Do funds with few holdings outperform kaushik

Original Article

Do mutual funds with few holdings
outperform the market?
Received (in revised form): 24th October 2008

Abhay Kaushik
is an assistant professor of finance at Radford University, Virginia. He received his MS in Economics and PhD in Finance from
Florida Atlantic University. His main areas of research include financial markets and exchange rate.

Scott W. Barnhart
is an associate professor of finance at Florida Atlantic University. He received his MS in Economics from Florida State University
and PhD in Economics from Texas A&M University. Professor Barnhart is the Programme Director of both the MBA with Financial
Planning Track and the Certified Financial Plannert Certificate Programme at Florida Atlantic University.

Correspondence: Abhay Kaushik, Department of Accounting, Finance and Business Law, Radford University, Virginia 24142, USA
E-mail: akaushik@radford.edu

ABSTRACT This paper investigates the performance of mutual funds that hold a small
number of stocks in their portfolio. Similar to results reported in the literature for the
average diversified mutual fund, our results indicate that the average small holding fund
does not outperform the S&P 500 index. On average, small holding funds under-perform
the market on a risk and investment style adjusted basis by about À20 basis points per
month, or by À2.40 per cent per year. We also find that there is a sharp contrast between
the performance of Winner and Loser portfolios. On average, Winner portfolios outperform
the S&P composite index by 410 basis points per month, or an astounding 49.2 per cent
per annum, whereas Losers under-perform by 320, or À38.4 per cent per annum, over the
same period. Cross sectional regressions indicate that Winner portfolio abnormal
performance is positively and significantly related to fund turnover and the per cent of
the fund’s assets invested in their top 10 most heavily weighted holdings. Results for Loser
portfolios show that abnormal performance deteriorates significantly with turnover,
concentration and expenses, but rises with Load and Size.
Journal of Asset Management (2009) 9, 398–408. doi:10.1057/jam.2008.39

Keywords: mutual fund performance; expense ratio; turnover ratio; holdings

INTRODUCTION underperformance of non-stock holdings.
Recent academic research on actively Moreover, Carhart (1997) shows that risk-
managed mutual fund performance has adjusted net returns from the average mutual
shown that the average well-diversified fund are negatively correlated with fund
mutual fund under-performs passive expenses and portfolio turnover, both of
market benchmarks after adjusting for risk, which have increased over time (Wermers
expenses and trading costs (see, for example, (2000)).1
Wermers (2000) among others). The In contrast to the results reported in
underperformance found is largely studies of broadly diversified mutual funds,
explained by mutual fund expenses and the financial press has frequently reported
transactions costs, and to a lesser extent the that small, more concentrated or focused

398 & 2009 Palgrave Macmillan 1470-8272 Journal of Asset Management Vol. 9, 6, 398–408
www.palgrave-journals.com/jam/

Do mutual funds with few holdings outperform the market?

