returns from investing in australian equity superannuation funds, 1991–1999

Returns from Investing in Australian EquitySuperannuation Funds, 1991–1999

MICHAEL E. DREW and JON D. STANFORD

In this analysis of investment manager performance, twoquestions are addressed. First, do managers that actively tradestocks create value for investors? Second, can the multifactormodel of Gruber capture the cross-section of average fundreturns for the Australian setting? The answers from this studyare as follows: as an industry, investment managers destroyedvalue for superannuation investors for the period 1991 through1999, under-performing passive portfolio returns by 2.80–4.00per cent per annum on a risk-unadjusted basis and 0.50–0.93 percent per annum on a risk-adjusted basis. Evidence is provided insupport of the four-factor model of Gruber; however, the modelfails to capture the impact of investment style for the Australiansetting. The findings suggest that Australian superannuationinvestors would transform their retirement savings intoretirement income more efficiently through the use of passivealternatives to the stock selection problem.

INTRODUCTION

Australia’s three-pillar approach to retirement income policy (age pension,compulsory superannuation and voluntary retirement income savings) hascreated a highly inelastic demand curve for investment managementservices. This has resulted in superannuation funds being one of the mostrapidly expanding categories of financial intermediary in Australia. Forinstance, in 1985 there were fewer than ten funds available for retailinvestors wishing to invest their retirement savings in a single-sectordomestic equities fund, compared with over 130 different options today. Inthe new century, Australians face a marketplace providing an unprecedented

Michael E. Drew, School of Economics and Finance, Queensland University of Technology, GPOBox 2434, Brisbane, 4001, Australia. Jon D. Stanford, School of Economics, University ofQueensland, St Lucia Campus, Brisbane, Queensland, 4072, Australia.

The Service Industries Journal, Vol.23, No.4 (September 2003), pp.12–24PUBLISHED BY FRANK CASS, LONDON

234sij03.qxd 27/06/2003 09:41 2

selection of management styles, investment philosophies and fund mandatesin which to transform retirement savings into retirement income.

This study seeks to examine the efficiency with which active managersconvert retirement savings into retirement income for fund members. Thefindings indicate that the average superannuation fund, specialising in themanagement of domestic stock portfolios, under-performs passive marketindices by about 2.80–4.00 per cent per annum (risk-unadjusted) and0.50–0.93 per cent per annum (risk-adjusted) for the period 1991–1999. Asan industry, investment managers destroy value for superannuationinvestors. The evidence of material under-performance of passivealternatives by the investment management industry does not paint apromising picture of Australia’s current retirement saving arrangements.

RESEARCH PROBLEM

The Australian Prudential Regulation Authority (APRA) [2001] report that,as an asset class, domestic equities account for approximately 37 per cent ofthe assets held by all superannuation funds. As stocks are subject to incomeand capital fluctuations (the degree of risk of this type of asset class ishigher than that associated with most other forms of investment) they havea relatively high expected return. Therefore, long-term investors (such assuperannuation investors) hold stocks with the expectation of achieving realgrowth of retirement savings, with the objective of accumulating sufficientcapital to privately fund consumption throughout retirement.

This raises the problem of how to manage that portion of superannuationsavings allocated to domestic equities. In solving this problem, researchersover the last two decades have asked: do investment managers who activelytrade stocks add value? Answers to this question have been provided on theone hand by the various active stock selection techniques employed bypractitioners, and on the other by the academy’s received statement ofcapital market efficiency, the efficient market hypothesis (EMH). Researchfrom the United States by Malkiel [1995] and Gruber [1996] and the UnitedKingdom by Bal and Leger [1996] and Leger [1997] finds that theinvestment management industry, on average, destroys value for investorsthrough under-performing benchmark returns. For instance, Gruber [1996]reports that the average equity mutual fund under-performs index returns bysome 65 basis points per annum for the period 1985 through 1994.1

Investment managers engaged in active selection assume that historicalinformation (e.g., past price behaviour, publicly available information)embodies information concerning the future performance of stocks. Thedecision to adopt an active approach is based on the premise that, through asuperior analysis of information, the fund manager can earn economic rents

13RETURNS FROM SUPERANNUATION FUNDS

234sij03.qxd 27/06/2003 09:41 Page 13

(superior risk-adjusted returns) for the superannuation investor. From aproduction function perspective, active investment management is highcost, with firms employing investment managers, economists, analysts andtraders to construct and trade the stock portfolio.

