Mutual Fund Performance, Management Teams, and Boards
John C. Adams, Takeshi Nishikawa, and Ramesh P. Rao
September 26, 2012
Abstract
This paper examines the performance of team-managed and single-managed funds in
the mutual funds. The recent surge in the use of team managed funds in the mutual
fund industry suggests that the benefits of team management are outweighing its costs.
However, most studies show that no superior returns are related to team managed
funds relative to single managed funds. Our analysis shows that not all teams are alike,
and therefore, for a team fund to be a better performer there needs to be a moderating
internal governance factor. We find that teams in funds with the highly independent
boards charge significantly less fees to their fund holders than those team-managed
funds with less independent directors.
Keywords: Mutual funds; board structure; organizational structure
JEL Classification: G20, G32, G34
John C. Adams is an Assistant Professor of Finance in the Department of Finance and Real
Estate, College of Business at the University of Texas at Arlington, Arlington, TX 76019.
Takeshi Nishikawa is an Assistant Professor of Finance at school of Business University of
Colorado, Denver CO 80202
Ramesh P. Rao is a Professor and Paul C. Wise Chair in Finance in the Department of Finance at
Oklahoma State University, Stillwater OK 74078
1
1. Introduction
Are two heads better than one? What about three or four? As an increasing number of
mutual funds have been structured as team-managed funds1, more practitioners and academics
alike have attempted to answer this question in relation to the performance of mutual funds in
the U.S. While there is still a paucity of studies that empirically examine the relation between
fund performance and fund management organizations, the emerging consensus seems to be
that team-managed funds tend to either underperform the single-managed funds (i.e., Chen,
Harrison, Ming, and Kubic (2004) and Bär, Kempf, and Ruenzi (2011)) or at best be no different
than single-managed counterparts (i.e., Prather and Middleton (2002) and Bliss, Potter, and
Schwarz (2008)).
The increasing popularity of team-managed funds is odd if indeed team-
managed structure does not enhance the performance of funds given the ever-increasing
importance of mutual funds as a financial intermediary.
As of 2010, about $11.8 trillion in assets were managed by various mutual funds for
nearly 25 million households with about 90 million investors in the U.S. (ICI, 2011). Echoing
this puzzle, Han, Noe, and Rebello (2008) show that there is a positive relation between
performance and team management once the selection bias where managers with lower
management ability are self-selected to a team management is controlled.
However, overall,
our understanding of the relation between fund performance and fund management
organizations is scant and limited.
The objective of this paper is to examine the relation
between fund performance and fund management organizations in the presence of the internal
governance mechanisms.
The mutual fund governance, particularly independent director requirement, has been
hotly debated among regulators, practitioners, and academics following the mutual fund
industry scandal of 2003-2004. In the wake of the scandals, in 2006 the SEC adopted a rule that
requires 75% of mutual fund directors be independent. However, following the lawsuit by the
U.S. Chamber of Commerce, the U.S. Court of Appeals for the District of Columbia faulted the
SEC for failing to provide little evidence supporting the required governance changes would
bring better and improved governance in the mutual fund industry. Recent academic evidence
For example, a The Wall Street Journal article by Eleanor Laise, “Your fund manager’s secrets,” report that as of
2006 about 65% of funds are team-managed funds based on Morningstar figures, up from 49% in 2000. The article
is available at http://online.wsj.com/article/SB116077809860592420.html. Our sample shows the similar number.
Please see Panel A of Table 2.
1
2
(i.e., Khorana, Tufano, and Wedge (2007) and Adams, Mansi, and Nishikawa (2010)) reports
empirical evidence that boards with higher proportion of independent directors are more
effective monitors, suggesting the SEC’s attempt to increase of independent director presence in
mutual fund boards might be beneficial. Indeed, the Investment Company Institute reports on
its website that “In nearly 90 percent of fund complexes, 75 percent or more of fund directors
are independent.”2
We hypothesize that the recent popularity of team-managed funds in the U.S. could be
related to the governance related benefits that this form of fund management organization
provides. We argue that the benefits of team management could potentially reduce the role of
the internal governance as the nature of the team management could be used as a supplement
to the internal governance mechanisms. In a corporate setting, Arena, Ferris, and Unlu (2011)
find that the presence of co-CEOships can serve as an alternative governance mechanism, with
co-CEO mutual monitoring substituting for board monitoring.
Because both corporate and
mutual fund boards have a fiduciary duty to protect the interests of shareholders, it is possible
that team-managed funds also provide alternative governance mechanisms in the mutual funds.
Sah and Stiglitz (1986 and 1988) suggest that in a team setting difference of opinions among
members are compromised which lead the team decisions to be less extreme than those of
individuals. The implication of Sah and Stiglitz’s argument for fund management is that team
would have an ability to diversify style and judgment (Sharpe (1981)). Consistent with Sah and
Stiglitz (1988), Bär et al. (2011) find evidence that team-managed funds follow less extreme
investment styles. Similarly, Han et al. (2008) report that the investment style of team-managed
funds is less eccentric than that of individually managed funds. Another potential benefit of
team management is that team setting would broaden the skills and knowledge which could
lead to better abilities to process more information (Hill (1982) and Herrenkohl (2004)).
Combining all the benefits of team management, we expect that the existence and benefits of
team management should be more pronounced in a fund where internal governance
mechanisms are relatively weak
While there are potential benefits, team management also has its own drawbacks. One
of the drawbacks of team management is the possible “moral hazard in teams” problem,
highlighted by Holmström (1982).
2
In team management where it is difficult to identify
See at their website http://www.ici.org/idc/policy/governance/overview_fund_gov_idc
3
individual members’ contributions to the success or failure of the team (Almazan, Brown,
Carlson, and Chapman (2004)), the potential remedies to reduce agency problems, such as the
labor market disciplines (Fama (1980)), optimal dynamic managerial contracts (Holmström
(1999)), and career concerns (Chevalier and Ellison (1999)), become less effective. Also, team
management could lead to delays in decision making (Sah and Stiglitz (1988)). Therefore, in a
sharp contrast to the potential benefits of team management where it could be used as a
supplement to governance mechanisms, these drawbacks of team management suggests that
there needs to be an existence of strong internal governance mechanisms for team management
to be successful. As such, we hypothesize that the existence and benefits of team-managed
funds are more prevalent with those funds that have strong internal governance mechanisms.
Employing a sample of 3,002 U.S. offered mutual fund from 99 investment companies
covering the period from 1999 to 2007, we examine the relation between fund performance and
fund management organizations in a framework that controls for endogeneity between fund
management structure and internal governance mechanisms. Our study starts with an analysis
of the relation between management structure and internal governance mechanisms. We find
that some internal governance mechanisms are important factors to influence the choice of fund
management structure even after controlling for the percent of team funds in an investment
company, suggesting that there is a potential effect of endogenous choice between team and
single-management (i.e., Han, et al (2008)). We also find that larger funds and younger funds
tend to be more team managed.
Next, we examine the relation between fund performance and fund management
organizations while carefully controlling for an effect of endogenous choice between team and
single-management. We use three different measures to capture fund performance: Carhart
four-factor alpha, expense ratio, and managerial performance measure of Carhart four-factor
alpha plus expense ratio (Elton, Gruber, and Busse (2004)). Overall, our results from the OLS
regressions show that regardless of the performance measures we use, there is no evidence that
team-managed funds either outperform or underperform the single-managed counterparts.
However, more interesting results emerge when we interact the team dummy with internal
governance measures. When Carhart four-factor alpha is employed as a performance measure,
the team-managed funds with higher proportion of independent directors perform significantly
better than those team-managed funds with less independent director representation.
4
In
contrast, the effect of board size to fund organizations show that the performance of teammanaged funds with large boards is significantly worse than those team-managed funds with
fewer board members.
These results from the analysis of Carhart four-factor alpha show that performance of
team-managed funds is highly influenced by the presence of internal governance mechanisms.
Specifically, higher proportion of independent directors, believed to result in
better
monitoring,leads to better performance of team-managed funds, while larger boards, believed
to be less effective monitoring (i.e., Yermack (1996)), results in worse performance of teammanaged funds, suggesting that the drawbacks of team management dominates the benefits in
the U.S. mutual fund industry.
When we use the expense ratio of the funds to measure the performance of the funds,
we find that expense ratios of team-managed funds with larger boards are significantly higher
than those team-managed funds with smaller boards. However, we do not see any significant
difference between team-managed funds with respect to the proportion of independent
directors.
While Carhart four-factor alpha and expense ratio measure the performance of
mutual fund for investors, the performance of fund manager is pre-expensed base. Thus, we
add expense ratio back to alpha to measure the true value of the managerial performance
following Elton, et al. (2004). The OLS regression results using Carhart four-factor alpha plus
expense ratio as a dependent variable show that unlike the other two performance measures
team-managed funds with either high proportion of independent directors or large board size
perform significantly better than those team funds with either less proportion of independent
directors or smaller board. However, from the earlier OLS regression results, it is shown that
the reason why team-funds with higher independent directors have better managerial ability is
due to the superior risk-adjusted return, measured by Carhart four-factor alpha, while for teamfunds with large boards are due mainly to the higher expense ratio. Given the fact that the
fiduciary duty of the boards is to protect interests of shareholders, we can conclude that teamfunds perform better when there is a higher proportion of independent directors. These results
are consistent with overall governance related findings with corporate settings.