portfolios, while perhaps not fully in a small number of companies may be in
diversified, may be a better investment bet.2 conflict with the common recommendation
This is exactly the style of investing of diversification, it is consistent with Warren
advocated by Warren Buffett and used in his Buffett’s huge success and the notion that
phenomenally successful Berkshire Hathaway some fund managers have informational
fund.3 Recent research in this area has advantages over others. By holding fewer
proceeded down to two related paths: the stocks, as opposed to one or two hundred,
first investigates scale economies or the effect with larger percentages of the fund’s assets
of fund size on performance and the other concentrated among fewer companies, fund
examines how portfolio concentration affects managers can take more aggressive positions
fund performance. in companies that they are more familiar
In the first strand examining scale with, thereby magnifying potential gains
economies, Berk and Green (2004) (and losses). Indeed, in the late 1990s, when
demonstrate in their model that some stock market index returns were driven
empirical regularities found in mutual fund largely by a few highly valued companies in
research, such as fund flow following the index, mutual fund companies
performance, and so on, result when they introduced a number of new funds with
assume that mutual fund manager costs are concentrated holdings.4
an increasing function of the amount of These arguments raise a simple yet
funds under management. They assume that important question: Do mutual funds with
‘‘managerial talent is a scarce resource and is fewer and more concentrated holdings
dissipated as the scale of operations increases’’. outperform broader based market
Empirically, Chen et al (2004) document benchmarks, or do they suffer the same
Berk and Green’s assumption, finding that underperformance of the average mutual
risk and fee-adjusted excess returns are fund cited above? In this study we examine
negatively related to size, measured by the the performance of mutual fund portfolios
total net assets under management. In related that hold a small number of stocks. As a
work, Shawky and Smith (2005) find a consequence of holding few companies,
quadratic relationship between risk-adjusted these funds also have concentrated holdings.
fund returns and the number of fund In a fashion similar to the existing literature,
holdings, suggesting that there is a trade off we compare the performance of these funds
between diversification benefits and with passive portfolio benchmarks like the
increased transactions and monitoring costs. S&P 500 index.
In the second strand investigating fund As no mutual fund trade association, such
concentration, Kacperczyk et al (2005) show as the Investment Company Institute (ICI),
that mutual funds that concentrate their or investment research firm, such as
holdings within a few industries outperform Morningstar Inc., has defined a fund
passive benchmarks by 1.58 per cent per year category with the fund characteristics we
after controlling for risk and style differences. wish to investigate, that is, funds with a small
They attribute their findings to superior number of concentrated holdings, we rely on
stock selection by managers of concentrated definitions reported in the financial press and
funds. Similarly, Nanda et al (2004) find that in fund objective statements taken from
fund families that have fewer or more internet sources.5 Specifically, this study
narrowly focused investment strategies defines a small, concentrated portfolio as a
outperform families that have a wider variety mutual fund with holdings of 10–30 stocks.6
of strategies. We investigate the performance of these
Although the argument in favour of funds over the recent 2001–2006 year
holding a fund whose assets are concentrated period, a period that includes both recession

& 2009 Palgrave Macmillan 1470-8272 Journal of Asset Management Vol. 9, 6, 398–408 399

Kaushik and Barnhart

and expansion.7 During this period investors section discusses the methodology and the
have shown great interest in more narrowly penultimate section presents the empirical
focused, non-diversified funds, such as sector results. The last section concludes the
funds and exchange-traded funds. A case in paper.
point, over the period of study, the growth in
the total net assets under management of the
funds we investigate grew at a compound THE PROS AND CONS OF
annual rate of 21.44 per cent, versus a rate of HOLDING SMALL DIVERSIFIED
8.33 per cent for the overall mutual fund
industry (Source: ICI fact book).
PORTFOLIOS
In addition to examining the overall Fund managers who manage portfolios with
performance of these narrowly focused few holdings are conjectured to have a better
funds, we also segment funds into Winning understanding of those stocks and, therefore,
and Losing portfolios in order to see their are more informed to deliver higher returns
upside and downside potentials. We then compared with managers of large-holding,
examine the funds in a cross-sectional more diversified portfolios. This would be
analysis to see which fund characteristics, the result of following the Warren Buffett
such as expense ratio, turnover ratio, size, investment style. The obvious expected
concentration and load, explain their benefit to this structure would be higher
abnormal performance. returns, lower transactions costs and perhaps
In contrast to some of the literature cited expenses, because there will be fewer stocks
above, but in agreement with the findings for to trade and fewer stocks to research.
the average mutual fund, we find that the On the other hand, a smaller number
average, narrowly focused fund under- of holdings implies less diversification and
performs market benchmarks on a risk- higher idiosyncratic risk. Given the convex-
adjusted basis by about À2.4 per cent per option-like payoff in fund flows by investors
year. Despite this finding, there are some cited by Kacperczyk et al (2005), in which
phenomenal successes (and failures) within outstanding fund performers attract huge
this fund group: the top quartile of Winning positive cash inflows but poor performers
portfolios outperforms on a risk-adjusted do not experience outflows at the same
basis by approximately 49.2 per cent per year, intensity, fund managers may be motivated
whereas the Losing portfolios under-perform to place excessive bets on a few stocks. The
by about À38.4 per cent per year. In the implication is that standard measures of risk
cross-sectional analysis we find that fund for these companies should be higher than
turnover and the concentration of the fund’s the average mutual fund in the industry,
assets in its top 10 most heavily weighted and large losses may occur due to the rapid
holdings significantly and positively explain decline in a few stocks.
Winning performance, whereas fund
expenses and the fund’s assets in its top 10
most heavily weighted holdings are the DATA
major characteristics that significantly and We use the Morningstar Principia Pro
negatively explain Losing performance. database to first select funds with holdings
The remainder of the paper is organised of 10–30 stocks. Although we are interested
as follows: The next section discusses some in examining the performance of funds with
pros and cons of investing in narrowly small numbers of holdings that may be non-
focused mutual funds. The subsequent diversified, we are not interested in all funds
section describes the data sources and of this type and certain other types of funds.
discusses sample characteristics. The later Therefore, we screened out index funds,