The EMH suggests that, in a liquid market characterised by a largenumber of rational, expected-utility maximising participants makingunbiased forecasts of the future, stocks will be appropriately priced andreflect all available information. If the stock market is efficient in aninformational sense, no information or analysis can be expected to result inthe fund manager earning superior risk-adjusted returns or economic rents[Fama, 1970]. Unlike its active counterpart, the production of an indexedportfolio is very low cost, with stock selection for the portfolio reflecting thecomposition and contribution of individual stocks to the relevant benchmark.

The capital market efficiency debate is of particular relevance toAustralia’s superannuation arrangements. Superannuation is theCommonwealth Government’s preferred system for the provision ofretirement savings for Australians. The importance of superannuation forthe real sector cannot be underestimated. Superannuation is now the secondmost important asset (after the home) for Australians, with an averageaggregated superannuation membership balance of AUD 60,000 [APRA,2001]. It is not unreasonable to suggest that the impact of increasingcontributions (the Superannuation Guarantee Levy is scheduled to increaseto nine per cent over the next three years), with the compounding of returnson these savings, will result in superannuation being the most importantasset for Australian households within a generation. Given the long-termnature of superannuation investment,2 even small amounts of return under-performance by investment managers, when compounded over, say, 40years of working life, will have material impacts on the final pool ofretirement savings (and therefore retirement income) for the member. Thismakes it timely to investigate the efficiency with which funds transformretirement savings into retirement income.

DATA COLLECTION

Morningstar Research Pty Ltd (Morningstar), an independent measurementservice in Australia, provided monthly return observations (net ofmanagement fees, excluding entry and exit loads) for every retailsuperannuation fund classified as ‘Retail superannuation fund Australianequity – general’, from January 1991 through December 1999. The sampleof 148 funds is complete in the sense that it contains all of the funds withno missing data and was maintained by the same independent datacollection agency throughout the period.

14 THE SERVICE INDUSTRIES JOURNAL

234sij03.qxd 27/06/2003 09:41 Page 14

The sample contains three distinct cohorts within the retail classification:open-end, closed-end and non-surviving. The retail open-end cohort consistsof superannuation funds that are structured to accept investments fromindividuals. These funds are pooled and invested by a fund manager in aportfolio of general Australian equities. A typical retail fund requires aminimum initial investment of AUD 2,000, with minimum monthlycontributions of AUD 100. Retail open-end funds allow investors to buy andsell at a unit price based on the appraised value of total assets. Investors canleave and enter at any time and assets may be continually added to the fund.A total of 68 retail open-end funds are investigated in this study.

Closed-end retail funds no longer accept new investors or newinvestments from existing unitholders. These are usually difficult funds forinvestors to exit owing to a lack of liquidity in the fund’s underlyinginvestments. However, due to the fund being closed-end in nature, it permitsthe investment manager to be largely unaffected by the impact of largecapital inflows from superannuation investors. This provides the managerwith a degree of certainty regarding the assets under management. Despitethe issues relating to exiting such funds, retail superannuation investors arelarge users of these closed-end products. A total of 67 retail closed-endfunds are examined in this study.

The retail non-surviving cohort is comprised of retail funds that werefinalised (merged or terminated) during the sample period. The decision tofinalise a fund is typically made by the trustee on commercial grounds (suchas the pool of assets under management is no longer large enough to warrantthe continuation of the fund). The inclusion of the non-surviving cohortlargely mitigates the methodological flaw of survivorship bias for the study[Malkiel, 1995; Drew and Stanford, 2001a]. A total of 13 retail funds wereterminated over the sample period.

A final note of interest regarding the sample relates to the stock selectionpolicy of each of the funds. The trustee of every fund investigated in thisstudy struck an active stock selection mandate with managers. This impliesthat the trustee of each fund is of the belief that the managers employed aresuperior analysts, having the ability to consistently earn economic rentsthrough stock picking. While this decision has a number of legalimplications for trustees [Drew and Stanford, 2001b; Drew, Stanford andTaranenko, 2001; Drew, Stanford and Veeraraghavan, 2002], it has resultedin Australia’s retail superannuation fund industry being characterised as ahigh-cost producer of investment management services.

