Effects of expenditures and size on mutual fund performance.

Abstract

Mutual fund performance determinants affect expected returns or transaction costs. Factors affecting expected returns include asset allocation benchmark return and systematic risk, while transaction costs include explicit and implicit costs, which can be measured by expense ratio and fund size respectively. Insignificance of transaction cost determinants may be attributable to dominance of asset allocation in determining returns. This paper examines the expense ratio, performance, and size characteristics of domestic equity funds approved for Singapore's Central Provident Fund Investment Scheme for differing fiduciary standards, as these funds face the same standard of managing social security savings.

Keywords: Assets under Management; Expense Ratio; Financial Institution

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Determinants of mutual fund performance can be classified into factors affecting pre-tax or post-tax returns. Factors affecting pre-tax fund performance include (1) expenses, (2) investment style, (3) past pre-tax performance, (4) risk, and (5) turnover (Peterson et al, 2001). Post-tax factors are also important as after-tax returns are much less than before-tax returns for investors in high tax brackets. These post-tax determinants include (1) past pre-tax performance, (2) expenses, (3) risk, (4) investment style, (4) past tax efficiency, and (5) recent occurrence of large net redemption (Peterson et al, 2002). Comparison of these two groups of factors shows risk, style, past pre-tax performance and expenses affect performance before and after consideration of taxes. Still, studies on fund performance focused mainly on pre-tax factors.

While many funds are taxable on their profits and interests earned, studies on pre-tax factors are appropriate for funds whose profits and interests earned are non-taxable. For example, unit trusts approved for Singapore's Central Provident Fund (CPF) Investment Scheme are funds whose profits and interests earned are generally not taxable CPF Board, 2005. By studying these funds, this research focused on pre-tax determinants and avoided complication from differing tax rates. Besides, taxation laws pertaining mutual funds differ from country to country. For example, in the United States of America (USA), while dividends and interests paid by a mutual fund were taxed as ordinary shareholders' income, short and long-term capital gains were taxed at investor's marginal tax rate and capital gains rate of 20 per cent respectively (Jones 2003,). In Australia, income and capital gains derived by several types of superannuation funds were taxable at 15 per cent (Veltman, 2000). As for Singapore's CPF-approved unit trusts, even though investment profits were non-taxable, dividends received were taxed at investor's marginal tax rate (CPF Board, 2005). Therefore, the following discussion focuses on pre-tax factors.

Research on mutual fund performance did not agree on factors affecting fund returns. For example, Peterson et al (2002) did not consider assets under management an important factor, while Indro et al (1999) reported that fund size affected performance. While Sharpe (1966) observed that funds with higher reward-to-variability ratios incurred lower expenses, Ippolito (1989) found risk-adjusted returns are not related with expenses. This research focused on plausible effects of size and expense ratio on pre-tax fund performance.

The following section reviews conflicting literature on fund size and expense ratio characteristics to formulate hypotheses for their effects on fund performance. The next section describes data and methodology used.

Hypotheses and Models

This research builds on quantitative characteristics tested by Peterson et al (2001) as performance determinants for domestic equity funds in the USA. Specifically, fund size and expense ratio characteristics are reviewed in this order in the following sub-sections. This is followed by explanation of plausible relationship between fund size and expense ratio.

Fund Size as a Measure of Implicit Transaction Costs

According to Indro et al (1999), fund size reflects the following implicit transaction costs of active investment strategies: effect of huge transactions on market prices, opportunity cost of not trading, costs of being under scrutiny by market participants, and administrative stress from investment style deviation of large funds. Fund size results from flow of monies into and out of the fund.

