Fund flows and past performance in Australian managed funds

Description
The purpose of this paper is to examine the various segments of the managed funds
market to establish if there is any significant difference in the way the assets are allocated into various
asset categories and if investors base their investment decisions based on the past performance of
the fund.

Accounting Research Journal
Fund flows and past performance in Australian managed funds
Rakesh Gupta Thadavillil J ithendranathan
Article information:
To cite this document:
Rakesh Gupta Thadavillil J ithendranathan, (2012),"Fund flows and past performance in Australian
managed funds", Accounting Research J ournal, Vol. 25 Iss 2 pp. 131 - 157
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Fund ?ows and past performance
in Australian managed funds
Rakesh Gupta
Grif?th Business School, Grif?th University, Nathan, Nathan, Australia, and
Thadavillil Jithendranathan
University of St Thomas, St Paul, Minnesota, USA
Abstract
Purpose – The purpose of this paper is to examine the various segments of the managed funds
market to establish if there is any signi?cant difference in the way the assets are allocated into various
asset categories and if investors base their investment decisions based on the past performance of
the fund.
Design/methodology/approach – An average investor who does not possess superior investment
knowledge may base their investment decision on the past performance of funds resulting in ?ow
based on past performance. This study uses a panel regression model to test the relationship between
net ?ows and past excess returns.
Findings – Signi?cant differences are found in asset allocation between the retail and wholesale
segments. Retail investors prefer less risky investments compared to wholesale investors and have
lower preference for overseas investments. The results indicate that investors base their investment
decisions on the past performance of funds, with the retail segment showing a higher level of in?uence
of past performance, as compared to the wholesale segment. The results further show less evidence of
a reaction to risk among the managed investment categories.
Practical implications – Fund managers use fund performance for marketing purposes and results
of the study may be of importance to the managers and investors in understanding this objective.
The ?ndings are also of signi?cance for policy makers in terms of understanding investor behaviour.
Originality/value – This is the ?rst study of the Australian managed funds industry (including
wholesale and retail funds) that tests the link between past performance and fund ?ows. The study
includes data until June 2008, which includes a period when a number of policy changes occurred in
Australian superannuation industry.
Keywords Australia, Investors, Decision making, Fund management, Managed funds,
Past performance, Funds ?ow
Paper type Research paper
1. Introduction
Australia has the world’s highest per capita investments in managed funds[1], yet
there are relatively few studies on asset allocation and ?ow of funds into these
managed funds. The primary focus of this paper is to study asset allocation patterns
within various subsets of the managed fund industry in Australia and to investigate
whether the ?ow of funds is in?uenced by the past performance of the funds. To the
best of our knowledge this is the ?rst comprehensive study of asset allocation and
performance-?ow relationship of managed funds in Australia[2].
Superannuation funds constitute a signi?cant part of the Australian managed funds.
Since the mid-1980s Australia has instituted a mandatory superannuation retirement
savings scheme, under whichemployees who are subject to labor agreements receive upto
9 percent of their salaryinthe formof superannuationcontributions, rather thanincash[3].
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1030-9616.htm
Fund ?ows in
Australian
managed funds
131
Accounting Research Journal
Vol. 25 No. 2, 2012
pp. 131-157
qEmerald Group Publishing Limited
1030-9616
DOI 10.1108/10309611211287314
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Around 90 percent of the Australian workforce is currently participating in this scheme.
According to the Australian Prudential Regulation Authority statistics, 89 percent of the
superannuation funds allow individual investors choices on the funds within various
asset classes.
The Australian managed fund industry can be broadly divided into retail and
wholesale segments. Within the retail segment there are funds that cater to investors of
superannuation contributions, retirement income and discretionary investments.
Wholesale markets have higher investment requirements and serve mostly
institutional investors. There are more than 20,000 individual funds that cater to
different clientele with allocation of funds into various asset categories. If individual
investors do not have a sophisticated understanding of the ?nancial markets, they may
end up pursuing short-term strategies purely based on past returns of the funds, which
can be detrimental to their long-term investment goals. This study uses quarterly ?ow
of funds and fund return data from 1998 to 2008 to see if there are discernible patterns
in the relationship between these two variables that can lead to identifying aggregate
investment strategies of the fund participants. Understanding of the issue is important
for fund managers who may use their past performance to attract new money into
funds. This is an important consideration in developing policies to provide more
choices for fund members. If members of funds start moving money across funds
based purely on past performance of the funds it may not be an optimal investment
strategy and can lead to adverse outcomes in the longer term.