The average fund investigated in the study charged investors amanagement fee of 1.8 per cent per annum (with a range 1.5–2.5 per centper annum). As there are no strictly passive alternatives for retail investors,a survey of twenty-one US passive investment managers (indexed against


234sij03.qxd 27/06/2003 09:41 Page 15

the S&P 500) listed at Indexfunds.com was undertaken to provide a guideto the cost of a passive alternatives. The results of the survey showed thatan average index fund charged a management fee of 0.33 per cent perannum (with a range of 0.15–0.55 per cent per annum), some 150 basispoints below the Australian active fund average. It is also important to notethat the estimates provided later in this article ignore the impact of entry andexit loads, as this study is concerned with the skill of active managers. Theaverage entry load for the sample was 3.7 per cent, with an average exit feeof 2.0 per cent. This compares with nil entry and exit loads for all US indexfunds. The international comparison of management fees and entry and exitloads highlights the premium paid by Australian superannuation investorswith funds under active management.

METHODOLOGY

The techniques employed by researchers to evaluate the value of activemanagement are categorised under two classifications: risk-unadjustedreturns (preliminary model) and risk-adjusted returns (multifactor model).

Risk-unadjusted Returns

The preliminary model of manager evaluation employed in this study is arudimentary, risk-unadjusted measure of return relative to the market.Preliminary estimates of average performance are obtained from:

Rit – Rmt (1)

where:

Rit = return on fund i in month t;Rmt = return on the Australian Stock Exchange Top 100 accumulation

index in month t.

The limitations of the preliminary model are well documented. Tucker et al.[1994] argue that the most egregious error committed during anyassessment of manager performance is conducting a comparison of fundreturns without consideration of differential fund risk levels. Further,Tucker et al. [1994] observe that while the researchers have been aware ofthe need to account for differential risk for more than 30 years, practitionersand investors often persist in ignoring this critical issue.

Risk-adjusted Returns

Campbell [1996] argues that one of the important problems of modern


234sij03.qxd 27/06/2003 09:41 Page 16

financial economics is the quantification of the trade-off between risk andreturn. Although it is generally held that risky investments will generallyyield a higher return than investments free of risk, it was only with thedevelopment of the capital asset pricing model (CAPM) that researcherswere able to quantify risk and the reward for its adoption [Sharpe, 1964;Linter, 1965]. The defining feature of the CAPM is that expected returns ofan asset must be linearly related to the covariance of its return with thereturn of the market portfolio.3

However, recent research has found that the single-factor CAPM islimited in its ability to capture the cross-sectional variation of stock returns[Fama and French, 1992; Malkiel and Xu, 1997; Drew and Veeraraghavan,2001] resulting in the development of multifactor asset pricing models. Thisstudy (as with all evaluation studies) is then faced with the controversialissue of selecting the factors to be included in the model that explain thecross section of expected returns in equity markets. Gruber [1996] suggeststhat researchers can resolve this problem through selecting factors formanager evaluation that span the major types of securities held by the fund.

The philosophical stance adopted by this study was to select benchmarksthat reflected the universe of securities from which managers can select tobuild a domestic stock portfolio. To be classified by Morningstar as a ‘retailsuperannuation fund Australian equity – general’ the fund must hold aminimum of 80 per cent of portfolio assets in general Australian equities,with a maximum of 20 per cent of portfolio assets in domestic fixed interestsecurities. The typical mandate of the funds investigated in this studyrestricts the majority of investment to large capitalisation stocks comprisingthe Australian Stock Exchange (ASX) Top 100 index.

Following the parameters set by the typical trust deed of superannuationfunds, the ASX Top 100 accumulation index is used as the key proxy for themarket portfolio, with the ASX Top 20 accumulation index used as aconfirmatory market proxy. Moreover, if managers are attempting toundertake strategic behaviour through investing in small capitalisationequities [Banz, 1981], implementing a value stock selection style[Rosenberg, Reid and Lanstein, 1985] and actively switching between stockand bonds [Gruber, 1996] these effects are captured by the multifactormodel. Given that this study examines funds with a mandate to out-performa broad stock accumulation index (as with Ferson and Schadt [1996];Gruber [1996] and Zheng [1999]), a multifactor model is developed for theAustralian setting. Specifically, the four-factor model employed in thisstudy examines market, size, style and bond factors [Gruber, 1996].

