L. J. PRATHER

Table 3.

Homogeneity of Systematic Risk within CDA Investment Objective Cla-

Index (F value)

sses.

Investment Number of Funds CRSP EWMSCI

Objective CRSP VW

AG 43 3.135** 2.135** 0.506

(G) 112 1.094 0.995 0.94/0.38

(GI) 66 7.286** 9.962** 2.538**

(B) 36 4.752** 0.999 1.471*

(BP) 66 1.937** 2.585** 2.047**

Note: T presents reshe onOVto df

be

his tableults of te-way ANA F-test etermine i

risk differences observed in Table 2 are statistically significant or whether they

can be attributed to chance. Column one provides the CDA investment objective

and column two lists the number of funds comprising the sample. Columns three

and four are the ANOVA F-statistics for the tests of the null hypotheses that the

risk for domestic only investors is homogeneous within the investment objective

group. Column five is the ANOVA F-statistic for the test of the null hypothesis

that the risk for globally diversified investors (MSCI) is homogeneous within the

investment objective group. **,*Indicates significance at the 0.01 and 0.05 levels,

respectively.

CRSP EW index and three of the five investment objectives

exhibit heterogeneous risk with the CRSP VW and MSCI in-

dexes. Moreover, two of the five investment objective classes

exhibit heterogeneous risk with all three indexes and another two

of the five investment objective classes exhibit heterogeneous

risk with two of the three indexes.

Differences in Systematic Risk between Load

and No-Load Funds

Chordia (1996) and Malhotra and McLeod (1997) reported

that load funds hold less cash than no-load funds. Presumably,

this is due to a more stable clientele and redemptions that are

more predictable. The act of holding dissimilar amounts of cash

could cause systemic differences in risk between load and

no-load funds. If no-load funds hold more cash and fewer risky

assets, they would be less risky ceteris paribus because the

standard deviation of a portfolio (p) is equal to the product of

the weight in the risky asset (wr) and the standard deviation of

the risky asset (r) or p = wr (r). Therefore, as the propor-

tion of cash increases (wc), the proportion of the total invest-

ment in the risky portfolio (wr) decreases and so does the stan-

dard deviation of the portfolio (p). This would decrease the

systematic risk (β) as well since the beta of a portfolio (βp) can

be expressed as βp= ρ(σp /σm), where ρ is the correlation be-

tween the portfolio and the market and σp

and σm are the portfo-

lio and market variabilities, respectively. Alternatively, the beta

of a portfolio is the weighted sum of the beta of each asset

times the beta of the asset. Because the beta of cash is zero, a

portfolio with higher cash holdings would have a smaller beta

ceteris paribus.

Brown, Harlow, and Starks (1996) found that no-load fund

managers with a poor performance record in the first half of the

year alter risk in the second half of the year to improve per-

formance suggesting that no-load funds investors may be more

sensitive to performance. Chordia (1996) believes that is the

case and that switching costs create differences in loyalty be-

tween load and no-load fund investors. He believes that this

mitigates fund flows for load funds and therefore creates dif-

ferent effects for load and no-load portfolio managers. Therefo-

re, the load structure may explain the documented heterogene-

ous within group risk.

To test the hypothesis that systematic risk is homogeneous

tween the load and no-load funds for each investment objec-

tive, the sample was segmented into two groups, load funds and

no-load funds. This division provides a sample of 180 load

funds consisting of 21 aggressive growth (AG), 52 growth (G),

39 growth and income (GI), 22 balanced (B), and 46 bond and

preferred stock (BP). The remainder of the sample consists of

143 no-load funds broken down into 22 (AG), 60 (G), 27 (GI),

14 (B), and 20 (BP). The monthly returns from each group are

computed to provide an equally weighted 156-month index

return from each group. Using equally weighted indexes is

important since the objective is to determine the similarity of

risk between the average load fund and the average no-load

fund in a selected investment objective. Once the indices were

computed, a modified market model, Equation (4), was used to

determine the relative systematic risk.

–αβ

,, ,,

–ε

DItf tLDLDNLtf tt

RRR R

(4)

where RLDI,t is the return on the load fund index for

ble 4 columns two through four provide the sample size

fo

able 4.

ity of Systematic Risk between Load and No-load Funds.

a given

investment objective group during each month t of the 156-

month sample period, Rf,t is the risk-free rate of interest (90 day

US T-bills), RNLI,t is the return on the no-load fund index for a

given investment objective group during each month t of the

156-month sample period, and αLD and βLD are the estimated

excess risk-adjusted return and systematic risk coefficients of

the load fund index. This permits determining whether the av-

erage risk of load funds differs systematically from that of

no-load funds. If the risk of load and no-load funds is the same,

the estimated βLD coefficient should not differ statistically from

one.

Ta

r the total sample, the load fund sample, and the no-load fund

sample respectively. Column five provides the systematic risk

estimate generated by regressing the returns of the index of load

funds on the index of no-load funds and column six is the ad-

justed coefficient of determination of the model. A beta of one

would suggest equal risk whereas a beta with a confidence in-

terval that excludes one would suggest that risk is significantly

different between the two groups. Results suggest that systemic

differences exist and the differences in risk are significant at

the .05 level. These results are consistent with no-load portfo-

lio managers holding more cash (e.g., Chordia (1996), Mal-

hotra and McLeod (1997)) and having similar risky asset port-

folio compositions. At a minimum, these findings suggest that

T

Homogene

Number of Funds

Investment

Objective Total LoadLD R

2 No-load β

AG 43 21 22 1. 0.030*986

(G) 112 52 60 1.040* 0.991

(GI) 66 39 27 1.099* 0.989

(B) 36 22 14 1.066* 0.972

(BP) 66 46 20 1.099* 0.951

Note: Tle presentltsests of whether siffhis tabs the resu of tystemic derences in

risk exist between load and no-load funds. Column one is the CDA investment

objective group. Columns two through four provide the sample size for the total

sample, the load fund sample, and the no-load fund sample, respectively. Column

five provides the slope estimate generated by regressing the returns of the index

of load funds on the index of no-load funds over the 156-month sample period. A

beta of one would suggest equal risk whereas a beta with a confidence interval

that excludes one would suggest that risk is significantly different between the

two groups. The model below estimates betas:

αβ

,, ,,

ε

DItf tLDLDNLtf tt

RRR R

*Indicates that the .05 confidence interval does not include oe. n

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