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Mutual Funds’ Soft Dollar Arrangements: Determinants, Impact on Shareholder Wealth, and Relation to Governance

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Abstract

Mutual fund advisers either expense the cost of research and other services or pay for them with soft dollars. This study is the first to use actual soft dollar and total brokerage commission figures for a large number of funds and to examine how soft dollars are linked to mutual fund governance. Employing a survivorship bias-free sample of actively managed US mutual funds, we find that higher soft dollar and total brokerage commissions are associated with higher advisory fees but not with higher risk-adjusted fund returns. These findings suggest that mutual fund shareholders, on average, do not benefit from the research and the information supplied by third parties such as brokers. We also find that larger and more highly compensated boards are associated with lower advisory fees. Larger boards are also associated with slightly lower turnover. The median tenure of board directors is negatively correlated with soft dollar commissions and turnover, but not correlated with total brokerage commissions or the cost of turning over a portfolio. Higher proportions of directors with a finance background are associated with higher advisory fees, brokerage commissions, and turnover costs. These associations might indicate greater agency costs.

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Notes

  1. The Securities and Exchange Commission’s Report on mutual fund fees and expenses (2000) explains it as the absence of a widely accepted approach to measure spread costs. Including trade commissions in the expense ratio can be misleading if brokers charging higher commissions have better execution that results in lower spread costs.

  2. This is because, according to Horan and Johnsen (2008), an institutional broker typically provides a fund’s manager with credits up-front to pay a specific dollar amount of the manager’s research bill to independent vendors. In exchange, the manager promises to send the broker a specific amount of future trades at premium commission rates.

  3. Firms are rarely punished by regulators for abusing soft dollar practices. The most recent occurrence is an $813,000 fine imposed by the SEC on a New York-based firm Instinet on December 26, 2013 for inappropriate use of soft dollars (SEC 2013).

  4. A SEC ruling in December 2004 prohibited the use of commission bundling to pay for distribution expenditures. Our sample ends in 2003. Funds are still allowed to charge 12b-1 fees for distribution. The 12b-1 fee is part of a fund’s expense ratio but it is also reported separately.

  5. See Tufano and Sevick (1997), Vafeas (1999), Perry (2000), Ryan and Wiggins (2004).

  6. It is possible that the advisers who are more successful at using the services obtained through the soft dollar arrangements are more likely to disclose amounts of bundled commissions in addition to their existence. To determine whether the lack of uniform disclosure leads to selection bias, we conduct the Heckman sample selection bias test at the initial screening stage with 106 funds, 31 of which do not disclose the information. The test fails to reject the null of no selection bias and is robust to treating the funds that report zero soft dollar commissions as having no soft dollar arrangements. Including them into the sample under the assumption that they do not use soft dollar arrangements does not qualitatively affect the results.

  7. When we exclude convertible and balanced funds from the analyses, the results are qualitatively the same.

  8. Vanguard funds did not use soft dollars for research and other services during the sample period.

  9. The CRSP Mutual Fund Database tracked share classes but not funds before 2004. According to the 2013 Investment Company Institute Fact Book (2013), there were an average of 4471 actively managed equity funds per year from 1999 to 2003 (4966 including hybrid funds), with average net assets of $791 million ($788 million including hybrid funds). The average net assets per fund is $724 million in our sample.

  10. The advisory fee often has a “stacked” structure: e.g., the advisory fee may be 1 % for the first $10mln of assets under management, 0.75 % for the next $90mln in assets (between $10 million and $100 million), and 0.5 % for assets above $100mln. In such cases we compute the advisory fee based on the total net assets at the beginning of the year. In this example, if these assets were $200 million at the beginning of the year, the weighted advisory fee is (10mln*0.01 + 90mln*0.0075 + $100mln*0.005)/200mln, or 0.638 %.

  11. Excluding these 40 zero soft dollar fund-years from the sample does not change the results.

  12. Large fund families such as Fidelity are likely to appear more frequently in the sample set. However, because a fund’s family with a higher weight in the industry is more likely to influence the industry norms, this characteristic of a sample is representative of the whole population of actively managed equity mutual funds.