One of the theoretical explanations for the relationship between the fund ?ows and
the performance of the fund is provided by Gruber (1996). This study classi?es US
investors into sophisticated and “disadvantaged clientele.” “Sophisticated” investors
move their money into funds that are performing well and this explains the increase of
?ows into those funds. “Disadvantaged clientele” is divided into three groups:
(1) Unsophisticated investors who move their money partly based on the in?uence
of advertisements and advice from the ?nancial advisors.
(2) Institutionally disadvantaged investors such as pension accounts where the
choice of funds is restricted by the employment contracts.
(3) Tax disadvantaged investors who are unwilling to sell their holding in one fund
and incur capital gains tax.
The above framework of classifying investors is interesting from the Australian
perspective. In Australia the retail managed funds are primarily focused on small
individual investors who may either be making their superannuation contributions
or non-superannuation discretionary investments. In general, retail investors base their
choice of funds on the advice they receive from ?nancial advisors. Traditionally
?nancial advisors have not charged fees for their services, but were compensated by the
funds they sell[4]. Until 2005, the portability of superannuation funds was restricted
and employees were forced to choose between the various types of funds offered through
their employment contract. There is difference in the taxation of returns from
non-superannuation investments, since they are subject to capital gains taxation.
It is assumed that rational investors will choose a diversi?ed portfolio of assets,
which will maximize their risk adjusted return. As pointed out by Sharpe (1992),
asset allocation accounts for a large part of the variability in the return on a typical
investor’s portfolio. In a portfolio allocation model, expected returns and its variance
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as well as the correlation between the asset returns will determine the weights of each
individual asset in the portfolio. Moving funds into an asset category or a particular
fund based only on its past returns can thus result in sub-optimal allocation.
In this study, we divide the sample by asset categories and use a panel regression
approach to study the relationships between fund ?ows and its past return and risk
performance. The results of the panel regressions show that there is signi?cant
difference in asset allocation between the retail and wholesale segments. Retail
investors prefer less risky investments compared to wholesale investors and they have
lower preference for overseas investments. There is evidence that investors base their
investment decisions on the past performance of funds with the retail segment showing
higher level of in?uence of past performance as compared to the wholesale segment.
There is very little evidence that the investors in both segments attribute signi?cant
importance to the risk aspect of the fund returns.
The rest of the paper is organized as follows. Section 2 covers the literature review,
Section 3 describes the data and Section 4 outlines the methodology used in this paper.
Section 5 analyzes the results and Section 6 concludes the paper.
2. Literature review
An investor may use the past performance as a factor in choosing a fund within an
asset class. The conventional wisdom is that funds with superior performance will
attract new funds and inferior performance will result in out?ows. There are several
studies that examine the relationship between the fund ?ows and performance of the
US mutual fund industry. Ippolito (1992) studied the US mutual funds for the period of
1965-1984 and ?nd a clear underlying movement of investments in the mutual fund
industry toward recent good performers and away from recent poor performers.
The symmetry between the in?ows of good performers and out?ows of poor
performers was studied by Sirri and Tufano (1998) and they ?nd that consumers base
their fund purchase decisions on prior performance information, but do so
asymmetrically, investing disproportionately more in funds that performed very well
during the prior period. Goetzmann and Peles (1996) ?nd a signi?cant relation between
?ows and past returns only for the top quartile of past returns. Atheoretical framework
for analyzing the asymmetry in fund ?ows is provided by Lynch and Musto (2003). The
explanation for the asymmetry in the ?owof funds can be explained by the fact that poor
performance of a fund will result in changes in strategies and/or personnel and hence
past bad performance may not be relevant to the future performance of the fund.
