin, G. S. (2015). The relation between fees and return predictability in the mutual fund industry. Economic Modelling, 47, 260-270.)	Own estimation.
Age (Ida)	Time, in semesters, since the opening of the fund.	-	SI-ANBIMA 4.3.
Size (Size)	${S i z e}_{i, t} = I n ({N A}_{i, t})$ where: Size_i,t is the size of the fund i, in the period t; NA_i,t is the net assets of the fund i, in the period t.	-	SI-ANBIMA 4.3.
Type (Type)	Dummy variable that takes the value 1, if the fund is open, and 0, otherwise.	-	SI-ANBIMA 4.3.
Manager (Man)	Dummy variable that takes the value 1, if there is a coincidence between the manager and the fund administrator, and 0, otherwise.	-	SI-ANBIMA 4.3.
Market Segmentation (MS)	Dummy variable that takes the value 1, if the fund is exclusive, and 0, otherwise.	-	SI-ANBIMA 4.3.
Risk Free (Rf)	Risk-free rate of return in Brazil, estimated by IDC returns.	-	Economatica.

	Manag. Fee (%per semester )	HHI	SENT ₁	SENT ₂	Alpha (% per semester)	Age (sem)	NA (R$ million)	Net Ret. (%per semester )
Stock Funds
Nr. obs.	7844	7844	7844	7844	7844	7844	7844	7844
Minimum	0.00	0.13	-2.76	4.47	-4.13	0.66	0.00	-32.31
Maximum	3.44	0.17	3.47	5.10	2.44	106.36	9542.12	18.85
1st Quartile	0.25	0.15	-1.01	4.61	-0.45	10.49	20.39	-2.32
3rd Quartile	1.14	0.16	0.23	4.85	0.73	19.81	190.53	4.17
Mean	0.80	0.16	-0.12	4.73	0.06	17.09	204.90	0.60
Median	0.80	0.16	-0.23	4.70	0.18	14.21	65.64	0.59
Stand. Dev.	0.62	0.01	1.45	0.16	1.06	10.92	465.10	6.75
Asymmetry	0.84	-0.61	1.04	0.69	-0.97	2.83	7.25	-1.31
Kurtosis	1.26	0.45	1.26	-0.14	1.98	11.43	80.73	5.81

	Increase				Decrease
	Probit		Logit		Probit		Logit
	Coef.	Sig	Coef.	Sig	Coef.	Sig	Coef.	Sig
Intercept	-5.9175	***	-12.3665	***	-4.4743	***	-9.2610	***
HHI	-0.2374		-0.9399		3.4090		7.6249
SENT ₁	0.0394		0.0798		0.0399		0.0918
SENT ₂	0.8252	***	1.8435	***	0.5232	**	1.1604	***
Alpha	0.0082		0.0218		0.0642		0.1501
Age	-0.0062		-0.0148		-0.0014		-0.0029
Size	0.0117		0.0246		-0.0322	**	-0.0704	**
Type	0.2230		0.4816		0.2354		0.5082
Manager	-0.2688	***	-0.5991	***	-0.2178	***	-0.4894	***
SM	0.1425	**	0.2795	**	0.1551	**	0.3440	***
Rf	3.5495		7.7321		19.0401		45.1944

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
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