international funds, sector funds, specialty of 197 funds over the period, consisting of
funds, hybrid funds, bond funds and 387 yearly fund observations and 4640
quantitative funds. Following Shawky and monthly fund observations.
Smith (2005) among others, we include only Fund- and manager-specific variables
type A shares in the event that the fund offers such as turnover ratio, expense ratio, load
multiple share types. charges, the fund’s investment in its top 10
Monthly returns over the period January most heavily weighted holdings, total net
2001–December 2006 are obtained from the assets and 12b-1 fees are taken from the
Center for Research in Security Prices CRSP mutual fund database and
(CRSP) using Wharton Research Data Morningstar Principia Pro database.
Services (WRDS). From these sources we Table 1 contains a break-down of the
obtain the returns of our fund sample, the firms in our sample into the well-known
S&P 500 composite index, the Fama–French nine-box investment style and capitalisation
factors (see Fama and French (1993)), SMB diagram, where all definitions are taken from
(the difference in returns between small and Morningstar Inc. It is clear from the chart
large capitalisation stocks), HML (the that the sample is dominated first by large
difference in returns between high and low companies and second by growth companies;
book-to-market stocks), the Carhart however, there are some firms from all
momentum factor, MOM (the difference in categories.
returns between stocks with high and low Table 2 contains annual returns, annual
past returns) and the monthly risk-free standard deviations of monthly returns and
return. The resulting sample contains a total the 6-year average Sharpe ratio for the

Table 1: Distribution of investment style and capitalisation

Large-Value Large-Blend Large-Growth

31 (15.7%) 38 (19.3%) 68 (34.5%)
Mid-Value Mid-Blend Mid-Growth

11 (5.58%) 11 (5.58%) 19 (9.64%)
Small-Value Small-Blend Small-Growth

5 (2.54%) 4 (2.03%) 10 (5.08%)

The table provides a distribution of sample funds based on style/capitalisation. Each box reports the number and
(percentage) of funds in each category. Definitions are obtained from Morningstar Inc.: Large-valuea is defined as
funds that invest primarily in big US firms that are less expensive or growing more slowly than others; Large-blend
funds are portfolios that are fairly representative of the overall large-cap US stock market in size, growth, rates and
price; Large-growth portfolios invest primarily in big US firms that are projected to grow faster than other large-cap
stocks; Mid-valueb are portfolios that primarily invest in medium-sized firms or a mix of small, medium and large
firms; Mid-blend are portfolios that invest in various sizes and styles of medium-sized firms and tend to stay away
from high-priced growth stocks; Mid-growth funds primarily invest in mid-size firms that tend to grow faster than
other mid-cap stocks; Small-valuec funds are portfolios that primarily invest in small US companies with valuations
and growth rates below other small-cap peers; Small-blend funds tend to invest in various sizes and styles of small
size firms or may use a mix of holdings with valuations and growth rates close to the small-cap averages; Small-
growth tend to invest in faster growing companies whose shares are at the lower end of the market capitalisation
range.
a
Large stocks are defined as firms with market capitalisation of over $10 billion.
b
Mid stocks referred to firms with market capitalisation of between $2 billion and $10 billion.
c
Small stocks are firms with capitalisation of between $300 million and $2 billion.