Finally, we test the robustness of our findings. Specifically, we delete any funds that
experienced changes in organizational forms. In other words, we rerun the probit and OLS
models with the samples that did not change their management organizations within the last 12
5
months. Using these samples, we find the same results as our overall results, suggesting that
our results are not influenced by the changes in the management organizations.
This study contributes to the literature in two different ways. First, to the best of our
knowledge this is the first empirical evidence that provides a link between fund performance
and fund management organizations in the presence of internal governance mechanisms.
Because existing literature suggests that team management can be either beneficial as an
alternative governance mechanism or detrimental unless with proper governance mechanisms,
the influence of internal governance is critical when the performance of team management is
examined.
Second, this paper sheds light on the effectiveness of independent director in
governing mutual funds. Given the dramatic increase in team-managed funds, our results
show the increasing importance of independent directors.
Our paper is organized as follows: Section 2 describes the data and methodology. Section 3
presents the empirical results. Finally, Section 4 concludes.
2. Data and Variables Measures
2.1 The Sample
We use several databases to build our sample. We obtain mutual fund returns, total net
assets, expense ratios, 12b-1 fees, management fees, fund age, institutional ownership data, load
s, and other fund characteristics from the Morningstar Direct mutual fund database. We hand
collect end of year board of director information from the Statement of Additional Information
(SAI), which is located in each fund’s prospectus (e.g. Form 485a). We also record from each
fund’s Form 485a filing whether the investment company that sponsors the fund is a publicly
traded corporation or a subsidiary of a publicly traded corporation.
We cross check this
sponsor level ownership structure against the Dun and Bradstreet, Hoover, and CRSP
databases. Since most funds offer multiple share classes of the same underlying portfolio in
order to accommodate the preferences of varying investor clienteles regarding fees, sales
charges, and account sizes, we compute the fund level value weighted average of each share
class level variable.
We next sum the total net assets of each fund to obtain the size of the assets under
management of each sponsor and include the 55 largest in our sample. We avoid a large
sponsor bias by including data for small and medium sized investment companies. We then
6
focus on actively managed funds by excluding index and exchange traded funds. The resulting
sample contains funds from 99 investment companies over the years 1999 to 2007.
2.2 Team vs. Single Managed funds
The Morningstar database reports the identity of fund managers. For funds with
individual or single managers, Morningstar reports their full names. When funds are managed
by more than one individual, Morningstar often only provides the last names of managers with
the longest tenured or lead managed listed first.
In some instances, Morningstar uses
“Management team,” “multiple managers,” and prior to 2001 the name of the lead manager
followed by “et. al”. In these cases, we classify a fund as single-managed when only one
manager name is given in the database whereas multiple names or anonymous reporting of
“Management team” or “Multiple managers” are classified as team-managed funds.3 However,
following the SEC’s 2004 release of Disclosure Regarding Portfolio Managers of Registered
Management Investment Companies, 17 CFR Parts 239, 249, 270, and 274, Release No. 33-8458; 3450227; IC-26533; File No. S7-12-04 funds are obliged to disclose the identities of all team
members. In our sample, the instances of Morningstar reporting anonymous team have become
increasing less frequent and disappeared in the years following the SEC’s disclosure
requirement.
2.3 Board Characteristics
We follow Tufano and Sevick (1997) and focus our analysis on board structure and
composition (e.g. board size and independence). We collect calendar year end board structure
data from the statement of additional information (SAI), which is included in each fund’s
prospectus (Form 485). The SAI lists all directors and details how a director is affiliated with
the fund sponsor and if a particular director serves as the board chairperson. We compute
Board Size as the natural logarithm of the number of trustees serving on each board as our
measure of board size.
We use the definition of director independence in SEC (2004)
regulations and compute Independent Directors as the ratio of independent (also known as
Massa, et al. (2010) argue that named managers exert more effort than anonymous ones. In
unreported analysis we eliminate anonymously managed funds and find similar results.
3
7
disinterested) trustees to the total number of directors. SEC regulations classify as independent
those directors who are not employees, not employee family members, not employees or 5% or
more shareholders of a registered broker-dealer, and are not affiliated with any recent legal
counsel to the fund. Independent Chair is determined using manual collection based on Form 485
to ascertain whether the board has a chairperson who is an independent director. Finally, we
gather information if a single board oversees all of the funds of the sponsor (Unitary Board
Structure) and designate a dummy variable that takes on a value of one if it is a unitary board
and otherwise zero.
2.4 Performance Variables
This study employs three fund performance measures. The first measure is each fund’s riskadjusted return using Carhart (1997) four factor model’s alpha. Computed as
( Ri ,t  R f ,t )   i  1 ( RMRF t )   2 ( SMBt )   3 ( HMLt )   4 ( PR1YRt )  ei ,t
,
(1)
where Ri is the mutual fund return net of expenses, RMRFt is the excess return on the CRSP
value-weighted aggregate market proxy, Rf, is the 30-day T-bill return, SMBt (small minus big) is
size factor that captures the stock return performance of small firms relative to large firms,
HMLt (high minus low) is the relative return of value and growth stocks, and PR1YRt is a
momentum factor computed as the difference in returns of prior year high and low return
portfolios. We use the Kenneth French data base to acquire values for each of the factors.
Similar to Bliss et al. (2008) and Almazan et al. (2004) the alpha measure for each fund is
computed each year using monthly data.
Second, we use the expense ratio of the fund as a way to capture fund performance.
Although the risk-adjusted return is important for mutual fund investors, mutual fund
investors can enhance their returns by focusing on mutual funds with lower expense ratios
within given fund objectives. The extant literature shows a negative relation between fund
returns and expense ratios (i.e., Blake, Elton, and Gruber, 1993); Malhotra and MacLeod, 1997;
Wermers, 2000). More importantly, the fee negotiations are a primary role that mutual fund
directors, particularly independent directors, undertake to protect mutual fund investors’
interests. As such, mutual fund directors could have direct influence on the fund expense,
8
while they are less capable of controlling the fund returns (Kong and Tang, 2008). Adams et al.
(2010) report that independent directors are associated with lower expense ratios.
Third, we follow Elton et al (2004) and add back each fund’s expense ratio to its four factor
alpha to capture managerial performance. Cash policies and portfolio trading activities incur
costs to the fund that negatively impact the fund returns so even if there were no expenses
returns among funds could vary considerably. Also, expense ratios are negotiated annually by
fund sponsors and mutual fund boards so fund managers have little input on fee levels.
Likewise, the custodian and distribution policies are likely set by the sponsor and not the fund
manager.
Bär et al. (2011) report that team managed funds follow less extreme investment
strategies and are less likely to achieve extreme performance outcomes. Likewise, Han et al.
(2008) find evidence to support their claim that team managed funds follow generic trading
strategies that result in higher average returns but also make returns less informative of
managerial performance. If behave differently than individuals and team-managed funds show
different risk-taking and trading activities it is critical to examine the managerial performance
of team versus single funds. A brief description of the sample variables and the data sources
used, to obtain or compute them, is presented in Table 1.
[Insert Table 1 About Here]
2.5 Descriptive Statistics
Our final sample consists of 3,002 U.S. domiciled mutual funds sponsored by 99 investment
companies and covers the period from 1999 to 2007. Table 2 reports the distribution of singlemanaged and team-managed funds in our sample. Panel A shows the distribution of fund
management structures for each year. In the earlier years of the sample, more funds utilized a
single-manager structure. Beginning in 2001 and continuing for the remaining years in the
sample, the majority of funds, about 53%, favored a team-management structure. The number
of funds employing management teams increases in most years and from 1999 through 2007 the
proportion of team-managed funds increases by about 31%.
This trend is consistent with
earlier studies that report growing popularity of team-managed funds (i.e., Bliss et. al., 2008;
Han et al., 2008). This value is similar to Morningstar’s estimate quoted in a recent Wall Street
9
Journal article.4 This similarity in the proportions of team-managed funds suggests that our
sample reflects patterns in fund management structures across the universe of mutual funds.
[Insert Panels A and B of Table 2 About Here]
Panel B of Table 2 reports the incidence of single and team managed funds by investment
objective. It is notable that funds with less complex investment objectives, such as sector and
municipal bond funds, are more likely than the average fund to utilize a single-manager. In
contrast, funds with more complex investment objectives (i.e. aggressive growth, balanced, and
total return funds) tend to be team-managed. In general, the distribution of single versus team
managed funds seems to indicate that team management is more prevalent in investment
objectives that can be characterized as complicated and disparate, while funds that follow a
more focused investment strategy tend to be managed by individuals. In this respect, our
sample is similar to the one employed by Bliss et al. (2008).