The ?ow-performance relationship of wholesale balanced pooled Australian
superannuation funds was studied by Sawicki (2001) and she ?nds a positive,
statistically signi?cant relationship between recent performance and ?ow of funds, but
not the convexity observed in the US markets. Using a sample of 148 retail equity
superannuation funds Drew et al. (2002) tested the persistence of performance of these
funds and report that the raw risk adjusted returns showed mean reversions and prior
annual performance had little in?uence on future fund returns. Bilson et al. (2005)
tested the performance persistence using a sample of managed growth and managed
stable Australian retail funds. The performance persistence was tested using ?ve
different matrices and they ?nd that the inadequate adjustment of risk may cause
spurious persistence in excess fund returns. The relationship between current-quarter
cash ?ows and past performance was tested by Frino et al. (2005), using a sample
Fund ?ows in
Australian
managed funds
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of 398 Australian managed growth and managed stable funds and they report a
positive relationship between current net cash ?ows and past performance.
In another study, the asset allocation strategies within the Australian equities, ?xed
interest and listed property class of funds were examined by Benson et al. (2007). They
document evidence of momentum investing by fund managers. The absence of
investor sophistication is also evident in the study by Gharghori et al. (2008). They ?nd
little evidence that the Australian investors are able to identify high performing
superannuation funds.
Behavioral biases are also evident in other contexts. Del Guercio and Tkac (2002)
compared the difference in cash ?ows of the US mutual funds and pension funds.
Their results reveal signi?cant difference between the behaviors of the two groups of
investors. Pension fund clients move money away from poorly performing funds and
do not ?ock disproportionately towards recent winners. They also use risk measures,
such as, Jensen’s alpha and tracking error to evaluate the performance of the funds.
On the other hand, mutual fund investors tend to direct their cash ?ows towards recent
winners and do not knowingly use risk-adjusted performance measures. Using daily
net aggregate fund transfers in the US voluntary retirement contribution funds
(401k plan), Agnew and Balduzzi (2010) ?nd that in response to market movements,
investors in these funds shift investments between equities, cash and bonds.
Additionally, Sialm et al. (2012) compare the fund ?ow characteristics of the US de?ned
contribution pension plans and the rest of the mutual funds. Their results reveal that
de?ned contribution fund ?ows are more sensitive to superior and inferior performance
of the funds.
An investor can obtain the information about a fund fromactive and passive sources
and ratings by independent sources, such as, Morningstar can be an important part of
the decision making. The effect of mutual fund ratings by Morningstar on the fund ?ows
is studied by Del Guercio and Tkac (2008). Using a large sample of rating changes by
Morningstar from 1996 to 1999, this study ?nds that the rating changes have a
signi?cant in?uence on the investment allocation decisions of retail mutual fund
investors. A possible explanation for this relationship is that investors view
Morningstar ratings as informative quality measures and use it to channel their
investments. Also using ratings, Gerrans (2004) reports that in a survey of Australian
individual investors 75 percent used fund rating in their decisions to invest. The effect of
rating changes on investor behavior in Australia is further explored by Faff et al. (2007).
Their results indicate that Australian retail investors tend to move toward newly
upgraded funds and withdraw funds from those that are recently downgraded.
Additionally, Watson et al. (2011a) evaluated Australian equity funds using ef?cient
portfolio models and report that ef?cient funds are likely to receive an upgrade in the
medium to long-term. In a recent study, Watson et al. (2011b) ?nd that the ratings of
Australian superannuation funds failed to distinguish between highly performing and
moderately performing funds.
The behavioral aspects of the US discount brokerage investors are studied by
Bailey et al. (2011). Using proxies for the two behavioral biases – disposition effect and
narrow framing – they ?nd that behaviorally biased investors make poor decisions
about expenses, trading frequency and timing. The choice of investment vehicles by
different groups of investors in Australian retirement funds are investigated by
Speelman et al. (2007). Their results provide an interesting insight into the gender
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differences in investment choices. Female investors are more risk averse than male
investors and young female investors exhibit the highest level of risk aversion. As the
investors age, there is an indication they tend to become return-chasers. A survey of
Australian investors by Fry et al. (2007) ?nd support to the behavioral theory of
investor inertia, with few surveyed participants showing an interest in changing their
superannuation fund. Phillips (2011) recently examines the relative risk aversion
coef?cient that characterizes the representative self-managed superannuation fund
investor. He shows that this particular category of investor may be too risk averse to
maximize their expected growth rate of wealth accumulation.