Table 2: Annual returns, standard deviations and the average Sharpe ratios for sample firms and the S&P 500
index
Sample firms S&P composite index
Year
Return (%) Standard deviation (%) Return (%) Standard deviation (%)

2001 À16.10 30.40 À12.02 19.01
2002 À25.34 22.42 À24.35 19.74
2003 29.44 14.70 24.22 10.91
2004 7.51 13.35 8.88 6.95
2005 2.57 14.18 3.24 7.49
2006 8.63 11.50 12.99 5.46
Average 1.12 17.76 2.16 11.59
Sharpe ratio 0.1378 0.4276

sample funds and the S&P 500 index. From model used in the literature by Carhart
this table we see that the average fund in (1997), among others. This model controls
the sample outperformed the S&P 500 for systematic risk and investment style
in only one year, that is, 2003, and had a factors and is used commonly in the
larger standard deviation of returns in every literature. The model is
year in the study. The average annual return
and standard deviation over the 2001–2006 rit À rft ¼ ai þ b1i ÂRMRFt þ b2i ÂSMBt
period for the S&P 500 is 2.16 and 11.59 þ b3i ÂHMLt þb4i ÂMOMt þ eit
per cent, respectively, whereas those for the (1Þ
sample funds are 1.12 and 17.76 per cent.
Thus, consistent with our expectations for where ritÀrft is the excess return on fund i in
narrowly focused funds, their risk as month t minus the corresponding monthly
measured by standard deviation is greater Treasury bill rate; ai is the monthly measure
than that for the S&P. However, the lower of abnormal performance (alpha); RMRFt
average return for small holding funds was the excess return on the market, that is,
not expected. The Sharpe ratios, calculated the S&P 500 composite index return minus
as the return from the given portfolio minus the corresponding monthly Treasury bill
the Treasury-bill rate all divided by the rate; bi is Beta, the measure of systematic
standard deviation of returns, provide a risk; SMBt the difference in returns between
measure of excess return per unit of risk. small and large capitalisation stocks; HMLt
Here we see that the S&P 500 has delivered the difference in returns between high and
approximately triple the excess return per low book-to-market stocks; and MOMt the
unit of risk than the sample firms. Although difference in returns between stocks with
these results indicate that narrowly focused high and low past returns.
funds may not deliver the returns expected of This model is estimated over the entire
more risky investments, we show below that 2001–2006 period, consisting of 72 months
some of these funds reward investors of data or 4640 monthly fund observations.
handsomely. The intercept in the model, ai, is the
abnormal performance in excess of risk
premiums associated with the market, size,
METHODOLOGY book-to-market and momentum factors.
In order to investigate the abnormal A positive alpha indicates that fund managers
performance of the funds in our sample more in the sample are able to outperform the
thoroughly than with simple Sharpe ratios, market on a risk and investment style
we first estimate the standard four-factor adjusted basis, whereas a negative alpha