Panel C of Table 2 provides summary statistics for fund and family, performance, and board
of director characteristics segmented by fund management type. In addition, Panel C reports
the results for tests of differences in the mean and median values for each variable across the
single and team managed subsamples. Single managed funds are sponsored by sponsors with
more assets under management than the sponsors of team managed funds. Panel C reports
mean and median Family level TNA values are economically and statistically greater in single
managed funds (mean value of around $175 billion) than in team managed funds (mean of
about $83 billion). The large difference in the mean and median vales reflects the nature of the
mutual fund marketplace which features a few very large fund families. This skewness is also
reflected in the number of funds offered by fund families, especially for single managed funds
where the mean number of funds offered is about 80 and the median value is 58. Of course,
interpreting family level data is problematic since many families utilize both fund management
structures, some families do not sponsor any team-managed funds, while others offer only
team-managed funds.5
4
Please see footnote 1.
American funds and Cox & Dodge are some of the examples that have been using team-managed funds
extensively. Janus and Fidelity have adopted team management style more recently. See the following article from
U.K. Reuters: http://uk.reuters.com/article/2007/10/25/fidelity-mutualfunds-idUKN2522199020071025
5
10
[Insert Panels C & D of Table 3 About Here]
Consistent with the notion that bigger funds require more managerial resources, Panel C
reports that team-managed funds are, on average, larger with mean and median TNA values of
approximately $1.6 billion and $0.38 billion, respectively. These values are economically and
statistically greater than the TNA of single-managed funds. Also, team-managed fund families
offer more share classes than single-managed families suggesting their marketing and operating
policies are more complex than those of single managed funds.6 Consistent with the results
presented in Panel A that team managed funds are more prevalent in later years, team managed
funds tend to be younger than single managed funds. Average and median fund ages are
higher for the single-managed funds than for team-managed funds, suggesting recently offered
funds tend to be team-managed (i.e., Bliss et al. (2008) and Massa et al. (2010)).
In terms of trading activities, mean turnover ratio is greater for single-managed funds,
but the median value is higher for team-managed funds. However, team-managed funds tend
to hold more stocks and less cash than single-managed funds. Single-managed funds offer
significantly fewer share classes, lower front and rear loads (sales charges), and lower
institutional ownership. Overall, the univariate statistics in Panel C suggest that single and
team managed funds differ in terms of their clienteles and that clientele effects are important
factors in deciding fund management type. This finding is supported by anecdotal evidence
that some investors prefer certain fund management structures. For example, it has been
reported that Janus started to employ teams in response to institutional investors’ demands.7
Panel C also summarizes the performance metrics employed in this study. Consistent
with Elton et al. (2004), the mean and median Carhart four factor alphas (Alpha) of the sample
funds are negative. Panel C also indicates there are no significant differences in the mean and
median alphas of single and team managed funds. The mean and median expense ratios are
about 3 and 5 basis points lower for single-managed funds, differences that are significant at the
one percent level.
However, our measure of fund manager performance, alpha plus expense
ratio, is similar for single and team-managed funds. Overall, the performance characteristics in
6
We use the terms single and team managed families to indicate to families of funds offering each management
structure and acknowledge that many families offer both single and team managed funds.
7
See the link provided for an article in footnote 5
11
Panel C do not suggest meaningful differences in performance between single-managed and
team-managed funds.
Finally, Panel C reports distributional statistics for funds’ boards of directors. Panel C
reports that boards of team managed funds are smaller, more independent, and more often
oversee all of the funds within the family complex (Unitary), results that are statistically
significant at the one and five percent levels. However, in terms of economic significance the
differences appear small. For example, the differences in the median values for all of the board
characteristics are zero and the differences in the board size and independent director means
are negligible.
Panel D of Table 2 reports Pearson correlations for our key variables of interest.
Consistent with the univariate statistics there is no significant correlation between team
management and fund performance, measured by alpha or alpha plus expenses. However,
team management is a positive and significant correlation with expense ratio, fund TNA,
independent director proportion, and unitary board presence. In contrast, family TNA, the
number of funds offered in the family, board size, and independent chair are negatively and
significantly correlated with team management. Consistent with earlier studies (i.e., Adams et
al. (2010), Elton et al. (2004)), the Carhart four factor alpha is significantly and negatively
correlated with fund’s expense ratio. Overall, there is a significant variation in the fund, family,
and board characteristics between team and single funds.
3.
Multivariate Analysis
We provide multivariate OLS regression analysis to examine the relation between fund
management structure, board governance, and performance while controlling for fund
characteristics.
To test which effect, substitution or free rider, dominates we apply the
following specification while using fund level clustered standard errors
4
Performancei,t = 0 +  βj (Board Characterisiticsi,t ) +  βj(Fund Characteristicsi,t )
j 1
j 5
10
11
22
j 11
j 13
+  βj (Public,t )+ β12 (Investment Objectivei,t )+  βj (Timet ) + i,t,
12
(1)
where Performance is either the annualized Carhart four factor alpha (Alpha) computed over the
preceding twelve months, the annual expense ratio (Expense) , or the sum of each fund’s alpha
and expense ratio (Alpha + Expense). Board Characteristics include board size, independent
directors, independent chair dummy, and unitary board dummy.8
Fund Characteristics
include fund TNA, fund age, cash holdings, stock holdings, portfolio turnover, and institutional
ownership. Public is a dummy that takes on a value of 1 if the fund sponsor is publicly traded.
The variables Investment Objective and Time represent control dummies for each fund’s
benchmark investment objective category (e.g., growth and income, aggressive growth,
international equity, etc.) and time dummies, respectively.
3.1 Single and Team-Managed Sub-Sample Analysis
Table 3 presents results from regressing each of the fund performance measures (Alpha,
Expenses, and Alpha + Expenses) on board and fund characteristics for sub-samples of single
and team-managed funds in Panel A while Panel B reports Chow tests for differences in
selected estimated coefficients. Models 1, 3, and 5 report regression coefficients for singlemanaged funds while Models 2, 4, and 6 report results for team-managed funds.
The
dependent variables are alpha (Models 1 and 2), expense ratios (Models 3 and 4), and manager
performance, measured as alpha plus expense ratios (Models 5 and 6).
Model 1 reports the estimated coefficient for Fund TNA in the single-manager sample is
positive and statistically significant at the one percent level. Model 2 reports similar results
Fund TNA in the team-managed sample. Models 3 and 4 report that Fund TNA is negatively
related to fund expense ratios, while Models 5 and 6 report that Fund TNA is positively and
significantly related to gross expense ratios (Alpha + Expenses).
Institutional ownership
estimated coefficients are negative and significant for expenses (Models 3 and 4). In terms of
portfolio characteristics, Table 3 reports that cash holdings are positively related to performance
In unreported analysis we construct a composite board structure variable. This assigns values of one when a fund’s
board is smaller or more independent than the sample means. These values are then added to the independent chair
and unitary board dummy to create a board composite measure that ranges in magnitude from one to four. The
results from these alternative specifications are similar to those reported.
8
13
in team-managed funds only (Models 2 and 6) while stock holdings are negatively related to
performance for single-managed funds (Models 1 and 5).
Table 3 also reports that board size is negatively and significantly related to performance
for team-managed funds (Models 2, 4, and 6) but insignificantly related to performance for
single-managed funds (Models 1,3, and 5). Independent directors are negatively related to
performance for single managed funds in Models 1 and 5 and positively related to performance
in team managed funds in Models 2 and 6.
Interestingly, the estimated coefficients for
independent directors are positive and statistically significant (at the one percent level) for both
single and team-managed funds in the expense ratio specification (Models 3 and 4). These
results differ from Adams, Mansi, and Nishikawa (2010) who report a negative relation between
board independence and expenses, however they employ a sample of index mutual funds while
we are concerned with actively managed funds. Furthermore, the economic impact of board
independence on expenses in our sample of actively managed appears small.
The remaining
governance variables, Independent Chair, Unitary Board, and Public sponsor ownership, are
generally significant for expenses only and have similar signs and significance levels in single
and team-managed funds.
Panel D lists the results from Chow tests of differences in the estimated coefficients
(team – single) for each performance measure. Panel D reports the estimated coefficients for
board size and independence are significantly larger for alpha and alpha plus expenses (e.g.,
Model 2 vs Model 1 and Model 6 vs Model 5 in Panel A). The tests also indicate significant
differences in the independent chair and unitary board coefficients for the expense ratio
specifications (Models 3 and 4 in Panel A). Overall, the results presented in Table 3 are more
consistent with boards acting to mitigate problems associated free rider problems inherent in
team-managed funds (i.e., the free rider hypothesis) than the hypothesis that management
teams are substitutes for board governance (i.e., the substitution hypothesis). Of course, both
effects could be present and free rider effects dominate substitution effects.
3.2 Self Selection, Teams and Boards of Directors
Table 3 provides compelling evidence that the impact of board structure on fund
performance varies significantly across single and team-managed funds. However, selection
14
bias is a concern as managers may self-select single or team management structures. For
example, better managers (those whose expected performance is high) have career incentives to
favor single-managed funds so controlling for self-selection is critical. We control for these
issues by employing Heckman (1979) selection correction and instrumental variable
approaches.