3. Data
Data for this study were obtained from Plan for Life, which is a ?rm of actuaries
and research. The data covers the period from 1991 to 2008 and contains quarterly
information about the funds under management, net cash ?ows, cash in?ows, cash
out?ows and investment earnings. According to the data vendor the information
provided is consistent with the investment and ?nancial services de?nitions. Since
the data pre-September 1998 is sparse and the signi?cant growth in the managed funds
occurred since that date, we use only the fund data for the period fromSeptember 1998 to
June 2008. The total number of funds includedinthe studyis 20,400; of which15,133 were
active as of June 2008, while 3,009 had terminated and 1,898 had transferred to other
funds. There were more than 150 fund families that offered these products.
The funds are categorized according to the investment category[5] and product
markets. For this study we divide the data into retail and wholesale markets. Retail
managed funds have low minimum investment of less than A$5,000 and generally
are marketed through ?nancial advisors. Historically the wholesale funds have higher
minimum investment compared to the retail market and lower fees. Only the unitized
wholesale funds are used in this study. The retail market is further subdivided into
superannuation, discretionary investments and retirement income. The details of funds
under management for each of these categories are shown in Table I. Average funds
under management for the retail segment for the period under study is A$352.3 billion,
and for the wholesale segment it is A$184.8 billion. Within the retail segment the
average superannuation funds under management is A$157.7 billion, non-discretionary
funds under management is A$140.9 billion and the size of retirement income fund is
A$53.7 billion. Average growth rate among the funds is between 11 percent to 16 percent;
with the wholesale segment having the highest annual growth rate of 15.6 percent and
the discretionary investments had the lowest annual growth rate of 11 percent.
Category
Average funds under
management
Funds under
management on
September 1998
Funds under
management
on June 2008
Annual growth
rate (%)
Superannuation 157,695.8 72,192.3 235,825.8 12.57
Non-superannuation 140,927.5 70,401.8 200,854.2 11.05
Retirement income 53,664.8 25,421.8 95,549.7 14.16
Total retail 352,288.1 168,015.9 532,229.7 12.22
Wholesale 184,761.0 63,905.0 273,383.6 15.64
Total 562,328.6 232,675.6 805,613.3 13.22
Table I.
Total investments in
retail and wholesale
products (in Australian
dollars)
Fund ?ows in
Australian
managed funds
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The investments into these funds can be divided into 12 major categories, unit trusts,
master fund investments which are further subdivided into nine more categories.
Allocationof funds into various asset classes is presentedinTable II (Panels A-F) andthe
category descriptions are shown in Table III. For the entire sample the highest average
proportion of investments is in managed funds (31.1 percent). The second highest
investment is in mixed portfolios (14.5 percent), followed by Australian equity
(14.2 percent). The changes in the asset allocation from 1998 to 2008 indicate that the
proportionof managedfunds decreasedfrom39.6 percent to 24.9 percent, while the share
of mixed portfolios increased from 6.3 percent to 22.7 percent. The other asset category
with signi?cant decrease in share is capital guaranteed (11.5 percent to 4.7 percent). Both
Australian equities and overseas investments had signi?cant increase in their share.
In the wholesale category the highest average allocation is in managed funds
(25.8 percent), followed by overseas investments (23.9 percent) and Australian equities
(22.4 percent). There is signi?cant reduction in the share of managed funds in the
wholesale segment from 1998 to 2008 (40.6 percent to 18.7 percent), which is the reason
why its proportional representation decreased in the total sample. The proportions of
Australian equities and overseas investments have increased from 1998 to 2008. One of
the least preferred categories of investment in the wholesale segment is capital
guaranteed (0.03 percent).
The asset allocation in the total retail market is signi?cantly different from the
wholesale market. The highest average allocation is in managed funds (35.1 percent),
followed by mixed portfolios (21.1 percent), cash (12.8 percent) and Australian equity
(10.97 percent). The most interesting difference between the wholesale and retail
segment of the market is the investment in overseas assets. Nearly 24 percent of
wholesale funds are invested in overseas assets, while only 4.5 percent of the retail funds
are invested in overseas assets. Compared to the wholesale funds, a higher proportion
of the retail funds are invested in cash.