indicates the opposite, and we examine these expenses are negatively related to abnormal
below. performance, and Carhart has documented a
Once the Carhart (1997) four-factor negative association between loads and
model is estimated, the parameters b1, y, b4 performance. However, these authors differ
are then used to calculate the alphas using in their findings regarding turnover. Carhart
the following equation: (1997) finds a negative effect of turnover on
the average mutual fund’s performance,
ait ¼ rit À rft À b1i ÂRMRFt À b2i ÂSMBt whereas Kacperczyk et al (2005) and
À b3i ÂHMLt À b4i ÂMOMt Wermers (2000) find a positive effect of
(2Þ turnover on abnormal performance. The
positive effect of turnover on abnormal
The alphas are subsequently used in cross- performance is attributed by Wermers (2000)
section regressions using the model in (3) in as the result of managers acting on
an attempt to investigate the abnormal information and having superior stock
performance across the sample funds using picking skills.
fund-specific characteristics. Following the We examine both the performance results
existing literature, we estimate the following in model (1) and the cross-sectional
model on a monthly basis across all funds regression results in model (3) over the entire
available in each month of the sample: sample period, as well as in the top and
bottom quartiles of the sample, sorted by
ait ¼ b0 þ b1 ÂExpensesit
excess return (fund return minus T-bill
þ b2 ÂLoadit þ b3 ÂSizeit return). This, of course, results in estimating
þ b4 ÂTtopit þ b5 ÂTurnoverit two distinct regression models, representing
þ uit ð3Þ two different regimes, one for the top
quartile of excess returns (Winners) and
where Expensesit is total annual management the other for the bottom quartile (Losers).
and administrative expenses including 12b-1 We chose quartiles for Winners and Losers
fees divided by the average total net assets of arbitrarily based on similar segmentations
fund i at time t; Loadit is the total of of firms reported in the literature.
maximum front-end and deferred sales Alternatively, we could have chosen them
charges as per cent of the total net assets of using a regime switching or threshold
fund i at time t; Sizeit the natural log of total model, using panel data developed by
net assets of fund i at time t; Turnoverit the Hansen (1999), in which the regime break
minimum (of aggregated sales or aggregated points are estimated along with other
purchases of securities), divided by the model parameters.8 Additionally, this
average 12-month total net assets of the fund, segmentation into Winners and Losers
also used as a proxy for transaction costs reduces the number of fund months in
associated with rebalancing the portfolio; and each of these quartiles to roughly 1000
Ttopit is per cent of the fund’s total net assets observations, after months in which
in its top 10 most heavily weighted holdings independent variable data points were not
and is used as a proxy for concentration. available are eliminated. Although this
Note that all the variables above with the reduction in sample size to the approximate
exception of Size are divided by 12 to put 1000 observations in each regression is still
them on the same measurement basis as the relatively large by conventional standards,
dependent variable, which is the monthly it is small by mutual fund standards, where
alpha. the typical regression may contain thousands
Previous research by Carhart (1997) and or tens of thousands of fund month
Kacperczyk et al (2005) has shown that observations.



EMPIRICAL RESULTS Table 3: Abnormal performance: (a) all funds;
(b) Winner quartile and (c) Loser quartile
Variable Estimate t-value
Performance
Panel a
Regression results from equation (1), the a À0.002 À3.52***
Carhart (1997) four-factor model, are RMRF 1.075 59.1***
SMB 0.288 15.0***
reported in Table 3, panels a–c. The results in HML À0.118 À5.02***
panel a, for all funds in the sample, indicate MOM 0.081 5.89***
Adj. R2 0.591 —
that, on average, small portfolios do not Number of fund months 4640 —
outperform the S&P 500 index after
Panel b
controlling for small stocks, book-to-market a 0.041 20.15***
and momentum. Results reported in panel a RMRF 0.421 9.16***
SMB 0.130 3.0***
show that monthly abnormal performance of HML 0.018 0.38
small portfolios relative to the S&P 500 index MOM À0.105 À4.89***
is À0.002 (À2.4 per cent per annum) before Adj. R2 0.178 —
Number of fund months 1,159 —
considering expenses and loads. All the
coefficients in the regression are highly Panel c
a À0.032 À19.28***
significant. Although the results above RMRF 0.770 16.0***
indicate that smaller funds are more risky SMB 0.094 2.29**
HML À0.313 À8.07***
than the S&P index, the beta coefficient MOM À0.040 À1.13
from panel a indicates that the funds are only Adj. R2 0.458 —
Number of fund months 1,160 —
marginally more risky in terms of systematic
risk, with a beta slightly greater than 1.0. The table summarises regression results for the
Carhart (1997) four-factor model showing the abnormal
The positive coefficients on SMB and MOM performance of sample firms, a, relative to market and
indicate that small cap companies and style benchmarks. Results are obtained from
regressing the excess return of each fund (the monthly
momentum stocks increase abnormal fund return minus the corresponding month T-bill rate)
performance, whereas the negative against the excess return of the market, RMRF, the
Fama–French factors, SMB, which is the difference in
coefficient on HML indicates that growth returns between small and large capitalisation stocks,
stocks tend to detract. HML, which is the difference in returns between high
It is intriguing to examine the and low book-to-market stocks, and MOM, which is
the difference in returns between stocks with high and
performance of the top and bottom low past returns.
performers within the overall sample. *, **, *** indicate statistical significance at the 10, 5 and
1 per cent levels, respectively.
Therefore, we divide the sample into
Winners and Losers, defined as those funds
in the top and bottom quartiles based on
excess return (monthly fund return minus (5.3 per cent), or 74.4 per cent annually,
corresponding month T-bill return). Each whereas for the Loser group it is À6.4
year from 2001 to 2006, we sort the entire per cent (À4.7 per cent), or À76.8 per cent
sample of monthly fund excess returns, annually. The four-factor model results for
labelling the top quartile Winners and the Winner and Loser portfolios are reported in
bottom quartile Losers. We then re-estimate Table 3, panels b and c, respectively. Results
the Carhart (1997) four-factor model using from the alpha coefficients indicate that the
these two sub-samples. average Winner fund outperforms the S&P
As one would expect for small, highly 500 index on a risk-adjusted basis of 410
concentrated portfolios, the differences in basis points per month (49.2 per cent per
the two quartiles are large. The Winner annum), whereas Losers earn À320 (À38.4
group has a mean (median) monthly excess per cent per annum). The larger positive
return over the entire period of 6.2 per cent coefficient on SMB indicates that smaller