We implement the Heckman selection correction by first modeling team management
using fund, family, and governance characteristics. Fund characteristics are the natural log
fund TNA under the premise that as fund size increases so does the requirement for managerial
resources and the natural log of fund age as Bliss et al. (2008) and Massa et al. (2010) argue that
younger funds tend to be structured as teams. Our models also include the number of share
classes offered by a fund and the proportion of institutional ownership to capture clientele
effects, cash and stock holdings as well as portfolio turnover to account for differences between
single-managed and team-managed funds (i.e., Bär et al., 2011).
For completeness, our
Heckman correction models also include front load and deferred load dummies as in (Almazan,
et al., 2004).
Family characteristics include two variables; the percentage of team-funds in a family
and the number of funds offered in a family. Unreported analysis indicates that the choice of
single vs team-management type reflects policy decisions at the family level.
Anecdotal
evidence supports this finding. For example, American Funds and Cox & Dodge are reportedly
strongly advocates of team management structures.9 The number of funds offered in a family is
included to capture the potential peer monitoring effect in Almazan et al. (2004) that occurs on
large fund families.
Increased peer monitoring suggests that there is less incentive for larger
fund families to employ team management structures.10,11
The governance variables are the natural log of board size, the proportion of
independent directors, a unitary board dummy, independent chair dummy, and a dummy for
publicly-sponsored funds. We also include fund-objective and year fixed effects. We then
Need a article cite here for the dodge and cox and American funds sentence……
Indeed, Massa et al. (2010) argues that the fund family uses team management as an effort to avoid falling victims
to “star” who leave the fund.
11
Because of very high correlation between log of family TNA and the number of funds offered in a family,
following Han et al. (2008), we use the number of funds in a family in the model. We also use log of family TNA
instead of the number of funds offered in a fund family. The results do not change.
9
10
15
calculate the inverse Mill’s ratio (Lambda) for each fund and include it in regression models to
control for self-selection effects.
3.2 Empirical results
The results from OLS regression analyses employing the Heckman approach are
presented in Table 4 which includes three panels to separately report the results for each of the
three performance measures. Panels A, B, and C report regression results when Carhart’s four
factor alpha (Alpha), expense ratio (Expense Ratio), and the sum of alpha and expense ratio
(Alpha + Expense) are the dependent variables, respectively. Model 1 of each panel is the base
model while Models 2 through 5 interact the team dummy with board size, the percentage of
independent directors, the independent chair dummy, and the unitary board dummy. In all
models, the inverse Mill’s ratio (Lamba) is significant, suggesting that the consideration of selfselection bias is important.
Panel A of Table 4 reports estimated coefficients when alpha is the dependent variable.
Model 1 reports that the team managed dummy is not significantly related to alpha. This result
is consistent with Bliss et al. (2008) and Prather and Middleton (2002). Our results show that
overall fund performance is not significantly related to the governance issues (i.e., Kong and
Tang (2008)). Model 1 also reports positive and statistically significant (at the one percent level)
results for Fund TNA suggesting economies of scale benefits. Alternatively, larger funds may
employ managers with superior security selection skills. Fund Age is negatively related to
alpha, results that are consistent with Evans (2010) who notes new funds are often incubated in
that they not offered for sale until they are successful.
The estimated coefficient for
institutional ownership is positive and significant (at the five percent level) suggesting that
institutional investors provide monitoring that improves performance and/or institutional
investors are performance sensitive and seek better performing funds. Cash holdings and stock
holdings also significantly affect fund performance. Consistent with Khorana (2001), larger
turnover by funds leads to underperformance, suggesting managers of underperforming funds
tend to trade excessively.
None of the governance estimated coefficients are statistically
significant suggesting that on average select optimal governance schemes.
16
More interesting findings are presented Models 2 through 5 that include interactions of
governance measures and the team management dummy. The estimated coefficients for the
fund characteristics Models 2 though 5 have similar signs and significance to those reported in
Model 1. Model 2 notes that the board size and team management dummy interaction term is
negative and significant (at the five percent level), results that are consistent with those reported
in Table 3. This finding indicates that smaller boards are associated with superior performance
in team managed, but not single managed funds. The estimated coefficient for the independent
director – team managed dummy is positive and significant in Model 3, suggesting that more
independent boards are associated with better performance in team managed funds but not in
single managed funds.
The remaining governance measure interactions with team
management, independent chair dummy and unitary board dummy, are not significantly
related to alpha. Overall, the results in Panel A suggest that board factors commonly associated
with improved monitoring (e.g. smaller and more independent boards) appear to be effective in
team managed funds where free rider problems can be severe.
Panel B of Table 4 summarizes the results using expense ratios as the performance
measure. The mutual fund investors can enhance their returns by lowering expense of the
funds.
Since the primary role of fund boards is to negotiate the fees with investment
companies, the expense ratio is an important operational performance measure.
Model 1
reports that while the team dummy is negative, it is not significant, indicating that the teammanaged funds do not charge less fees than single-managed funds.
The governance
characteristics are all significantly related to expense ratios. Interestingly, Model 1 reports a
positive relation between board independence and fund expense ratios (significant at the one
percent level), results that differ from Adams et al (2010) who document an inverse relation
between independent directors and expense ratios. However, our study focuses on actively
managed funds while they examine passively managed funds.
In addition, although the
estimated coefficient on independent directors is positive and statistically significant it is
economically very small.
Model 2 reports the interaction term between board size and team management is
positive and statistically significant at the one percent level. The board size –team management
coefficient is economically significant as well with a one standard deviation in board size
resulting in a 19 basis point increase in fees for team managed funds. This is in line with the
17
notion that bigger boards are less effective monitors (i.e., Yermack, 1996), and evidence that
team-managed funds’ performance is critically impacted by governance structure. In contrast
to Panel A, the interaction term between independent directors and teams is insignificant on
Model 3. Also unlike Panel A, the independent chair and team interaction term is positive and
significant.
Finally, following Elton et al. (2004), we examine the fund management skill by adding
back the expense ratio to the Carhart four factor alpha (Alpha) for each fund in Panel C of Table
4. In general, the signs and significance levels are similar to those reported for alpha in Panel A.
For example, Model 1 reports that the team managed dummy coefficient is insignificant. Model
2 shows the interaction term between board size and team management status in negative and
significant at the 10 percent level.
Model 3 reports a positive and significant estimated
coefficient on the director independence and team management dummy interaction term.
Overall, our findings in Tables 3 and 4 show significant influence of board governance
mechanisms on performance in team-managed but not single-managed funds. The free rider
hypothesis predicts that strong governance mechanisms are necessary to alleviate potential free
rider problems among fund management team members. The substitution hypothesis argues
that team members serve to moderate extreme investment decisions and enhance managerial
skills so that effective board governance in single but not team-managed funds. Our findings,
that small and independent boards are positively associated with performance in team but not
single-managed funds, are more consistent with the free rider hypothesis than the substitution
hypothesis.
Of course, both effects could be present and potential free rider problems in team-
managed funds outweigh any substitution in governance benefits they provide. Given the
trend in recent years towards more team managed-funds our examination highlights the
importance of boards in protecting the interests of the mutual fund investors.
3.3 Robustness Checks
Our results from the previous section show the importance of internal governance on
team-managed funds’ performance. However, it is possible our findings are driven by the
changes in the management organization through time. For example, sponsors commonly use
management teams to mentor new managers prior to planned departures of senior managers.
18
This practice results in some funds temporarily changing management structure (e.g. single
managed funds become team managed during a mentoring period). To make sure our findings
are not driven by fund organizational changes, we exclude funds that change management style
in the preceding year.12
Table 5 employs the restricted sample to repeat the analysis presented in Panel C of
Table 4.
The sample is reduced by almost 3,000 fund-year observations, suggesting that
changes in management structure are common in the mutual fund industry. Unlike Panel C of
Table 4, the interaction term between board size and team management structure is not
statistically significant. However, the estimated coefficient on the independent director and
team management interaction term is positive and statistically significant at the one percent
level. Furthermore, this finding is consistent with the results presents with the unrestricted
sample in Table 4. Although not reported, we repeat the specifications in Panels A and B of
Table 4 (e.g. employing alpha and the expense ratios as separate dependent variables) and find
similar results. Overall, the results presented in Table 5 suggest that frequent changes in
management structure are not driving our results.
Our analysis suggests the choice of board composition and structure causes returns in
team managed funds to be relatively high or low. It is also possible that causality runs in the
other direction, that prior performance leads funds to adopt certain governance structures (see
e.g. Hermalin and Weisbach, 2003).13 The level of monitoring effort exerted by individual
directors and the propensity of both fund sponsors and directors to actively promote
shareholder interests are important but unobservable determinates of mutual fund returns. If
board structure is correlated with these unobservable factors the board size and independence
variables are endogenous. In addition to employing year fixed effects, in Table 6 we employ a
two stage least squares approach and use the percentage of a sponsor’s funds that are team
managed as an exogenous first stage instrument.