Breaking down the retail funds also shows interesting differences in asset allocations.
Managed funds are the most popular asset category for the superannuation
investors (50.4 percent). On the other hand the discretionary investors chose cash as the
most popular type of investment (23.1 percent). Given the fact that it is easier for
discretionary investors to withdraw funds, it is reasonable to assume that they chose
funds with the least amount of risk. The other noticeable difference is the allocation of
funds into Australian equity and overseas investments. Discretionary funds have higher
investments in these categories compared to the superannuation funds. This may be
an indication that there may be a sub-group of discretionary investors who are willing
to invest in assets with higher risks.
The asset allocation pattern of retirement income funds shows clear preference for
less risky assets. After managed funds (39.3 percent), the next highest allocation is into
capital guaranteed. Even among the managed fund category the allocations are
weighted more towards balanced (17.9 percent) than managed growth (13.1 percent).
Both superannuation and discretionary funds have higher proportion of the assets into
the managed growth category.
Superannuation fund-level rates of return (ROR) are calculated as follows:
ROR
i;t
¼
Net earnings after tax
i;t
Size
i;t21
þ
1
2
NF
i;t
ð1Þ
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Category
Average
(%)
September 1998
(%)
June 2008
(%)
Minimum
(%)
Maximum
(%)
Panel A. All products (wholesale and retail)
Australian equity 3.64 2.34 4.30 2.3 4.55
Equity balanced 4.55 3.89 3.88 3.9 5.36
Equity growth 6.05 3.41 6.84 3.4 7.75
Total equity 14.24 9.64 15.01 9.63 17.65
Capital guaranteed 7.74 11.48 4.67 4.2 11.97
Cash 11.04 14.69 10.57 8.9 14.69
Fixed interest 4.73 5.24 4.56 4.1 5.25
Fixed rate 0.16 0.58 0.03 0.0 0.58
Managed balanced 10.52 11.60 9.11 9.0 13.35
Managed growth 15.72 20.17 11.92 11.9 21.08
Managed stable 4.84 7.83 3.82 3.4 7.83
Total managed 31.1 39.6 24.9 24.3 42.3
Mortgage 1.81 2.00 1.58 1.4 2.21
Overseas 1.66 0.78 1.72 0.8 1.93
Overseas – American 0.04 0.07 0.00 0.0 0.07
Overseas – European 0.16 0.24 0.06 0.1 0.31
Overseas – ?xed interest 1.33 1.16 1.43 0.9 1.59
Overseas – global 7.05 3.95 8.05 3.9 9.65
Overseas – Japan 0.07 0.03 0.07 0.0 0.16
Overseas – Paci?c region 0.32 0.30 0.59 0.1 0.68
Total overseas 10.62 6.52 11.92 5.84 14.39
Property 1.28 1.35 1.27 0.9 1.63
Property balanced 0.88 1.00 1.04 0.7 1.15
Property growth 0.57 0.59 0.78 0.4 0.78
Property securities 1.37 1.00 0.96 0.8 1.89
Total property 4.10 3.94 4.05 2.78 5.44
Mixed portfolios 14.49 6.30 22.74 6.3 22.74
Panel B. All wholesale products
Australian equity 2.04 2.49 0.65 0.65 3.40
Equity balanced 6.23 2.72 6.93 2.72 7.60
Equity growth 14.09 8.13 16.22 8.13 18.05
Total equity 22.37 13.34 23.80 11.49 29.05
Capital guaranteed 0.03 0.07 0.01 0.01 0.07
Cash 9.03 14.08 9.50 6.83 14.08
Fixed interest 8.25 7.10 8.27 7.10 10.17
Fixed rate
Managed balanced 8.92 11.35 5.87 5.64 13.95
Managed growth 13.46 22.01 10.99 8.92 22.01
Managed stable 3.38 7.22 1.80 1.55 7.22
Total managed 25.8 40.6 18.7 16.1 43.2
Mortgage 1.48 0.49 2.40 0.45 2.40
Overseas 1.31 1.08 0.18 0.18 2.22
Overseas – American 0.06 0.09 0.01 0.00 0.11
Overseas – European 0.21 0.13 0.11 0.11 0.33
Overseas – ?xed interest 3.93 3.96 4.22 2.78 4.86
Overseas – global 17.62 8.37 21.64 8.37 24.13
Overseas – Japan 0.18 0.09 0.20 0.07 0.45
Overseas – Paci?c region 0.59 0.43 1.54 0.14 1.76
(continued)
Table II.