Rit–Rft=αi+βmt(Rmt–Rft )+βsi(Rst–Rlt )+βgi(Rgt–Rvt )+βdi(Rdt–Rft )+εi (2)


234sij03.qxd 27/06/2003 09:41 Page 17

where:

αi = risk-adjusted excess return measured from the four-factormodel;

Rit = return on fund i in month t;Rft = yield on the Reserve Bank of Australia 13-week Treasury Note

in month t;Rmt = return on the Australian Stock Exchange Top 100 accumulation

index in month t (market factor or single-factor CAPM);Rst–Rlt = difference in return between a small capitalisation portfolio and

a large capitalisation portfolio based on Australian StockExchange-Frank Russell Company indices in month t (sizefactor4);

Rgt–Rvt = difference in return between a growth portfolio and a valueportfolio based on Australian Stock Exchange-Frank RussellCompany indices in month t (style factor);

Rdt–Rft = difference in return on a bond index that representsCommonwealth, semi-government and corporate bonds acrossall maturities, based on the Warburg Dillon Reed CompositeBond (All Maturities) accumulation index in month t (domesticfixed interest factor); and,

βki = sensitivity of difference in return on fund i to portfolio k, wherek can represent the market, size, style or domestic fixed interestfactor.

Following Gruber [1996], it is important to note that the indices inEquation 1 are constructed as zero investment portfolios. This implies thatthe intercept (α) of a time series regression of a random portfolio against theindices should be zero.

ANALYSIS

The investment managers investigated in this study engage in active stockselection on behalf of superannuation investors. These managers challengethe EMH proposition that a passive stock selection strategy will beunbeatable by any active asset selection strategy over the long term, assecurity prices fully reflect available information. This section finds thatactive managers evaluated using risk-unadjusted and risk-adjustedmethodologies, under-perform market benchmarks (ASX Top 100 and Top20 accumulation indices). The analysis commences with the risk-unadjustedmodel of fund manager performance described in Equation 1 and is shownin Table 1.


234sij03.qxd 27/06/2003 09:41 Page 18

An examination of risk-unadjusted fund returns finds that managersunder-perform the market by between –280 to –394 basis points per annum.As previously discussed, meaningful deductions cannot be made withoutadjusting fund manager return for risk. Moreover, the preliminary modelignores that fact that managers in this study can hold up to 20 per cent offund assets in domestic fixed interest securities. Table 2 presents multifactorrisk-adjusted estimates as described in Equation 2.

The multifactor estimates in Table 2 provide evidence on the limitationsof using the preliminary model. Estimates from the multifactor modelillustrate that the average fund in the sample had an estimated βm of lessthan one (the average was in the range of 0.62 to 0.85 with the marketportfolio having a β of 1). Therefore, the preliminary model, as expected,tends to provide estimates that understate performance due to the manager’sallocation to domestic fixed interest securities. The multifactor model doesa sound job of capturing the cross-section of manager performance,explaining some 84 per cent of the variability of returns.

The multifactor model estimates suggest that managers under-performthe market by a range of –50 to –93 basis points per annum. Moreover, theevidence presented on the other three explanatory variables (size, style anddomestic fixed interest securities) illuminates some important issues forsuperannuation investors.

First, an examination of the regression coefficients in Table 2 suggeststhat the funds investigated during the sample period held equities that were


TABLE 1

RISK-UNADJUSTED RETURN ESTIMATES

Cohort Rit–Rmt

Rmt = ASX Top 100 accumulation indexRetail open-end –0.1901Retail closed-end –0.2053Retail non-surviving –0.6066All retail funds –0.2336Basis points (p.a.) –280

Rmt = ASX Top 20 accumulation indexRetail open-end –0.3064Retail closed-end –0.2946Retail non-surviving –0.6142All retail funds –0.3281Basis points (p.a.) –394

The excess return, Rit–Rmt is the difference between the return on fund i in month t and theAustralian Stock Exchange (ASX) Top 100 Accumulation Index (with the ASX Top 20Accumulation index used as a confirmatory proxy). This excess return methodology reflects thecontributions of Malkiel [1995] and Gruber [1996]. Performance measures are in percentagereturn per month, on an equal-weight basis.

234sij03.qxd 27/06/2003 09:41 Page 19

TA

BL

E 2

RIS

K-A

DJU

ST

ED

RE

TU

RN

ES

TIM

AT

ES

Coh

ort

α mβ s

β gβ d

R2

adj

D–W

Rm

t=A

SX T

op 1

00 a

ccum

ulat

ion

inde

xR

etai

l ope

n-en

d–0

.028

2 (t

=0.

14, s

e=0.

209)

0.85

21 (

t=20

.12,

se=

0.05

8)0.

1797

(t=

2.77

, se=

0.07

8)0.