The percentage of sponsor funds that are
team managed is a plausible instrument since it satisfies both the relevance (e.g., the decision to
employ teams is typically made by the sponsor) and the untestable exclusion (only influences
returns via its effect on the likelihood of a fund to be single or team managed) conditions.
12
We also consider two-year restriction. Though not reported, using the funds that do not change management
structure in the prior two year period, we find the same results.
13
However, mutual fund boards typically oversee multiple funds (a single board oversees all of the funds within an
investment trust and many investment companies sponsor multiple trusts) making it unlikely that the performance of
individual funds causes changes in board structure.
19
Table 6 repeats the analysis presented in Panel C of Table 4. The estimated coefficient on the
board size and team management structure interaction term is negative and statistically
significant at the ten percent level. This finding is similar to Panel C of Table 4 and favors the
hypotheses that free rider problems are more problematic in teams where board myopia is more
likely (e.g. with larger boards). Table 6 also reports that the impact of independent directors on
fund performance is more pronounced in team managed funds (the independent
directors/team management interaction term is positive and statistically significant at the one
percent level). Alternatively, team managed funds benefits more from independent director
monitoring than do single managed funds. Either interpretation favors the free rider over the
substitution hypothesis.
Unlike Table 4, the estimated coefficient on the independent director
and team interaction term is negative and statistically significant at the five percent level.
However, the results suggest an economically small effect.
Finally, as an alternative approach to examine the effect of fund governance characteristics
and team management structures on fund performance, in the spirit of Gompers, Ishii, and
Metrick (2003) we create an index score for the governance strength of each fund. First, a value
of 1 is assigned to a fund whose board has greater independent director representation than the
overall median or otherwise 0. Second, a value of 1 is assigned to fund whose board size is
smaller than the overall median value, or otherwise 0. The third value is the indicator variable
used to capture the presence of an independent chair, while the fourth and the last measure is
the indicator variable used to capture the presence of a unitary board. We sum these indicator
variables to create an index that has the maximum number of 4 and the minimum of 0, whereas
the 4 being the strongest hypothesized governance measure and 0 being the weakest. Using
this index, we rerun the Heckman’s approach, and report the second stage OLS model in Table
7. The results are consistent with the evidence from our primary specifications.
4.
Conclusion
The mutual fund industry has witnessed an increasing popularity of team managed
funds in recent years. While the benefits of team management have been recognized, there also
have been potential drawbacks related to team management. Indeed, much of the finance
literature examined the performance of team managed funds has failed to reveal relative
outperformance of team managed funds over single managed funds. If there is no apparent
20
superior performance, why has the mutual fund been experiencing this trend in shifting to
more team managed funds? This paper sheds some light on this apparent puzzle why there has
been an increasing trend in the use of team management in mutual fund management, while no
superior performance is recognized for this type of management.
Using the funds offered by 99 largest fund families for the period from 1999 to 2007, we
test the performance of team managed funds with single managed funds. The results are
similar to the earlier studies that there is no significant difference in performance between these
two organizational forms. However, when we control for potential governance moderating
factors in our models, we find evidence that is more consistent with the notion that the
drawback of the team management (e.g., free-rider problem) dominates the benefit of team
management. This means that rather than being a potential governance mechanism, the team
management could pose a problem on its performance, measured by the alpha and expenses in
our study, suggesting that not all team managed funds are alike.
Our results show that the
team managed funds with highly independent boards have significantly lower expense than
team-managed funds with less independent boards.
Our results are robust to alternate
specifications of governance measures.
Our finding complements a growing literature that examines the performance of team
management in organizations through its benefits and drawbacks. Although there has been an
increasing number of research exploring the team phenomenon, few have succeeded to provide
a direct analysis of teams because “team” can be defined loosely in the literature. Unlike these
earlier studies, we use team more firmly by using the mutual fund teams, thus our results are
cleaner. However, we acknowledge that there needs to be more research to enhance our
understanding of team management.
21
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24
Table 1
Variable definitions and primary source*
Variable
Data Source
Explanation
Managerial Organization
Team Managed
Morningstar
Dummy that equals one if the fund has more than one manager
Performance and Risk
Carhart 4 Factor Alpha
Expense Ratio
Morningstar/CRSP
Morningstar/CRSP
Alpha plus expense
Morningstar/CRSP
Computed using 1 year of monthly data. See Carhart (1997) for details.
Percentage of assets used to pay for operating expenses, including 12b-1 fees, management
and administrative fees, and other asset-based costs incurred except for sales charges.
Carhart 4 factor alpha plus expense ratio
Fund & Family Characteristics
Fund and Family TNA
Fund Age
Front Load
Rear Load
Morningstar/CRSP
Institutional Holding
Portfolio Turnover
Morningstar/CRSP
Morningstar/CRSP
Funds in a Family
Percentage of Team
Stock Holdings
Cash Holdings
Classes in a Fund
Morningstar/CRSP
Morningstar/CRSP
Morningstar/CRSP
Morningstar/CRSP
Morningstar/CRSP
Log of total net assets of fund or family.
The number of years since the fund’s oldest class inception
Dummy that equals one if a fund has a sales charge at initial fund purchase, not included
in expense ratio in percentage
Dummy that equals one if a fund has a redemption charge, not included in expense ratio
in percentage
Percentage of institutional class holdings in fund
Trading activity/change in portfolio holdings computed as the lesser of sales or purchases
divided by average monthly total net assets in percentage
The number of funds under a mutual fund family
The percentage of funds in a family organized as a team
Percentage of TNA held in Common Stocks
Percentage of TNA held in Cash
The Number of Classes offered in a fund
Form 485
Form 485
Form 485
Form 485
Log of number of directors on fund board
Proportion of directors who are classified as outsiders (independent)
Dummy that equals one if the board chair is an independent director
Indicator variable if a single board oversees all funds managed by sponsor.
Governance Characteristics
Board Size
Independent Directors
Independent Chair
Unitary Board Structure
Morningstar/CRSP
Morningstar/CRSP
Morningstar/CRSP
Note: For fund with multiple share classes we compute the weighted average value (using TNA of each class), where the reported fund TNA is the sum of the
TNA from all classes. All Morningstar data are cross- checked or recomputed with the CRSP Mutual Fund database.
25
Table 2
Distribution of team managed funds
Panel A: Distribution of fund management structures by year
Years
Number
Single
Team
%
Single
Team
1999
2000
2001
2002
2003
2004
2005
2006
2007
776
891
932
1,054
1,138
1,053
1,063
936
925
683
886
1,037
1,213
1,439
1,401
1,577
1,490
1,454
53.19
50.14
47.33
46.49
44.16
42.91
40.27
38.58
38.88
46.81
49.86
52.67
53.51
55.84
57.09
59.73
61.42
61.12
Total
8,768
11,180
43.95
56.05
Note: Panel A reports the number and percentage of samples by year for each type of fund management
structure.
26
Panel B: Distribution of team-managed funds by objectives
Objective Title
Sector Fund
Single State Municipal
Total Return
Others
Single
Obs.
729
187
14
174
326
149
759
165
545
553
576
230
1,276
770
1,739
230
146
Observations
8,768
Aggressive Growth
Balanced
Global Bond
Global Equity
Government Security
Income
International Equity
Ginnie Mae Fund
Growth and Income
High Quality Bond
High Quality Municipal
High Yield Bond
Long Term Growth
(%)
37.29
21.27
4.18
29.59
40.50
47.60
41.84
43.88
38.06
40.93
52.65
46.28
44.46
57.72
56.50
29.60
58.40
Team
Obs.
1,226
692
321
414
479
164
1,055
211
887
798
518
267
1,594
564
1,339
547
104
(%)
62.71
78.73
95.82
70.41
59.50
52.40
58.16
56.12
61.94
59.07
47.35
53.72
55.54
42.28
43.50
70.40
41.60
43.95
11,180
56.05
Note: Panel B summarizes the number and percentage of samples by investment objectives for each type
of fund management organization. Others include precious metal funds, utility funds, and special funds.
27
Panel C: Descriptive statistics
Mean
Single
Median
Stand. Dev.
Mean
Team
Median
Stand. Dev.