Studies examining the relationship between past performance and flow of funds revealed that investors, when searching for quality funds based on performance record, placed their monies in funds with superior recent performance (Guercio and Tkac, 2002; Ippolito, 1992; Sawicki, 2000, Sirri and Tufano, 1998). While Ippolito (1992) as well as Sirri and Tufano (1998) found recent poor performance not leading to outflows from retail mutual funds in the USA, Sawicki (2000) reported Australian investors moving monies out of poorly performing wholesale funds. Agreeing with Sawicki (2000), Guercio and Tkac (2002) found changes in fund ratings reflecting past performance influencing flow of money to and from the funds. Sawicki (2001) suggested small funds that were relatively young were more likely to abandon unsuccessful strategies for more successful ones, so that investors would not perceive the need to withdraw from such funds. In a later study, Sawicki and Finn (2002) reported small funds being represented disproportionately among the top, but underrepresented among worst performers, suggesting fund size to be a performance determinant.

Indeed, nett assets under management could affect performance, as funds need to attain minimum size in order to achieve returns nett of research expenses and other costs. However, a fund that is too big could incur excessive costs, resulting in diminishing or even negative marginal returns. Initially, growth in the fund size could provide cost advantages, as brokerage costs for larger transactions are lower while research expenses would rise less than proportionately with fund size. After initial growth, a fund that has grown too large may cause its managers to deviate from its original objectives by investing in lower quality assets (which otherwise would not be considered when the fund is smaller) and increase administrative costs by additional coordination and hiring of staff to manage subfunds (Indro et al, 1999).

Clearly, flow of monies into funds with recent good performance is an attempt by investors to seek maximum risk-adjusted returns in an asymmetric information environment. However, after getting larger with injection of additional monies, funds with good recent returns cannot sustain their performance, as demonstrated by Carlson (1970), Dunn and Theinsen (1983) as well as Jensen (1969) in the USA and Tng (2005) in Singapore. As fund managers are compensated proportionately to the amount of assets under management, they are rewarded or penalised by clients based on recent performance. Even though past performance and flow of funds based on past performance may not be useful determinants of future performance, the amount of assets under management could affect fund performance.

Reviewing literature on relation between size and performance of funds produced mixed findings. Cicotello and Grant (1996), Droms and Walker (1994) as well as Grinblatt and Titman (1994) reported the absence of such relation for funds in the USA. The relation was also absent in Australia (Bird, Chin and McCrae, 1983; Gallagher, 2003; Gallagher & Martin, 2005) and Sweden (Dahlquist, Engstrom and Soderlind, 2000). However, fund size was a performance determinant in the USA (Indro et al, 1999). In Singapore, fund size may be a performance determinant as larger funds could achieve economies of scale compared to smaller funds. As Singapore is relatively small among developed equity markets, domestic equity funds may not suffer from diminishing marginal returns due to excessive fund size. This is tested in the first hypothesis:

[H.sub.1]: There is no significant difference in performance between small and large funds.

As funds need to attain minimum size to achieve returns nett of research and other costs, the following section examines such costs as plausible performance determinant.

Expense Ratio as a Measure of Explicit Transaction Costs

Passively managed index funds have lower costs and generally outperform actively managed funds (Bogle, 1998). Actively managed funds incur various costs. Examples of such costs are operating and research expenses, which are represented by the fund's expense ratio. There are various definitions of expense ratio. According to the Investment Company Institute (ICI), the national association of investment companies in the USA, a fund's expense ratio is its cost of doing business, as disclosed in its prospectus and expressed as a percentage of its assets (ICI, 2004). However, it is too general to view expense ratio as cost of conducting business for a fund.

Indro et al (1999) identified the ratio as proportion of fund assets paid for operating expenses and management fees, including 12b-1 fees (USA Securities and Exchange Commission Rule 12b-1 permitting funds to use as much as one percent of assets per year to pay for distribution and marketing costs), administration fees and other costs incurred by the fund, but excluding brokerage costs. Even though various costs are included in the expense ratio, most of these expenses could be associated with cost of financial market research, as Indro et al (1999) considered expense ratio to reflect the fund manager's explicit cost of research. As Indro et al (1999) characterised most retail fund investors as passive and not informed, expense ratio was considered the price paid by investors of a fund to its manager to inform them about the financial market.