  13. Funds with high turnover also bear the market impact cost of transactions in addition to brokerage commissions. However, Berkowitz et al. (1988) argue that the market impact costs are small relative to commissions and conclude that there is no economic trade-off between the market impact costs and commissions. Chan and Lakonishok (1993) suggest no correlation between the market impact costs and brokerage commissions. Thus, following Livingston and O’Neal’s (1996), we do not control for the market impact cost.

  14. If a fund has multiple share classes, a weighted average monthly return is computed based on the weights of different share classes at the beginning of each month.

  15. We also ran the regression with the variable SoftPerTr i,t , defined as the log of the ratio of the dollar amount of transactions involving soft dollars to the soft dollar commissions – a control for the quality of information suggested by Brennan and Chordia (1993). A higher ratio might be suggestive of better information. This variables’ estimated coefficient is not significant, and its inclusion does not affect the results qualitatively. However, including it results in “losing” 104 funds that do not report the amount of transactions involving soft dollars. Accordingly, we do not use this variable.

  16. Including family fixed effects for all 70 families would dramatically reduce the regression’s power, especially given that we already use the objective and year fixed effects (some families are represented by one or very few funds in our sample). When we add dummy variables for the 11 most highly represented families (accounting for 191 funds, about a half of our sample), the results do not change notably. Therefore, we do not include family fixed effects in the final set of regressions.

  17. The normalized Herfindahl index characterizes the relative competitiveness in an investment objective to which the fund belongs compared to the case where net assets are equally distributed among all funds within the objective. We repeat the tests without normalizing the Herfindahl index; the results are qualitatively the same.

  18. To be classified as a director with a finance background, one either must have had a finance occupation in the past or is currently occupied in the finance industry (the latter group constitutes the majority of such directors). Since directors often sit on the boards of many funds offered by the same sponsor, the variable OtherDir only considers directorships outside of the fund’s sponsor (in our sample, all of them also happen to be outside of the mutual fund industry). The variable constructed in this manner captures the proportion of directors who do not depend only on one source of fees and potentially sends a signal about the board’s quality.

  19. Tufano and Sevick (1997) suggest measures of excess director compensation. When we use excess compensation (either per seat or per director, following Tufano and Sevick’s (1997) Equations 1 and 2 on p.338 in their paper) in place of unadjusted compensation, it is not significant in the regressions. Perhaps directors are concerned more about the potential loss of income from the fund’s sponsor (in case they oppose the fund’s policies and lose their seat) than how this income compares to the fees paid by other funds or sponsors.

  20. Decomposing alternative rent transfers into loads and 12b-1 fees does not affect the results.

  21. Because we use the lag of the log of FundSize in Eq. (1) to avoid a spurious correlation, the number of fund-years is reduced.

  22. The positive association between turnover and advisory fees is consistent with the findings of Deli (2002).

  23. Excluding the governance variables does not change the signs, magnitude, and significance of the remaining variables’ coefficients.

  24. In a recent study, Fricke (2014) reports that more highly compensated fund boards and boards with lower fund holdings are associated with lower turnover of underperforming funds’ managers, consistent with the agency costs explanation.

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Acknowledgments

We thank Melissa Frye, David Nanigian, Abhishek Varma, Drew Winters, and the anonymous referee for helpful comments. All remaining errors are ours.

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Authors and Affiliations

  1. Bahçeşehir University, İstanbul, Turkey

    Yaman Ö. Erzurumlu

  2. College of Business, Illinois State University, Normal, IL, 61790-5480, USA

    Vladimir Kotomin

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  1. Yaman Ö. Erzurumlu
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  2. Vladimir Kotomin
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Correspondence to Vladimir Kotomin.

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Erzurumlu, Y.Ö., Kotomin, V. Mutual Funds’ Soft Dollar Arrangements: Determinants, Impact on Shareholder Wealth, and Relation to Governance. J Financ Serv Res 50, 95–119 (2016). https://doi.org/10.1007/s10693-015-0222-1

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