Investment pro?les
Fund ?ows in
Australian
managed funds
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Category
Average
(%)
September 1998
(%)
June 2008
(%)
Minimum
(%)
Maximum
(%)
Total overseas 23.90 14.15 27.90 11.65 33.85
Property 2.04 3.11 1.74 1.29 4.05
Property balanced 2.16 3.51 2.27 1.69 3.51
Property growth 1.55 1.71 2.20 1.16 2.20
Property securities 2.64 1.27 2.08 1.26 3.89
Total property 8.39 9.59 8.29 5.40 13.64
Mixed portfolios 0.79 0.61 1.16 0.48 1.16
Panel C. All retail products
Australian equity 4.70 2.25 6.37 2.25 6.76
Equity balanced 3.97 4.35 2.53 2.53 4.91
Equity growth 2.30 1.63 2.43 1.63 2.73
Total equity 10.97 8.24 11.33 6.42 14.39
Capital guaranteed 7.91 15.82 3.85 3.5 15.82
Cash 12.76 14.95 11.73 9.6 14.95
Fixed interest 3.22 4.55 2.92 2.7 4.55
Fixed rate 0.24 0.81 0.05 0.1 0.81
Managed balanced 12.07 11.75 11.26 11.1 13.56
Managed growth 17.19 19.36 12.35 12.4 21.98
Managed stable 5.83 8.00 5.03 4.6 8.05
Total managed 35.1 39.1 28.6 28.1 43.6
Mortgage 2.07 2.58 1.26 1.3 2.58
Overseas 1.97 0.66 2.60 0.7 2.67
Overseas – American 0.03 0.05 0.00 0.0 0.07
Overseas – European 0.15 0.28 0.04 0.0 0.35
Overseas – ?xed interest 0.09 0.10 0.08 0.1 0.21
Overseas – global 2.01 2.29 1.54 1.4 3.19
Overseas – Japan 0.02 0.01 0.00 0.0 0.07
Overseas – Paci?c region 0.18 0.25 0.14 0.1 0.48
Total overseas 4.45 3.64 4.41 2.27 7.04
Property 1.00 0.67 1.10 0.5 1.54
Property balanced 0.31 0.06 0.47 0.1 0.62
Property growth 0.10 0.17 0.09 0.1 0.17
Property securities 0.80 0.90 0.44 0.4 0.97
Total property 2.21 1.80 2.10 1.04 3.31
Mixed portfolios 21.07 8.49 33.71 8.5 34.02
Panel D. All retail superannuation products
Australian equity 8.6 4.4 10.7 4.4 11.5
Equity balanced
Equity growth
Total equity 8.6 4.4 10.7 4.4 11.5
Capital guaranteed 6.0 14.3 2.2 2.0 14.3
Cash 6.8 9.1 5.9 4.5 9.1
Fixed interest 2.1 3.3 2.1 1.5 3.3
Fixed rate 0.2 1.0 0.0 0.0 1.0
Managed balanced 20.5 20.3 19.9 18.9 22.6
Managed growth 21.6 23.5 18.1 17.7 26.3
Managed stable 8.3 11.2 6.5 5.8 11.5
Total managed 50.4 55.0 44.5 42.4 60.4
Mortgage
(continued)
Table II.