In order for active management incurring research expenses to be worthwhile, incentives in the form of economic gains from trading based on information from useful research would compensate fund managers for incurring such costs (Grossman and Stiglitz, 1980). Therefore, fund managers efficiently incurring research expenses can earn positive risk-adjusted returns nett of expenses. Otherwise, inefficient expenses may lead to their income (proportionate to amount of assets under management) being penalised as investors withdraw monies from under-performing funds with excessive expenses.

Research on the relationship between risk-adjusted fund returns and expenses reported conflicting results in USA. While Sharpe (1966) observed funds with higher reward-to-variability ratios incurring lower expenses, Friend et al (1970) reported insignificant negative correlation between risk-adjusted fund returns and expenses. Furthermore, Ippolito (1989) found risk-adjusted returns not related with expenses, while Berkowitz and Qiu (2003) confirmed importance of expenses as determinant of fund performance. For large equity markets, high research expenses could be justified for better performance with more useful information on many investment choices available. For small markets, high research expenses might be wasteful with limited investment choices. As Singapore is relatively small among developed equity markets, a passive investment strategy may be justified when funds with higher research expenses cannot outperform their counterparts with lower expenses. This is tested in the second hypothesis:

[H.sub.2]: There is no significant difference in performance between funds with high expense ratios and those with low expense ratios.

The following sub-section explores plausible relationship between expense ratio and fund size.

Relation between Expense Ratio and Fund Size

The previous two sub-sections demonstrated performance of mutual funds could be related to implicit and explicit costs, which are measured by expense ratio and fund size respectively. The third and final hypothesis tests the relation between fund size and expense ratio. If initial growth in size could provide cost advantages in terms of brokerage costs and research expenses, large funds could have lower expense ratios than small funds:

[H.sub.3]: There is no significant difference in expense ratios of big and small funds.

To summarise transaction cost determinants of mutual fund performance explained in this section, Figure 1 provides a conceptual model.

[FIGURE 1 OMITTED]

As shown in the figure, fund performance determinants can be classified into expected return and transaction cost determinants. Major determinants of expected return include benchmark index return and systematic risk, while transaction cost determinants include expense ratio and fund size measures of explicit and implicit costs respectively.

A plausible determinant of explicit costs that is missing from this model is the fund's turnover ratio, measuring amount of trading in fund assets and computed by dividing amount of purchases or sales by average assets (Indro et al, 1999). Passive buy-and-hold or active stock selection with market timing can be reflected by low or high turnover ratio respectively. With most variability in fund returns explained by asset allocation benchmark return (Brinson, Hood and Beebower, 1986; Brinson, Singer and Beebower, 1991; Ibbotson and Kaplan, 2000), a remaining significant determinant could be transaction costs, which is considered one of the most important criteria for fund evaluation (Bodie, Kane and Marcus, 2005; Corrado and Jordan, 2005).

The following section describes how hypotheses were tested using secondary data.

Data and Methodology

To carry out this research, five years of quarterly returns, nett assets under management and expense ratios from 1999 to 2004 for 19 retail funds approved for Singapore's CPF Investment Scheme were examined. These funds were invested in shares from the Singapore Stock Exchange. Table 1 identifies funds used for this research.

For this research, only CPF-approved funds were considered as they followed the same fiduciary standard for managing social security savings, so as to control differing fiduciary standards. Failure to control such standards may lead to biased test results (Frye, 2001). Examining CPF-approved equity funds therefore facilitates direct comparison of similar funds. Among these funds, those investing only in the domestic stock market were selected. Excluded from the research sample were funds based on benchmarks other than the Singapore Straits Times Index, as each benchmark has a unique market cycle. As funds investing only in the local stock market have the same risk classification, this approach controls for differing systematic risk.