174,544
80.219
1,485
14.632
93.739
50.524
3.674
2.880
0.476
0.465
15.867
0.674
49,673
58.000
320
12.340
57.000
76.915
2.200
3.000
0.000
0.000
0.000
1.00
283,531
66.810
4,813
10.90
127.520
46.819
6.360
1.705
0.499
0.499
30.947
0.469
83,212
53.302
1,649
14.424
92.228
55.673
3.456
3.477
0.613
0.582
24.114
0.779
41,330
49.000
376
11.414
62.000
83.075
2.000
4.000
1.000
1.000
1.405
1.000
159,180
31.622
6,108
11.64
116.382
45.116
6.698
2.010
0.487
0.493
36.554
0.415
91,332***
26.917***
-164**
0.208
1.511
-5.149***
0.218**
-0.597***
-0.137***
-0.117***
-8.364***
-0.105***
8,343***
9.000***
-56***
0.926***
-5.000***
-6.160***
0.200***
-1.000***
-1.000***
-1.000***
-1.405***
0.000***
Performance Characteristics
Alpha
Expense Ratio
Alpha + Expense
-0.649
1.118
0.469
-0.805
1.038
0.142
9.917
0.487
9.915
-0.775
1.147
0.372
-0.864
1.090
0.113
8.386
0.502
8.374
0.126
-0.029***
0.097
0.059
-0.052***
0.029
Board Characteristics
Board Size
Independent Directors
Independent Chair
Unitary Board
9.188
80.044
47.183
36.234
9.000
80.000
0.000
0.000
2.722
11.412
49.923
48.070
9.099
80.516
43.184
42.710
9.000
80.000
0.000
0.000
2.477
10.831
49.535
49.468
0.089**
-0.472***
3.999 ***
-6.476***
0.000
0.000***
0.000***
0.000***
Family and Fund Characteristics
Family TNA
Number Family Funds
TNA
Fund Age
Portfolio Turnover
Stock Holdings
Cash Holdings
Number of Class
Front Load
Rear Load
Institutional Holdings
Public
Observations
8,768
Tests of Difference
Mean
Median
11,180
Note: This table reports descriptive statistics for the overall fund samples from 1999 through 2007, segmented by fund management organizations. All variables
are gathered or computed at the end of each year from 1999 through 2007. Definition of variables presented in this table can be found in Table 1. The last two
columns report the tests of difference. The notations ***, **, * denote statistical significance at the 1%, 5%, and 10% levels respectively.
28
Panel D: Pearson Correlations (need alpha +expenses in here)
Team
Managed
Alpha
Expense
Ratio
Alpha +
Expense
Family
TNA
Number
of Funds
Fund
TNA
Board
Size
Indep.
Directors
Alpha
-0.007
Expense Ratio
0.029***
-0.043***
Alpha + Expense
-0.005
0.999***
0.012*
Family TNA
-0.200***
0.031***
-0.178***
0.021**
Number of Funds
-0.257***
0.026***
-0.073***
0.022***
0.792***
Fund TNA
0.015**
0.022***
-0.122***
0.015**
0.301***
0.094***
Board Size
-0.017**
0.008
0.098***
0.013*
0.293***
0.331***
0.090***
Independent
0.021***
0.015**
0.043***
-0.013*
0.019**
0.152***
-0.017**
0.008
Unitary Board
0.065***
-0.009
-0.083***
-0.014*
-0.118***
-0.262***
-0.036***
0.038***
0.045***
Indep. Chair
-0.040***
-0.009
0.027***
-0.007
0.221***
0.348***
0.029***
0.217***
0.389***
Unitary
Board
0.148***
Note: This table reports correlation statistics for our sample. The notation ***,**,*, represent significance at the 1 and 5% levels, respectively. Variable definitions are
provided in Table 1
29
Table 3
Performance in Team and Single Managed Funds
Dependent Variables
Intercept
Fund TNA
Fund Age
Institutional
Cash Holdings
Stock Holdings
Turnover
Board Size
Indep. Directors
Independent Chair
Unitary Board
Public
Objective dummy
Year dummy
Ajdusted-R2
N
Alpha
Single
Team
(1)
(2)
1.396
-1.748
(0.481)
(0.145)
0.556***
0.385***
(0.000)
(0.000)
-0.722***
-0.257*
(0.000)
(0.079)
0.002
0.003*
(0.381)
(0.069)
0.006
0.042***
(0.633)
(0.000)
-0.015**
-0.005
(0.040)
(0.391)
-0.002*
-0.001
(0.093)
(0.131)
-0.049
-0.637**
(0.875)
(0.019)
-0.018**
0.011*
(0.019)
(0.095)
0.003
-0.002
(0.121)
(0.187)
0.001
-0.001
(0.898)
(0.888)
-0.212
0.036
(0.268)
(0.835)
Expenses
Single
Team
(3)
(4)
***
1.433
0.970***
(0.000)
(0.000)
-0.088***
-0.063***
(0.000)
(0.000)
0.001
-0.050***
(0.935)
(0.000)
-0.003***
-0.004***
(0.000)
(0.000)
-0.002
-0.001
(0.106)
(0.555)
-0.001
-0.001
(0.687)
(0.853)
0.001**
0.001***
(0.023)
(0.000)
0.016
0.173***
(0.564)
(0.000)
0.003***
0.003***
(0.009)
(0.000)
0.001
0.001***
(0.526)
(0.001)
-0.001***
-0.001***
(0.009)
(0.000)
0.150***
0.119***
(0.000)
(0.000)
Alpha + Expenses
Single
Team
(5)
(6)
*
2.829
-0.778
(0.099)
(0.509)
0.468***
0.322***
(0.000)
(0.000)
-0.720***
-0.307**
(0.000)
(0.034)
-0.001
-0.001
(0.610)
(0.660)
0.004
0.041***
(0.727)
(0.000)
-0.016**
-0.005
(0.037)
(0.382)
-0.001
-0.001
(0.120)
(0.312)
-0.033
-0.464*
(0.915)
(0.088)
-0.015*
0.015**
(0.051)
(0.028)
0.003
-0.002
(0.106)
(0.302)
-0.001
-0.001
(0.959)
(0.548)
-0.067
0.154
(0.731)
(0.362)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
0.069
8,768
0.068
11,180
0.486
8,768
0.484
11,180
0.069
8,768
0.068
11,180
B: Chow tests for differences in coefficients in Single and Team managed funds. (p-values)
All
All Governance-related
Board Size
Independent Directors
Independent Chair
Unitary
Alpha
0.002***
0.001***
0.013**
0.001***
0.497
0.994
Expenses
0.000***
0.000***
0.000***
0.399
0.003***
0.092*
Alpha + Expenses
0.001***
0.002***
0.046**
0.001***
0.656
0.901
Note: This table presents ordinary least square regressions of fund performance on fund management organizations.
The data covers the period from 1999 to 2007 for 3,002 funds. The dependent variables are Carhart four factor alpha
(Alpha), the annual expense ratio (Expenses), and the sum of Carhart alpha and expense ratio (Alpha + Expenses), all
are calculated each year. The independent variables include log of fund TNA, (log fund TNA), log of fund age, (Log
fund age), the number of classes offered in a fund (Number of class), the percentage of institutional class in a fund
30
(Institutional), the percentage of cash a fund holds (Cash holdings), the percentage of stock a fund holds (Stock
holdings), approximate percentage of fund holdings that changed over the preceding year (Turnover), proportion of
outside directors (Independent Directors), log of number of directors on fund board (Board Size), a dummy variable
that equals one if the board is comprised as unitary board (Unitary board), and a dummy variable that equals one if
the board chair is an independent director (Independent Chair). P-values derived from fund-level clustered robust
standard errors are reported in the third column. The notations ***, **, * denote statistical significance at the 1%, 5%,
and 10% levels respectively.
31
Table 4
Teams and Boards of Directors
Panel A:
Intercept
Lambda
Team
Fund TNA
Fund Age
Institutional
Cash Holdings
Stock Holdings
Turnover
Indep. Director
Board Size
Independent Chair
Unitary Board
Public
Board Size*Team
Indep Dir*Team
Dependent variable = Alpha
Base
Board Size
Indep. Dir.
(1)
(2)
(3)
-0.830
-1.961*
0.520
(0.398)
(0.070)
(0.627)
0.272**
0.249*
0.256**
(0.034)
(0.053)
(0.047)
0.065
2.017**
-2.298***
(0.657)
(0.016)
(0.004)
0.463***
0.464***
0.464***
(0.000)
(0.000)
(0.000)
-0.455***
-0.460***
-0.457***
(0.000)
(0.000)
(0.000)
0.003**
0.003*
0.003**
(0.039)
(0.053)
(0.039)
0.026***
0.027***
0.026***
(0.001)
(0.001)
(0.001)
-0.009**
-0.009**
-0.009**
(0.048)
(0.048)
(0.044)
-0.001**
-0.001**
-0.001**
(0.039)
(0.041)
(0.047)
-0.002
-0.001
-0.018**
(0.703)
(0.835)
(0.014)
-0.262
0.227
-0.283
(0.182)
(0.427)
(0.148)
0.001
-0.001
0.001
(0.947)
(0.842)
(0.815)
0.001
0.001
0.001
(0.572)
(0.533)
(0.800)
-0.137
-0.092
-0.145
(0.265)
(0.463)
(0.238)
-0.910**
(0.019)
0.029***
(0.002)
Indep. Chair*Team
Indep. Chair
(4)
-0.823
(0.402)
0.269**
(0.036)
0.126
(0.495)
0.464***
(0.000)
-0.457***
(0.000)
0.003**
(0.038)
0.026***
(0.001)
-0.009**
(0.049)
-0.001**
(0.040)
-0.002
(0.668)
-0.276
(0.163)
0.001
(0.637)
0.001
(0.544)
-0.126
(0.308)
-0.001
(0.544)
Unitary*Team
Ajdusted-R2
N
Unitary
(5)
-0.833
(0.399)
0.272**
(0.035)
0.069
(0.701)
0.463***
(0.000)
-0.455***
(0.000)
0.003**
(0.039)
0.026***
(0.001)
-0.009**
(0.048)
-0.001**
(0.039)
-0.002
(0.705)
-0.002
(0.182)
0.001
(0.947)
0.001
(0.722)
-0.137
(0.265)
-0.001
(0.975)
0.066
19,948
0.066
19,948
0.066
19,948
0.066
19,948
0.066
19,948
Note: This table presents ordinary least square regressions of fund performance on fund management organizations.