companies add more to Winner fund show that abnormal performance, a, is
abnormal performance, and the negative significantly and directly associated with
coefficient on HML indicates that growth turnover and the percentage of total net
stocks reduce excess returns in the Loser assets invested in the fund’s top 10 most
funds. heavily weighted holdings. Investment in the

Cross-section regressions
We examine the funds in the sample using Table 5: Cross-sectional regressions on fund
characteristics: (a) Winner quartile and (b) Loser
cross-section regressions to assess which quartile
fund-specific characteristics explain the
Variable Estimate T Value
abnormal performance. The variables used to
explain the abnormal performance are those (a)
Intercept À0.013 À2.64***
contained in model (3) above. Expenses 0.672 0.79
Table 4 presents means and medians for Load À0.243 À0.63
the variables used in the cross-sectional Ttop 0.488 5.44***
Turnover 0.021 3.94***
regressions on a year-by-year basis. Several Size À0.0002 À0.47
items are noteworthy. First, the average size, Number of fund months 1,015 —
Adj. R2 0.0398 —
in terms of total net assets, has increased over
time. Second, the percentage of the fund (b)
Intercept 0.004 0.79
invested in the top 10 most heavily weighted Expenses À2.761 À4.63***
holdings is quite large and stays relatively Load 0.844 2.08**
Ttop À0.429 À5.09***
constant at about 55 per cent. Finally, the Turnover À0.034 À6.24***
average number of holdings in the funds has Size 0.0022 4.37***
increased slightly, whereas turnover has Number of fund months 1,009 —
Adj. R2 0.1351 —
declined over time.
The table reports results of model (3) regressing
The cross-sectional results for Winner and abnormal performance, a, against fund characteristics
Loser portfolios, reported in Tables 5a and b, for Winner and Loser quartiles. Variable descriptions
are given in Table 4.
respectively, show a sharp contrast between *, **, *** indicate statistical significance at the 10, 5 and
the two. The results for Winners in Table 5a 1 per cent levels, respectively.