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Category
Average
(%)
September 1998
(%)
June 2008
(%)
Minimum
(%)
Maximum
(%)
Overseas 3.6 1.3 4.0 1.3 4.6
Overseas – American
Overseas – European
Overseas – ?xed interest
Overseas – global
Overseas – Japan
Overseas – Paci?c region
Total overseas 3.6 1.3 4.0 1.3 4.6
Property 1.6 1.1 1.6 0.8 2.3
Property balanced
Property growth
Property securities
Total property 1.6 1.1 1.6 0.8 2.3
Mixed portfolios 20.8 10.4 29.0 10.4 30.5
Panel E. All retail non-superannuation discretionary products
Australian equity 0.33 0.36 0.29 0.28 0.39
Equity balanced 9.78 10.39 6.71 6.71 11.76
Equity growth 5.72 3.90 6.43 3.90 6.97
Total equity 15.83 14.64 13.43 10.89 19.12
Capital guaranteed 3.50 8.60 1.59 1.4 8.60
Cash 23.14 25.23 22.19 18.2 26.66
Fixed interest 4.91 7.20 3.18 3.2 7.52
Fixed rate 0.00 0.01 0.00 0.0 0.01
Managed balanced 0.73 1.22 0.42 0.4 1.23
Managed growth 13.87 17.48 8.00 8.0 19.10
Managed stable 2.21 3.33 2.15 1.8 3.33
Total managed 16.8 22.0 10.6 10.2 23.7
Mortgage 5.13 6.16 3.33 3.3 6.16
Overseas 0.05 0.06 0.02 0.0 0.08
Overseas – American 0.07 0.13 0.01 0.0 0.16
Overseas – European 0.36 0.67 0.11 0.1 0.85
Overseas – ?xed interest 0.23 0.23 0.22 0.2 0.53
Overseas – global 4.95 5.45 4.09 3.6 7.65
Overseas – Japan 0.04 0.02 0.01 0.0 0.16
Overseas – Paci?c region 0.45 0.60 0.36 0.2 1.15
Total overseas 6.14 7.16 4.82 4.10 10.57
Property 0.07 0.21 0.03 0.0 0.21
Property balanced 0.79 0.14 1.24 0.1 1.58
Property growth 0.25 0.42 0.24 0.2 0.42
Property securities 1.97 2.15 1.17 1.2 2.43
Total property 3.08 2.92 2.69 1.51 4.64
Mixed portfolios 21.46 6.06 38.21 6.1 38.26
Panel F. All retail retirement income products
Australian equity 4.7 1.3 8.4 1.3 9.1
Equity balanced
Equity growth
Total equity 4.7 1.3 8.4 1.3 9.1
Capital guaranteed 25.5 40.3 12.7 12.3 40.3
Cash 2.6 3.1 4.2 2.1 4.2
(continued)
Table II.
Fund ?ows in
Australian
managed funds
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where, Size
i,t21
is the funds under management for the ith fund for the quarter t 2 1
and NF
i,t
is the net fund ?ows for the ith fund for the quarter t. To calculate the average
returns for each category of investment, a value weighted index of individual fund
returns is created. The average returns and standard deviations of these individual
indices are provided in Table IV. Among the various categories of investments, equity
growth funds have the highest quarterly returns of 2.58 percent. As a group Australian
equity funds have the highest quarterly returns, followed by the property funds.
Overseas funds had relatively poor performance except for the Paci?c region equity
funds and ?xed interest and currency funds. Overseas funds had the highest level of
risk as measured by the standard deviation of the quarterly returns, followed by the
property funds and equity funds.
For regression analysis a panel data is created for each individual investment
category. To avoid the survivorship bias, funds that were terminated or transferred are
included in the dataset, provided each fund had at least 24 continuous quarterly data
points. One of the issues that arose in the analysis is the sudden increase or decrease in
net ?ows during a quarter. To address this issue, those outliers in the net ?ows the
data for a quarter where the net ?ows is greater than 0.75 of the funds under
management at the beginning of the quarter, are dropped from subsequent analysis.
4. Empirical methodology
A typical mutual fund investment decision involves two steps – ?rst choose an asset
category and then select a fund within that asset category. The choice of asset category
depends on the investors risk preferences and the choice of the fund may depend on its
past performance. Individual investors are thus concerned about the returns and risks
Category
Average
(%)
September 1998
(%)
June 2008
(%)
Minimum
(%)
Maximum
(%)
Fixed interest 2.0 0.8 4.4 0.6 4.4
Fixed rate 0.9 2.4 0.2 0.2 2.4
Managed balanced 17.9 16.5 12.8 12.8 22.9
Managed growth 13.1 12.7 7.2 7.2 18.6
Managed stable 8.3 11.7 7.6 7.0 11.8
Total managed 39.3 40.9 27.6 27.0 53.3
Mortgage
Overseas 2.3 0.6 4.5 0.6 4.6
Overseas – American
Overseas – European
Overseas – ?xed interest
Overseas – global
Overseas – Japan
Overseas – Paci?c region
Total overseas 2.3 0.6 4.5 0.6 4.6
Property 1.8 0.7 2.2 0.6 3.2
Property balanced
Property growth
Property securities
Total property 1.8 0.7 2.2 0.6 3.2
Mixed portfolios 21.0 9.8 35.9 9.8 35.9
Table II.