Measurement of Expense Ratio and Fund Size

For this research, quarterly expense ratio secondary data were calculated according to guidelines developed by the Investment Management Association of Singapore (IMAS). According to IMAS guidelines, the ratio is considered as operating costs (including but not limited to administration fee, amortised expenses, audit fees, custodian and depository fees, goods and services tax on expenses, management fee, printing and distribution costs, registrar fees and trustee fee) expressed as percentage of fund's average nett assets for a given time period. IMAS guidelines require the ratio to be calculated by taking average of annualised expense ratios for two previous six-month periods. For feeder funds, the ratio is to be calculated as sum of annualised expense ratios of Singapore feeder fund and parent fund to facilitate comparability with direct investment funds (S&P, 2003-2004).

For fund size, Indro et al (1999) measured it using monthly nett assets under management. As quarterly data were used for this research, fund size was measured using net assets under management at the end of each quarter.

Survivorship Bias 

When collecting expense ratio and fund size data, consideration for survivorship bias was incorporated. As non-surviving funds are usually the worst performing, when data for non-survivors are not considered, resulting average performance of each fund group can be overstated.

To control for survival bias, this study collected data for surviving and non-surviving funds using quarterly reports for all CPF-approved unit trusts.

Hypothesis Testing 

To test hypothesis for no significant performance difference between two groups of funds, two-tailed pooled-variance t-test for difference in two means was conducted for returns of the fund groups during the two holding periods 1999-2002 and 2003-2004 at an alpha level of 0.05. To categorise each fund as big or small for the first hypothesis, funds were ranked by average assets under management for each time period in descending order, with top and bottom half being big and small funds respectively. Similarly, for the second hypothesis, funds were categorised into high or low expense ratio groups by ranking their expense ratios for each holding period in descending order, with top and bottom half being high and low expense ratio funds respectively.

Results and Interpretation

Summary characteristics of Singapore's CPF-approved domestic equity funds are tabulated in Table 2.

Performance of Large and Small Funds

Referring to Table 3, during 1999-2002, average return of big funds was 4.29 per cent, versus 0.96 per cent for small funds. For 2003-2004, large funds' return of 7.37 per cent continued to outperform small funds return at 5.84 percent.

Performing a two-sample t-test assuming unequal variances for returns of big and small funds showed significant out-performance of small funds by large ones during 1999-2002, but no significant performance difference during 2003-2004.

Performance of High and Low Expense Ratio Funds

As presented in Table 4, during 1999-2002, average return of funds with low expense ratios was 2.56 per cent, which was lower than 2.69 per cent average return of high expense ratio counterparts. For 2003-2004, the reverse happened as average returns of low and high expense ratio funds were 7.21 and 6.00 per cent respectively.

However, performing a two-sample t-test assuming unequal variances for returns of high and low expense ratio funds showed no significant performance differences during the two periods.

Expense Ratio of Large and Small Funds

From Table 5, during 1999-2002, average expense ratio of big funds at 1.54 was lower than small funds' at 2.17. For 2003-2004, average expense ratio of big funds at 1.30 continued to be lower than small funds at 1.99.

Performing a two-sample t-test assuming unequal variances for expense ratios of big and small funds showed no significant expense ratio differences for big and small funds during the two periods.

Conclusion and Recommendation

Even though there is evidence that large funds outperformed small funds, better performance of large funds was not significant for all holding periods tested, which is agreeable with findings from the USA (Cicotello and Grant, 1996; Droms and Walker, 1994; Grinblatt and Titman, 1994), Australia (Bird, Chin and McCrae, 1983; Gallagher, 2003; Gallagher and Martin, 2005) and Sweden (Dahlquist, Engstrom and Soderlind, 2000). As for expense ratio, the results seemed contradictory for different holding periods, and relation between expense ratio and re turns was insignificant, supporting findings from Ippolito (1989). Even though big funds seemed to have lower expense ratios than small funds, suggesting economies of scale, difference in expense ratio was insignificant.