1147

(t=

0.92

, se=

0.11

4)0.

3579

(t=

2.64

, se=

0.20

2)0.

8377

(df

=59

)2.

185

Ret

ail c

lose

d-en

d–0

.067

1 (t

=–0

.66,

se=

0.15

1)0.

8096

(t=

24.7

5, s

e=0.

043)

0.14

26 (

t=2.

78, s

e=0.

056)

–0.0

266

(t=

–0.0

4, s

e=0.

091)

0.34

44 (

t=3.

54, s

e=0.

111)

0.82

13 (

df=

81)

2.19

0R

etai

l no

n-su

rviv

ing

–0.2

541

(t=

–0.8

5, s

e=0.

264)

0.62

11 (

t=8.

49, s

e=0.

083)

0.24

83 (

t=2.

48, s

e=0.

105)

0.06

23 (

t=0.

41, s

e=0.

167)

0.59

68 (

t=3.

37, s

e=0.

197)

0.66

20 (

df=

53)

2.04

6A

ll re

tail

fund

s–0

.041

6 (t

=–0

.44,

se=

0.18

6)0.

8212

(t=

22.7

2, s

e=0.

058)

0.16

95 (

t=2.

76, s

e=0.

073)

0.04

75 (

t=0.

48, s

e=0.

110)

0.37

22 (

t=3.

12, s

e=0.

170)

0.82

11 (

df=

68)

2.13

Bas

is p

oint

s (p

.a.)

–50

Rm

t=A

SX T

op 2

0 ac

cum

ulat

ion

inde

xR

etai

l ope

n-en

d–0

.024

9 (t

=–0

.11,

se=

0.23

2)0.

8313

(t=

16.4

6, s

e=0.

065)

0.33

45 (

t=4.

49, s

e=0.

089)

0.03

81 (

t=0.

41, s

e=0.

132)

0.31

78 (

t=2.

16, s

e=0.

188)

0.80

71 (

df=

59)

2.10

6R

etai

l clo

sed-

end

–0.1

034

(t=

–0.7

4, s

e=0.

166)

0.79

11 (

t=20

.02,

se=

0.04

8)0.

2861

(t=

4.93

, se=

0.06

5)–0

.048

3 (t

=0.

13, s

e=0.

099)

0.32

24 (

t=2.

85, s

e=0.

123)

0.79

68 (

df=

81)

2.19

5R

etai

l no

n-su

rviv

ing

–0.2

273

(t=

–0.6

9, s

e=0.

277)

0.59

68 (

t=8.

00, s

e=0.

084)

0.33

68 (

t=3.

16, s

e=0.

115)

0.08

50 (

t=0.

57, s

e=0.

172)

0.58

34 (

t=3.

24, s

e=0.

204)

0.64

22 (

df=

53)

2.05

8A

ll re

tail

fund

s–0

.077

7 (t

=–0

.46,

se=

0.20

6)0.

7931

(t=

17.2

8, s

e=0.

059)

0.31

30 (

t=4.

57, s

e=0.

081)

0.00

21 (

t=0.

08, s

e=0.

121)

0.34

24 (

t=2.

56, s

e=0.

160)

0.78

79 (

df=

68)

2.14

3B

asis

poi

nts

(p.a

.)–9

3

Alp

ha (

α) i

s es

timat

ed f

rom

the

cro

ss-s

ectio

nal

time

seri

es r

egre

ssio

n of

the

exc

ess

fund

ret

urns

on

the

exce

ss m

arke

t re

turn

and

the

mim

icki

ng r

etur

ns f

orth

e si

ze (

Rst

–Rlt)=

styl

e (R

gt–R

vt)

and

bond

(R

dt–R

ft)

fact

ors:

Rit–R

ft=

α i+

β mt(R

mt–

Rft)+

β si(R

st–R

lt)+

gi(R

gt–R

vt)+

β di(R

dt–R

ft)+

ε i.T

he e

xces

s m

arke

t re

turn

=R

mt

–Rft

=is

the

dif

fere

nce

betw

een

the

retu

rn o

n th

e A

ustr

alia

n St

ock

Exc

hang

e (A

SX)

Top

100

Acc

umul

atio

n In

dex

(with

the

ASX

Top

20

Acc

umul

atio

n in

dex

used

as

a co

nfir

mat

ory

prox

y) a

nd th

e re

turn

on

the

Res

erve

Ban

k of

Aus

tral

ia 1

3-W

eek

Tre

asur

y N

ote

in m

onth

t.