The data covers the period from 1999 to 2007 for 3,002 funds. The dependent variable is Carhart four factor alpha,
calculated each year. The independent variables include log of fund TNA, (log fund TNA), log of fund age, (Log
fund age), the number of classes offered in a fund (Number of class), the percentage of institutional class in a fund
(Institutional), the percentage of cash a fund holds (Cash holdings), the percentage of stock a fund holds (Stock
32
holdings), approximate percentage of fund holdings that changed over the preceding year (Turnover), proportion of
outside directors (Independent Directors), log of number of directors on fund board (Board Size), a dummy variable
that equals one if the board is comprised as unitary board (Unitary board), and a dummy variable that equals one if
the board chair is an independent director (Independent Chair). The lambda, the inverse Mill’s ratio calculated based
on the probit model in Table 6, is added to control for endogeneity in each odd column of the results. All models
include year and investment objective fixed effects. P-values derived from fund-level clustered robust standard
errors are reported in the third column. The notations ***, **, * denote statistical significance at the 1%, 5%, and 10%
levels respectively.
33
Panel B:
Intercept
Lambda
Team
Fund TNA
Fund Age
Institutional
Cash Holdings
Stock Holdings
Turnover
Indep. Director
Board Size
Independent Chair
Unitary Board
Public
Base
(1)
1.315 ***
(0.000)
-0.093***
(0.000)
-0.019
(0.135)
-0.077***
(0.000)
-0.023**
(0.042)
-0.004***
(0.000)
-0.001
(0.491)
-0.001
(0.553)
0.001***
(0.000)
0.003***
(0.000)
0.089***
(0.000)
0.001***
(0.003)
-0.001***
(0.000)
0.130***
(0.000)
Board Size*Team
Indep Dir*Team
Indep. Chair*Team
Dependent variable = Expense Ratio
Board Size Indep. Dir. Indep. Chair
(2)
(3)
(4)
1.534***
1.371***
1.312***
(0.000)
(0.000)
(0.000)
-0.089***
-0.094***
-0.092***
(0.000)
(0.000)
(0.000)
-0.396***
-0.117
-0.045***
(0.000)
(0.178)
(0.000)
-0.077***
-0.078***
-0.077***
(0.000)
(0.000)
(0.000)
-0.023**
-0.024**
-0.023**
(0.050)
(0.041)
(0.047)
-0.004***
-0.004***
-0.004***
(0.000)
(0.000)
(0.000)
-0.001
-0.001
-0.001
(0.413)
(0.488)
(0.487)
-0.001
-0.001
-0.001
(0.550)
(0.537)
(0.544)
0.001***
0.001***
0.001***
(0.000)
(0.000)
(0.000)
0.003***
0.002**
0.003***
(0.000)
(0.020)
(0.000)
-0.005
0.088***
0.095***
(0.832)
(0.000)
(0.000)
0.001***
0.001***
-0.000
(0.001)
(0.003)
(0.964)
-0.001***
-0.001***
-0.001***
(0.000)
(0.000)
(0.000)
0.121***
0.130***
0.125***
(0.000)
(0.000)
(0.000)
0.176***
(0.000)
0.001
(0.241)
0.001***
(0.001)
Unitary*Team
Ajdusted-R2
N
Unitary
(5)
1.305***
(0.000)
-0.093***
(0.000)
-0.008
(0.590)
-0.077***
(0.000)
-0.024**
(0.040)
-0.004***
(0.000)
-0.001
(0.483)
-0.001
(0.562)
0.001***
(0.000)
0.003***
(0.000)
0.089***
(0.000)
0.001***
(0.003)
-0.001***
(0.004)
0.130***
(0.000)
-0.000
(0.117)
0.483
19,948
0.485
19,948
0.483
19,948
0.484
19,948
0.483
19,948
Note: This table presents ordinary least square regressions of fund performance on fund management organizations.
The data covers the period from 1999 to 2007 for 3,002 funds. The dependent variable is expense ratio. The
independent variables include log of fund TNA, (log fund TNA), log of fund age, (Log fund age), the number of
classes offered in a fund (Number of class), the percentage of institutional class in a fund (Institutional), the
percentage of cash a fund holds (Cash holdings), the percentage of stock a fund holds (Stock holdings), approximate
percentage of fund holdings that changed over the preceding year (Turnover), proportion of outside directors
(Independent Directors), log of number of directors on fund board (Board Size), a dummy variable that equals one if
the board is comprised as unitary board (Unitary board), and a dummy variable that equals one if the board chair is
an independent director (Independent Chair). The lambda, the inverse Mill’s ratio calculated based on the probit
34
model in Table 6, is added to control for endogeneity in each odd column of the results. All models include year and
investment objective fixed effects. P-values derived from fund-level clustered robust standard errors are reported in
the third column. The notations ***, **, * denote statistical significance at the 1%, 5%, and 10% levels respectively.
35
Panel C:
Intercept
Lambda
Team
Fund TNA
Fund Age
Institutional
Cash Holdings
Stock Holdings
Turnover
Indep. Director
Board Size
Independent chair
Unitary board
Public
Base
(1)
0.485
(0.618)
0.179
(0.162)
0.047
(0.750)
0.386***
(0.000)
-0.479***
(0.000)
-0.001
(0.466)
0.026***
(0.001)
-0.009**
(0.043)
-0.001
(0.104)
0.001
(0.819)
-0.173
(0.377)
0.001
(0.721)
0.001
(0.919)
-0.007
(0.953)
Board Size*Team
Indep Dir*Team
Indep. Chair*Team
Dependent variable = Alpha + Expense
Board Size Indep. Dir. Indep. Chair
(2)
(3)
(4)
-0.427
1.891*
0.489
(0.690)
(0.079)
(0.615)
0.160
0.162
0.178
(0.212)
(0.206)
(0.166)
1.621*
-2.415***
0.080
(0.053)
(0.002)
(0.662)
0.387***
0.387***
0.387***
(0.000)
(0.000)
(0.000)
-0.483***
-0.481***
-0.480***
(0.000)
(0.000)
(0.000)
-0.001
-0.001
-0.001
(0.406)
(0.467)
(0.470)
0.026***
0.026***
0.026***
(0.001)
(0.002)
(0.001)
-0.009**
-0.009**
-0.009**
(0.043)
(0.039)
(0.044)
-0.001
-0.001
-0.001
(0.108)
(0.104)
(0.105)
0.002
-0.015**
0.001
(0.711)
(0.035)
(0.840)
0.221
-0.195
-0.181
(0.436)
(0.318)
(0.360)
0.001
0.001
0.001
(0.887)
(0.595)
(0. 633)
0.001
-0.001
0.001
(0.881)
(0.821)
(0.900)
0.029
-0.015
-0.001
(0.813)
(0.899)
(0.992)
-0.734*
(0.057)
0.031***
(0.001)
-0.001
(0.733)
Unitary*Team
Ajdusted-R2
N
Unitary
(5)
0.471
(0.629)
0.179
(0.162)
0.060
(0.734)
0.386***
(0.000)
-0.479***
(0.000)
-0.001
(0.473)
0.026***
(0.001)
-0.009**
(0.043)
-0.001
(0.105)
0.001
(0.810)
-0.172
(0.377)
0.001
(0.719)
0.001
(0.874)
-0.007
(0.952)
-0.001
(0.888)
0.066
19,948
0.066
19,948
0.066
19,948
0.066
19,948
0.066
19,948
Note: This table presents ordinary least square regressions of fund performance on fund management organizations.
The data covers the period from 1999 to 2007 for 3,002 funds. The dependent variable is Cahart four factor alpha,
calculated each year plus expense ratio. The independent variables include log of fund TNA, (log fund TNA), log of
fund age, (Log fund age), the number of classes offered in a fund (Number of class), the percentage of institutional
class in a fund (Institutional), the percentage of cash a fund holds (Cash holdings), the percentage of stock a fund
holds (Stock holdings), approximate percentage of fund holdings that changed over the preceding year (Turnover),
proportion of outside directors (Independent Directors), log of number of directors on fund board (Board Size), a
dummy variable that equals one if the board is comprised as unitary board (Unitary board), and a dummy variable
that equals one if the board chair is an independent director (Independent Chair). The lambda, the inverse Mill’s
36
ratio calculated based on the probit model in Table 6, is added to control for endogeneity in each odd column of the
results. All models include year and investment objective fixed effects. P-values derived from fund-level clustered
robust standard errors are reported in the third column. The notations ***, **, * denote statistical significance at the
1%, 5%, and 10% levels respectively.