Table 4: Descriptive statistics
Variable 2001 2002 2003 2004 2005 2006

Size (in millions) $49.23; $14.65 $120.65; $47.88 $89.93; $25.2 $107.66; $20 $116.19; $19.7 $128.49; $36.45
Number of stocks 23.85; 24 24.35; 25 24.65; 25 24.39; 25 24.68; 25 25.98; 27
Ttop 58.08; 57.12 56.88; 55.68 54.24; 51.48 54.24; 52.56 57.96; 56.16 54.72; 53.52
(top 10 holdings %)
Expense ratio (%) 1.73; 1.45 1.54; 1.44 1.98; 1.45 1.80; 1.49 1.83; 1.49 1.67; 1.35
Load (%) 2.25; 0.25 1.78; 0.25 2.23; 0.25 2.25; 0.25 1.97; 0.00 1.83; 0.00
12b-1 fee (%) 0.125; 0.00 0.24; 0.25 0.19; 0.16 0.21; 0.00 0.15; 0.00 0.18; 0.00
Turnover ratio (%) 177; 81.48 160; 57.96 97.44; 53.04 111.72;44.04 106.68; 63.96 84.48; 58.92
Observations 73; 874 54; 648 71; 852 63; 756 57; 684 69; 828

The table provides descriptive statistics of some of the key fund-specific variables of sample funds. For each
variable, the mean value is followed by median value. Size is the annual total net assets under management and
reported in millions of dollars; Number of stocks is the average number of stocks held by the funds during the year;
Ttop is the percentage of the fund’s total net assets invested in its top 10 weighted holdings; Expense ratio is
operating expenses, management fees, 12b-1 fees, administrative fees and all other asset-based costs incurred
by the fund as a percentage of total net assets; Load is the sum of fund’s front-end and deferred sales charges;
12b-1 fee is the annual charge deducted from fund assets to pay for distribution and marketing expenses; Turnover
ratio is the minimum (of aggregated sales or aggregated purchases of securities), divided by the average 12-month
total net assets of the fund. Yearly fund observations are followed by fund month observations.



top 10 most heavily weighted holdings but significant negative impact on Loser
(Ttop) is also used as a proxy for abnormal performance.
concentration, which, some have argued, In contrast to the results for Winner
are also the best ideas of fund managers. portfolios, the coefficients on load and size
The 0.488 coefficient on Ttop implies that have positive and significant effects on
for every 100 basis-point increase in funds Loser portfolio abnormal performance.
devoted to the top 10 most heavily held Load has the largest effect, with a coefficient
companies, the annual abnormal return of 0.844, implying an 84 basis-point increase
increases by 48.8 basis points. This indicates in Loser portfolio abnormal performance
that fund managers in Winner portfolios for every 100-point increase in Loads.
are making large bets on good stocks. Although this may seem counter-intuitive
A smaller relationship is observed between and in contrast to the results reported in
abnormal performance and the turnover Chordia (1996), Carhart (1997) has shown
ratio. The turnover ratio coefficient of that loads, especially back-end loads and
0.021 suggests that for every 100 basis-point redemption fees, dissuade investors from
increase in turnover, annual abnormal frequently redeeming their mutual fund
performance increases by 2.1 basis points. positions, thereby allowing funds with
A positive relationship between turnover loads to keep less cash and invest more in
ratio and abnormal performance is higher return stocks. Thus, higher loads
consistent with the notion that the benefits may in fact increase abnormal performance.
exceed the trading costs associated with The 0.0022 coefficient on size indicates
turnover if rebalancing of the portfolio is that for every increase in total net assets
a function of information arrival and not under management of US$1 million,
churning activities. Studies by Chevalier abnormal performance for Loser funds
and Ellison (1999) and Wermers (2000) increases by a paltry amount of $2200
demonstrate that turnover ratios can have or relatively small 0.22 basis points.
a positive and significant impact on the
performance of actively managed mutual
funds. CONCLUSIONS
Results reported in Table 5b for Loser This paper investigates the performance of
funds show that expenses, turnover and Ttop mutual funds that hold a small number of
all negatively affect abnormal performance, stocks in their portfolio. Following
with expenses having a very large negative definitions in the financial press and in
effect. The À2.76 coefficient on expenses mutual fund-specific investment objective
implies that for every 100 basis-point statements, we limit our investigation to
increase in Loser fund expenses, annual funds that are concentrated in 10–30 stocks.
abnormal performance declines by an Our results indicate that, on average, fund
excessive 276 basis points. Thus, expenses portfolios with few holdings do not
take a large toll on Loser portfolio returns. outperform the S&P 500 index. On average,
Likewise, the À0.429 coefficient on Ttop small portfolios under-perform the market
implies that for every 100 basis-point on a risk and investment style adjusted basis
increase in the Loser fund’s investment in by about À20 basis points per month or
its top 10 most heavily weighted holdings, À2.40 per cent per year.
annual abnormal performance drops by We also find that there is a sharp contrast
approximately 43 basis points. Thus Loser between the performance of Winner and
portfolio managers are making large bets Loser portfolios. Screening on excess return,
that affect their portfolios, but in poorly that is, fund return minus the T-bill rate, we
performing stocks. Turnover also has a small define Winners as funds in the top quartile