To explain these results, the insignificance of fund size and expense ratios in affecting returns could be attributable to dominance of asset allocation determinant, which was demonstrated by Brinson, Hood and Beebower (1986), Brinson, Singer and Beebower (1991), as well as Ibbotson and Kaplan (2000) in the USA, and in Singapore by Tng (2005). According to Tng (2005), close to 90 per cent of variability in returns of CPF-approved domestic equity funds can be explained by asset allocation policy.

This research examined effects of expense ratio and size on fund performance in a small and developed equity market. In such a market, large funds cannot provide significant economies of scale to lower expenses or provide better returns than small funds. Besides, higher expenses cannot produce better returns. For further research, turnover ratio may be incorporated as a measure of explicit transaction cost to examine significance of this factor as a fund performance determinant in various equity markets.

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Tng Cheong Sing

Southern Cross University, Australia

Table 1: Research Sample

Organisation   Fund                        Symbol   1999-     2002-
type                                                2002      2004

Bank           DBS Horizon Singapore
                 Equity Fund               DHSE     [check]   [check]
               DBS Shenton Thrift Fund     DST      [check]   [check]
               OCBC Savers Singapore
                 Trust Fund                OSST     [check]   [check]
               OUB Union Singapore
                 Equity Fund               OUSE     [check]
               UOB Optimix Singapore
                 Equity Fund               UOSE     [check]   [check]
               UOB Unifund                 UU       [check]
               UOB United Growth Fund      UUG      [check]   [check]

Insurance      AXA Life-Fortress Fund      ALF      [check]   [check]
Company        AXA Life-Fortress Fund A    ALFA               [check]
               GE Greatlink Singapore
                 Equities Fund             GGSE               [check]
               Keppel Managed Fund         KM       [check]
               NTUC Income Singapore
                 Equity Fund               NISE               [check]
               OUB Manulife Golden
                 Singapore
               Growth Fund                 OMGSG    [check]
               UOB Life FOF-Unifund        ULFU     [check]
               UOB Life FOF-United
                 Growth Fund               ULFUG    [check]   [check]
               UOB LifeLink Growth Fund    ULG      [check]
Investment     Aberdeen Singapore Equity
Company          Fund                      ASE      [check]   [check]
               CMG First State Singapore
                 Growth Fund               CFSSG    [check]
               Schroder Singapore Trust    SST      [check]   [check]

Source: Funds identified from Mercer (1999-2002) and S&P (2003-2004)
data.

Table 2: Summary Characteristics of Singapore's CPF-approved
Domestic Equity Funds

Fund    Type                 1999:Q2 to 2002:Q1

                      Average         Size       Expense
                     quarterly    (S$ million)    ratio
                     return (%)

SST     Investment      7.32         113.42       1.71
UUG     Bank            4.51         103.33       1.36
ULFUG   Insurance       6.03          91.65       1.35
CFSSG   Investment      5.36          86.33       2.35
DHSE    Bank           -0.46          75.31       1.50
DST     Bank            4.33          43.96       0.96
UU      Bank            0.23          35.96       1.57
ULFU    Insurance       7.00          35.05       1.55
OMGSG   Insurance      -0.66          19.56       2.04
ALF     Insurance       2.05          17.72       1.45
OSST    Bank            4.53          17.03       1.49
KM      Insurance       0.12          10.58       1.16
ASE     Investment      5.84           6.97       2.58
OUSE    Bank           -6.13           3.00       3.32
UOSE    Bank            2.57           2.57       3.83
ULG     Insurance      -0.64           0.41       1.51
ALFA    Insurance
GGSE    Insurance
NISE    Insurance

Fund            2003:Q1 to 2004:Q3

         Average         Size       Expense
        quarterly    (S$ million)    ratio
        return (%)

SST        6.01         238.16       1.52
UUG        6.39         125.20       1.18
ULFUG      6.11          84.23       1.18
CFSSG
DHSE       7.28         109.26       1.49
DST       12.30          59.50       1.16
UU
ULFU
OMGSG
ALF        6.11          62.20       1.24
OSST       7.49          19.06       1.52
KM
ASE        5.59          21.11       2.12
OUSE
UOSE       4.93           0.85       5.02
ULG
ALFA       4.71          45.19       1.67
GGSE       4.88          30.31       1.20
NISE       7.45           1.69       0.43

Note: Type refers to the financial institution managing the
fund-bank, insurance or investment companies.