The

siz

e fa

ctor

is th

e re

turn

on

the

mim

icki

ng p

ortf

olio

for

the

com

mon

siz

e an

omal

y in

sto

ck r

etur

ns.

The

sty

le f

acto

r is

the

retu

rn o

n th

e m

imic

king

por

tfol

io f

or th

e co

mm

on b

ook-

to-m

arke

t equ

ity a

nom

aly

in s

tock

ret

urns

.T

he b

ond

fact

or is

the

retu

rn o

n th

e m

imic

king

por

tfol

io o

f do

mes

tic f

ixed

inte

rest

sec

uriti

es to

lim

it th

e de

fect

s of

ass

et c

over

age.

The

mar

ket,

size

, sty

le a

nd b

ond

fact

ors

are

cons

truc

ted

follo

win

g th

e de

scri

ptio

ns o

f Fa

ma

and

Fren

ch [

1993

; 199

5; 1

996]

, Gru

ber

[199

6] a

nd Z

heng

[19

99].

β k

is th

e fa

ctor

load

ing

on th

e co

rres

pond

ing

inde

pend

ent v

aria

ble.

All

t-st

atis

tics

are

prov

ided

in th

e br

acke

ts.

Perf

orm

ance

mea

sure

s ar

e in

per

cent

age

retu

rn p

er m

onth

on

an e

qual

-wei

ght b

asis

.

234sij03.qxd 27/06/2003 09:41 Page 20

smaller than the combination of equities in the ASX Top 100 and Top 20accumulation index. This suggests that managers are being strategic in theirbehaviour, investing in small-capitalisation stocks outside popularbenchmarks. The existence of a size factor in the sample provides furtherevidence of the strength of the multifactor model.

Second, a statistically significant explanatory variable was the excessreturn on a portfolio of domestic fixed interest securities above the risk-freerate. This finding highlights that investors engaging specialist domesticstock managers are, typically, investing in a portfolio that has a significantproportion (up to 20 per cent) of return contributed by lower volatile, fixedinterest securities. This relatively high proportion of domestic fixed interestexposure must be incorporated into the superannuation investor’s approachto the asset allocation problem.

Finally, dissimilar to the recent international evidence of Gruber [1996]and Blake and Timmerman [1998], the managers investigated in this studyare not characterised by a particular stock selection style. This is confirmedby the independent variable ‘style’ not being statistically different from zeroat the five per cent level. This issue warrants further investigation.Specifically, the way in which managers actually select stocks requires amore detailed analysis to provide a statistically significant explanatoryvariable for the Australian experience. A direction for future research maytake the form of qualitative techniques (such as fund manager surveys) toshed light on this important issue. This would also assist trustees inselecting or blending different managers to mitigate risk for fund members.

The estimates presented in this section provide no evidence to reject theEMH. As a group, active managers appear to have limited stock selectionability, resulting in the destruction of value for superannuation investors.The economic significance of this finding is that the marginal cost of activestock selection is far greater than its marginal benefit, a finding consistentwith recent evidence from the United States [Rubenstein, 2001].

CONCLUSION

This study of financial intermediaries specialising in the active managementof Australian stock portfolios for superannuation investors provides noevidence that active management adds value. The market for equities inAustralia appears to be remarkably efficient, with asset prices reflectingavailable information. From a policy perspective, Australian superannuationinvestors would achieve their retirement income objectives more rapidly byengaging a low cost fund manager employing a passive technique, or, self-managing the assets using a similar passive strategy [Drew and Stanford,2002, 2003]. For the retail market, this strategy is difficult to implement, witha complete lack of passive alternatives available.


234sij03.qxd 27/06/2003 09:41 Page 21

Gallery, Brown and Gallery [1996: 120] recommend that ‘urgent actionneeds to be taken to address the significant flaws in the current privatesector-based superannuation system’. We echo these sentiments, calling fortrustees to consider, as a matter of priority, the costs of active managementcurrently being borne by superannuation fund members. The evidencepresented in this study suggests that one way through the maze of political,institutional and economic complexity on the way to superannuation reformis to examine the active investment management techniques currentlyemployed by superannuation funds and suggest consideration is given topassive alternatives to the asset selection problem.