and Losers as those in the bottom quartile. likeyToo much of a good thing can be wonderful’. Source:
www.brainyquote.com.
On average, Winner portfolios outperform 4. Focus funds have big potential, if you dare. USA Today, 11
the S&P composite index by 410 basis points November 2002.
per month or an astounding 49.2 per cent 5. The following fund objective statement of the Janus 20
fund taken from the Fidelity website www.fideilty.com is
per annum, whereas Losers under-perform typical of the fund we are interested in: The fund seeks
by 320 or À38.4 per cent per annum over long-term capital appreciation. The fund is non-diversified
the same period. and intends to achieve its objective by concentrating its
investments in the equity securities of a smaller number of
To investigate this dramatic difference
companies than more diversified funds. Typically invests in
between Winner and Loser portfolios, we 15 to 35 firms at a time. The fund may invest in sectors or
use fund-specific characteristics in cross- foreign issuers.
sectional regressions to explain the abnormal 6. The Financial Dictionary and investopedia define focus
funds as those that contain a small number of stocks, in
performance from each group. The results general: (a) those who hold a portfolio concentrated in
indicate that Winner portfolio abnormal approximately 10–30 stocks, (b) those who concentrate
performance is positively and significantly their holdings within 1–3 sectors and (c) those who hold a
large number of different stocks, but a large portion of their
related to the turnover ratio and the total portfolio value is concentrated in a very small number
percentage of the fund’s assets invested in of stocks. (http://financial-dictionary.thefreedictionary.
their top 10 most heavily weighted holdings. com/Focused+Fund; http://www.investopedia.com/
Results for Loser portfolios show that terms/f/focusedfund.asp)
The Wall Street Journal defines focus funds as concentrated
abnormal performance deteriorates portfolios that tend to make big bets on just a few
significantly with turnover, concentration dozen stocks versus two to three times that amount
and expenses. On the other hand, Loser for a more diversified offering (Wall Street Journal,
28 November 2006).
portfolio abnormal performance is positively 7. According to the National Bureau of Economic Research
related to Load and Size. (NBER), the US economy underwent a recession in
March 2001 that ended in October of 2001. NBER
determined that the trough, which is also known as the
beginning of the expansion period, started in November
NOTES of 2001.
1. The funds analysed in these studies are characterised as 8. Hansen (1999) proposes estimating model parameters
large, broadly diversified funds from various investment and the threshold, g, using least squares. The overall
styles that exclude sector funds, international funds, index sample is then divided into regimes based on whether
funds, quant funds and bond funds. The benchmarks the threshold variable, qi,t (or fund performance in our
used to calculate risk-adjusted excess returns are those case) is smaller or larger than the computed threshold g.
used in this study and consist of the return on the S&P The value of g is computed with the restriction that a
500 index, the Fama–French HML and SMB factors minimum percentage of observations must lie in each
and Carhart’s Momentum factor, which are all defined regime. Hansen provides programs to run his analysis on
below. his website.
2. ‘A fund with few holdings, called a focus fund, has a better
chance of beating the S&P 500, but it’s more likely that
one or two bad stocks can smack shareholders senseless’.
Source: Focus funds have big potential, if you dare. USA REFERENCES
Today, 11 November 2002. Berk, J. B. and Green, R. C. (2004) Mutual fund flows and
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Fama, E. F. and French, K. R. (1993) Common risk factors in Nanda, V., Wang, J. Z. and Zheng, L. (2004) Family
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