37
Table 5
Robustness check using the funds years without fund structure changes
Intercept
Lambda
Team
Fund TNA
Fund Age
Institutional
Cash Holdings
Stock Holdings
Turnover
Indep. Director
Board Size
Independent chair
Unitary board
Public
Board Size*Team
Board Size
(1)
-0.835
(0.494)
0.260*
(0.002)
1.697*
(0.076)
0.375***
(0.000)
-0.339***
(0.004)
-0.001
(0.616)
0.032*
(0.000)
-0.010**
(0.039)
-0.001
(0.155)
0.001
(0.899)
0.308
(0.330)
-0.001
(0.888)
0.001
(0.690)
0.159
(0.246)
-0.661
(0.133)
Indep Dir*Team
Dependent variable = Alpha + Expense
Independence Independent Chair Unitary Board
(2)
(3)
(4)
1.594
-0.026
-0.017
(0.179)
(0.981)
(0.988)
0.259*
0.277**
0.278**
(0.053)
(0.039)
(0.039)
-2.550***
0.310
0.272
(0.002)
(0.127)
(0.173)
0.375***
0.374***
0.374***
(0.000)
(0.000)
(0.000)
-0.337***
-0.335***
-0.334***
(0.004)
(0.004)
(0.004)
-0.001
-0.001
-0.001
(0.677)
(0.695)
(0.679)
0.031***
0.031***
0.031***
(0.000)
(0.000)
(0.000)
-0.010**
-0.010**
-0.010**
(0.035)
(0.039)
(0.039)
-0.001
-0.001
-0.001
(0.150)
(0.153)
(0.153)
-0.019**
0.001
0.001
(0.013)
(0.990)
(0.997)
0.071
-0.049
-0.043
(0.744)
(0.822)
(0.841)
0.001
0.001
0.001
(0.827)
(0.840)
(0.975)
-0.001
0.001
0.001
(0.970)
(0.712)
(0.893)
0.113
0.128
0.122
(0.398)
(0.346)
(0.363)
0.035***
(0.000)
Indep. Chair*Team
-0.001
(0.799)
Unitary*Team
Ajdusted-R2
N
0.001
(0.917)
0.072
16,736
0.073
16,736
0.072
16,736
0.072
16,736
Note: This table presents ordinary least square regressions of fund performance on fund management organizations
using the Heckman’s approach. The data covers the period from 1999 to 2007 for 2,951 funds. The dependent
variable is Cahart four factor alpha, calculated each year, plus expense ratio. The independent variables include log
of fund TNA, (log fund TNA), log of fund age, (Log fund age), the number of classes offered in a fund (Number of
class), the percentage of institutional class in a fund (Institutional), the percentage of cash a fund holds (Cash
holdings), the percentage of stock a fund holds (Stock holdings), approximate percentage of fund holdings that
changed over the preceding year (Turnover), governance index score which is a sum of the four governance
measures. If the fund has greater proportion of outside director representation than the overall sample median, it is
38
assigned with a vlue of 1, and otherwise 0. If the fund’s board has the smaller size than the overall sample median
size, then it will be assigned a value of 1, and otherwise 0. The presence of independent chair is assigned a value of 1,
and otherwise 0. The unitary board is assigned a value of 1, and otherwise 0. All these four scores are added up to
make a governance index score where 4 is the highest (best) and 0 is the lowest (worst). The lambda, the inverse
Mill’s ratio calculated based on the probit model in Table 8, is added to control for endogeneity in each odd column
of the results. All models include year and investment objective fixed effects. P-values derived from fund-level
clustered robust standard errors are reported in the third column. The notations ***, **, * denote statistical
significance at the 1%, 5%, and 10% levels respectively.
39
Table 6
2SLS instrumental variable approach
Intercept
Team
Log fund TNA
Log fund age
Institutional
Cash Holdings
Stock Holdings
Turnover
Outside director
Log board size
Independent chair
Unitary board
Public
Board size*Team
Outside*Team
Indep. Chair*Team
Dependent variable = Alpha + Expense
Board Size Independence Independent Chair
(1)
(2)
(3)
-0.744
3.233***
0.806
(0.564)
(0.009)
(0.396)
2.373
-4.556***
0.115
(0.120)
(0.001)
(0.663)
0.386***
0.387***
0.387***
(0.000)
(0.000)
(0.000)
-0.482***
-0.480***
-0.483***
(0.000)
(0.000)
(0.000)
-0.001
-0.001
-0.001
(0.361)
(0.457)
(0.500)
0.027***
0.026***
0.026***
(0.001)
(0.002)
(0.001)
-0.009**
-0.009**
-0.009**
(0.043)
(0.036)
(0.044)
-0.107
-0.108
-0.107
(0.109)
(0.103)
(0.110)
0.002
-0.028***
-0.000
(0.663)
(0.008)
(0.947)
0.472
-0.207
-0.245
(0.263)
(0.293)
(0.217)
0.001
0.001
0.005*
(0.949)
(0.475)
(0.061)
0.000
-0.001
0.000
(0.882)
(0.612)
(0.761)
0.038
-0.035
0.037
(0.761)
(0.774)
(0.762)
-1.193*
(0.086)
0.054***
(0.001)
-0.008*
(0.051)
Unitary*Team
Ajdusted-R2
N
Unitary Board
(4)
0.585
(0.545)
-0.017
(0.943)
0.385***
(0.000)
-0.478***
(0.000)
-0.001
(0.559)
0.025***
(0.001)
-0.009**
(0.045)
-0.106
(0.111)
0.002
(0.704)
-0.165
(0.400)
0.001
(0.629)
0.003
(0.280)
-0.026
(0.828)
-0.006
(0.204)
0.068
19,948
0.068
19,948
0.067
19,948
0.067
19,948
Note: This table presents 2SLS approach with the percent of team fund management in the fund family as an
instrumental variable to examine the relation between fund performance and fund management organizations. The
data covers the period from 1999 to 2007 for 3,002 funds. The dependent variable is Cahart four factor alpha,
calculated each year, plus expense ratio. The independent variables include log of fund TNA, (log fund TNA), log of
fund age, (Log fund age), the number of classes offered in a fund (Number of class), the percentage of institutional
class in a fund (Institutional), the percentage of cash a fund holds (Cash holdings), the percentage of stock a fund
holds (Stock holdings), approximate percentage of fund holdings that changed over the preceding year (Turnover),
proportion of outside directors (Independent Directors), log of number of directors on fund board (Board Size), a
dummy variable that equals one if the board is comprised as unitary board (Unitary board), and a dummy variable
40
that equals one if the board chair is an independent director (Independent Chair). P-values derived from fund-level
clustered robust standard errors are reported in the third column. The notations ***, **, * denote statistical
significance at the 1%, 5%, and 10% levels respectively.
41
Table 7
Management Structure and Governance Index
Intercept
Team
Log fund TNA
Log fund age
Institutional
Cash Holdings
Stock Holdings
Turnover
Intercept
Public
Governance index
Governance index*Team
Adjusted R2
N
Dependent variable = Alpha + Expense
(1)
(2)
0.208
0.526
(0.786)
(0.502)
0.169
0.160
(0.184)
(0.209)
0.038
-0.425*
(0.798)
(0.092)
0.383***
0.381***
(0.000)
(0.000)
-0.481***
-0.478***
(0.000)
(0.000)
-0.001
-0.001
(0.505)
(0.417)
0.026***
0.026***
(0.001)
(0.001)
-0.009**
-0.009**
(0.042)
(0.038)
-0.001
-0.001
(0.105)
(0.106)
-0.005
-0.011
(0.971)
(0.934)
0.026
-0.135
(0.609)
(0.127)
0.258**
(0.019)
0.066
19,948
0.066
19,948
Note: This table presents ordinary least square regressions of fund performance on fund management organizations
using the Heckman’s approach. The data covers the period from 1999 to 2007 for 3,002 funds. The dependent
variable is Cahart four factor alpha, calculated each year, plus expense ratio. The independent variables include log
of fund TNA, (log fund TNA), log of fund age, (Log fund age), the number of classes offered in a fund (Number of
class), the percentage of institutional class in a fund (Institutional), the percentage of cash a fund holds (Cash
holdings), the percentage of stock a fund holds (Stock holdings), approximate percentage of fund holdings that
changed over the preceding year (Turnover), proportion of outside directors (Independent Directors), log of number
of directors on fund board (Board Size), a dummy variable that equals one if the board is comprised as unitary board
(Unitary board), and a dummy variable that equals one if the board chair is an independent director (Independent
Chair). The lambda, the inverse Mill’s ratio calculated based on the probit model in Table 8, is added to control for
endogeneity in each odd column of the results. All models include year and investment objective fixed effects. Pvalues derived from fund-level clustered robust standard errors are reported in the third column. The notations ***,
**, * denote statistical significance at the 1%, 5%, and 10% levels respectively.
42