ACKNOWLEDGEMENTS

We thank two anonymous referees and Stan Hurn, Tony Makin and Madhu Veeraraghavan forhelpful comments. We thank participants for their input at the Economic Society of Australia(Qld) Inc. workshops on the ‘Performance of Australian Fund Managers’ and ‘Issues inSuperannuation Choice’ and seminars at the Australian National University, Griffith University,Queensland University of Technology and the University of Southern Queensland. Any errorsand omissions are the responsibility of the authors.

NOTES

1. Recent evidence from Wermers [2000] finds that while gross returns from US equity mutualfund holdings outperform a broad market index by 130 basis points per year, the net fundreturns under-perform the same index by 100 basis points per year.

2. Superannuation savings cannot generally be accessed until age 55, scaling up to age 65depending on the contributor’s date of birth.

3. Using the CAPM, a number of measures of investment performance evaluation have beenderived by Sharpe [1964], Treynor [1966], Jensen [1968] and the recent M2 measure ofModigliani and Modigliani [1997]. On a similar sample of funds and time period used in thisstudy, Drew and Noland [2000] report an average monthly industry Sharpe measure of–0.008 (market 0.038), Treynor –0.623 (market 0.147), Jensen’s alpha –0.1616 (market 0.00)and M2 measure 1.14 (1.288). Using each of these single-index measures, approximately 75per cent of the funds delivered performance which was below the risk-adjusted marketreturn, with the remaining 25 per cent of funds achieving superior returns per unit of risk.These results are consistent with the US experience reported by Malkiel and Radisich [2001].For further discussion of these single-index measures in the Australian superannuationcontext see Drew and Noland [2000].

4. The size and growth portfolios were constructed from Australian Stock Exchange-FrankRussell Company indices as follows: (a) the small capitalisation portfolio is the average ofthe return on the Russell Small Value and Russell Small Growth indices; (b) similarly, thelarge capitalisation portfolio is the average return on the Russell Value 100 and RussellGrowth 100 indices; (c) the growth portfolio is the average of the Russell Small Growth andRussell Growth 100 indices; and, (d) the value portfolio is the average of the return on theRussell Small Value and Russell Value 100 indices. A value firm is denoted by a high bookequity (BE) to market equity (ME) ratio, with growth firms characterised by a low BE/MEratio. Small capitalisation firms have a low product of current share price and number ofordinary shares on issue. Australian Stock Exchange indices are value-weighted, and aretherefore dominated by large capitalisation firms.


234sij03.qxd 27/06/2003 09:41 Page 22

REFERENCES

Australian Prudential Regulation Authority, 2001, Insurance and Superannuation Bulletin,January, Canberra: Australian Prudential Regulation Authority.

Bal, Y. and L. Leger, 1996, ‘The Performance of UK Investment Trusts’, Service IndustriesJournal, Vol.16, No.1, pp.67–81.

Banz, R., 1981, ‘The Relation Between Return and Market Value of Common Stocks’, Journalof Financial Economics, Vol.9, No.1, pp.3–18.

Blake, D. and A. Timmermann, 1998, Mutual fund performance: Evidence from the UK, LSEFinancial Markets Group Discussion Paper 307, London: London School of Economics.

Campbell, J., 1996, ‘Understanding Risk and Return’, Journal of Political Economy, Vol.104,No.2, pp.298–345.

Drew, M., and J. Noland, 2000, ‘EMH is Alive and Well’, JASSA: Journal of the SecuritiesInstitute of Australia, No.4, pp.15–18.

Drew, M., and J. Stanford, 2001a, ‘The Impact of Fund Attrition on Superannuation Returns’,Vol.31, No.1, pp.25-32.

Drew, M., and J. Stanford, 2001b, ‘Asset Selection and Superannuation Fund Performance: ANote for Trustees’, Economic Papers, Vol.20, No.1, pp.57–65.

Drew, M. and J. Stanford, 2002, ‘The Economics of Choice of Superannuation Fund’,Accounting, Accountability and Performance, Vol.8, No.1, pp.1–20.

Drew, M. and J. Stanford, 2003, ‘Principal and Agent Problems in Superannuation Funds’,Australian Economic Review, Vol.36, No.1, pp.98–107.

Drew, M., J. Stanford and P. Taranenko, 2001, ‘Hot Hands and Superannuation FundPerformance: A Second Note for Trustees’, Economic Papers, No.4, pp.18–25.

Drew, M., J. Stanford and M. Veeraraghavan, 2002, ‘Selecting Australian Equity SuperannuationFunds: A Retail Investor’s Perspective’, Journal of Financial Services Marketing, Vol.7,No.2, pp.115–28.