Source: Developed using Mercer (1999-2002) and S&P (2003-2004) data.

Table 3: Two-sample t-test Assuming Unequal Variances for
Returns of Big and Small Funds

[alpha] = 0.05

1999:Q2 to 2002:Q1

                                          Big fund   Small fund

Mean return (%)                            4.29          0.96
Variance                                   8.542        13.785
Observations                               8             8
Hypothesised Mean Difference               0
Df                                        13
t Stat                                     1.993
P(T [less than or equal to] t) one-tail    0.034
t Critical one-tail                        1.771
P(T [less than or equal to] t) two-tail    0.068
t Critical two-tail                        2.160

2003:Q1 to 2004:Q3

                                          Big fund   Small fund

Mean return (%)                            7.37         5.84
Variance                                   6.060        1.681
Observations                               6            6
Hypothesised Mean Difference               0
Df                                         8
t Stat                                     1.343
P(T [less than or equal to] t) one-tail    0.108
t Critical one-tail                        1.860
P(T [less than or equal to] t) two-tail    0.216
t Critical two-tail                        2.306

Source: developed using Mercer (1999-2002) and S&P (2003-2004) data.

Table 4: Two-sample t-test Assuming Unequal Variances for
Returns of High and Low Expense Ratio Funds

[alpha] = 0.05

1999:Q2 to 2002:Q1

                                          Low expense   High expense
                                             ratio         ratio

Mean return (%)                               2.56          2.69
Variance                                      6.919        21.735
Observations                                  8             8
Hypothesised Mean Difference                  0
Df                                           11
t Stat                                       -0.07
P(T [less than or equal to] t) one-tail       0.473
t Critical one-tail                           1.796
P(T [less than or equal to] t) two-tail       0.945
t Critical two-tail                           2.201

2003:Q1 to 2004:Q3

                                          Low expense   High expense
                                             ratio         ratio

Mean return (%)                               7.21          6.00
Variance                                      6.897         1.367
Observations                                  6             6
Hypothesised Mean Difference                  0
Df                                            7
t Stat                                        1.027
P(T [less than or equal to] t) one-tail       0.169
t Critical one-tail                           1.896
P (T [less than or equal to] t) two-tail      0.339
t Critical two-tail                           2.365

Source: Developed using Mercer (1999-2002) and S&P (2003-2004) data.

Table 5: Two-sample t-test Assuming Unequal Variances for
Expense Ratios of Big and Small Funds

[alpha] = 0.05

                                          Big fund   Small fund

Mean expense ratio                          1.54        2.17
Variance                                    0.156       0.957
Observations                                8           8
Hypothesised Mean Difference                0
Df                                          9
T Stat                                     -1.686
P(T [less than or equal to] t) one-tail     0.063
T Critical one-tail                         1.833
P(T [less than or equal to] t) two-tail     0.126
T Critical two-tail                         2.262

                                          Big fund   Small fund

Mean expense ratio                          1.30        1.99
Variance                                    0.027       2.516
Observations                                6           6
Hypothesised Mean Difference                0
Df                                          5
T Stat                                     -1.072
P(T [less than or equal to] t) one-tail     0.166
T Critical one-tail                         2.015
P(T [less than or equal to] t) two-tail     0.333
T Critical two-tail                         2.571

Source: Developed using Mercer (1999-2002) and S&P (2003-2004) data.