Drew, M. and M. Veeraraghavan, 2002, ‘A Closer Look at Size and Value Premium in EmergingMarkets: Evidence from the Kuala Lumpur Stock Exchange’, Asian Economic Journal,Vol.16, No.4, pp.337–51.

Fama, E., 1970, ‘Efficient Capital Markets: A Review of Theory and Empirical Work’, Journalof Finance, Vol.25, No.2, pp.383–417.

Fama, E. and K. French, 1992, ‘The Cross-section of Expected Stock Returns’, Journal ofFinance, Vol.47, No.2, pp.427–65.

Fama, E. and K. French, 1993, ‘Common Risk Factors in the Returns on Stocks and Bonds’,Journal of Financial Economics, Vol.33, No.1, pp.3–56.

Fama, E. and K. French, 1995, ‘Size and Book-to-Market Factors in Earnings and Returns’,Journal of Finance, Vol.50, No.1, pp.131–55.

Fama, E. and K. French, 1996, ‘Multifactor Explanations of Asset Pricing Anomalies’, Journalof Finance, Vol.51, No.1, pp.55–84.

Ferson, W. and R. Schadt, 1996, ‘Measuring Fund Strategy and Performance in ChangingEconomic Conditions’, Journal of Finance, Vol.51, No.1, pp.425–61.

Gallery, N., K. Brown and G. Gallery, 1996, ‘Privatising the Pension’, Journal of AustralianPolitical Economy, No.38, pp.98–124.

Gruber, M., 1996, ‘Another Puzzle: The Growth in Actively Managed Mutual Funds’, Journal ofFinance, Vol.51, No.2, pp.783–810.

Jensen, M., 1968, ‘The Performance of Mutual Funds in the Period 1945–1964’, Journal ofFinance, Vol.23, No.2, pp.389–416.

Leger, L., 1997, ‘UK Investment Trusts: Performance, Timing and Selectivity’, AppliedEconomics Letters, Vol.4, No.4, pp.207–10.

Linter, J., 1965, ‘The Valuation of Risky Assets and the Selection of Risk Investments in StockPortfolios and Capital Budgets’, Review of Economics and Statistics, Vol.47, No.1, pp.13–37.

Malkiel, B., 1995, ‘Returns from Investing in Equity Mutual Funds 1971 to 1991’, Journal ofFinance, Vol.50, No.2, pp.549–72.

Malkiel, B. and A. Radisich, 2001, ‘The Growth of Index Funds and the Pricing of EquitySecurities’, Journal of Portfolio Management, Vol.27, No.2, pp.9–21.


234sij03.qxd 27/06/2003 09:41 Page 23

Malkiel, B. and Y. Xu, 1997, ‘Risk and Return Revisited’, Journal of Portfolio Management,Vol.23, No.3, pp.9–14.

Modigliani, F. and L. Modigliani, 1997, ‘Risk-adjusted Performance’, Journal of PortfolioManagement, Vol.23, No.2, pp.45–54.

Rosenberg, B., K. Reid and R. Lanstein, 1985, ‘Persuasive Evidence of Market Inefficiency’,Journal of Portfolio Management, Vol.11, No.3, pp.9–17.

Rubenstein, M., 2001, ‘Rational Markets: Yes or No? The Affirmative Case’, Financial AnalystsJournal, Vol.57, No.3, pp.15–29.

Sharpe, W., 1964, ‘Capital Asset Prices: A Theory of Market Equilibrium under Conditions ofRisk’, Journal of Finance, Vol.19, No.3, pp.425–42.

Treynor, J., 1966, ‘How to Rate Management of Mutual Funds’, Harvard Business Review,Vol.43, pp.63–75.

Tucker, A., K. Becker, M. Isimbabi and J. Ogden, 1994, Contemporary Portfolio Theory and RiskManagement, New York: West Publishing Company.

Zheng, L, 1999, ‘Is Money Smart? A Study of Mutual Fund Investors Fund Selection Ability’,Journal of Finance, Vol.54, No.3, pp.901–33.

Wermers, R., 2000, ‘Mutual Fund Performance: An Empirical Decomposition into Stock-pickingTalent, Style, Transaction Costs and Expenses’, Journal of Finance, Vol.55, No.4,pp.1655–95.


234sij03.qxd 27/06/2003 09:41 Page 24

returns from investing in australian equity superannuation funds, 1991–1999

Documents