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involved in investing. There are various agencies that report the performance of the
funds and individual fund managers also advertise their performance measures.
If investors follow the performance of funds carefully, they will tend to invest more in
funds that perform well in a particular category and withdraw investments from the
poor performing funds.
The most commonly used measure of fund performance is to compare the fund
return with that of a benchmark. In the case of the US markets, Sensoy (2009) points
out that more than one third of the benchmarks used are not correct for the funds’ true
investment style. To avoid this problem we use a value weighted index of fund returns
for each of the fund categories. The quarterly return of each fund and the index are
calculated using equation (1) and the active returns are calculated as:
r
i;t
¼ ROR
i;t
2ROR
Index;t
ð2Þ
The next important factor is to ?nd an appropriate measure for risk. The most commonly
used measures of risk in empirical analysis are Jensen’s alpha, Sharpe ratio and
tracking error. Australian Bureau of Statistics and Australian Prudential Regulation
Investment category
name De?nition
Australian equity Predominantly Australian shares
Capital guaranteed Spread portfolio with predominantly ?xed interest, with some shares in
property, offered by life companies, who offer some levels of guarantee on
capital and accumulated returns
Cash Predominantly short data and at call securities, generally with a maturity date
of less than 90 days
Equity balanced Predominantly Australian shares, where the investments selected are focused
on income producing type investments
Equity growth Predominantly Australian shares, where investments selected are focused on
capital growth type instruments
Fixed interest Commonwealth government and semi-government and corporate debt of
investment grade
Fixed rate Rate and capital are guaranteed at the end of the term of investment
Managed balanced Spread portfolio, with high degree of exposure to ?xed interest and cash, and
Australian and international shares, property
Managed growth Spread portfolio, with high degree of exposure to Australian and international
shares, with some property, ?xed interest and cash
Managed stable Spread portfolio, with high degree of exposure to ?xed interest and cash, with
some Australian and international shares, property, ?xed interest and cash
Mortgage Invested in mortgages
Overseas Predominantly international shares
Overseas – American International shares in US sector
Overseas – European International shares in European sector
Overseas – ?xed int.
and currency
International shares in ?xed interest and currency type instruments
Overseas – global International shares spread across world stock markets
Overseas – Japan International shares in Japan sector
Overseas – Paci?c International shares in Paci?c sector
Property Predominantly invested in actual commercial properties and property
securities
Table III.
Investment category
classi?cations
Fund ?ows in
Australian
managed funds
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Authority report the return of assets andthe standard deviation of the returns as a measure
of risk. The key question is how many investors are aware of the investment style of the
fund and how they evaluate the risk of the fund they are investing in. A survey of the US
mutual fundinvestors byCaponet al. (1996) showedthat only25 percent of the mutual fund
investors knew the investment style of the fund and only 26.7 percent of those surveyed
comparedthe fundreturnwiththe benchmark. They?ndthat 14 percent of the respondents
used standard deviation as the measure of risk and only 4 percent used alpha or Sharpe
measure to identify the risk. In this study we use tracking error[6] as the measure of risk.
An important factor that can in?uence the performance of a fund is its size.
Chen et al. (2004) show that the performance of the funds decreases with size and to
control for the size effect we use the lagged log size of the fund as a control variable. To
adjust for the momentum effect of net ?ows, the lagged value of the net ?ows is
included as an independent variable. A panel data for each of the asset categories is
created using the available quarterly data for the funds and the ?xed effects regression
is conducted using the following equation:
NF
i;t
¼ b
j
r
ji;t
þ cs
i;t21
þ dSize
i;t21
þ eNF
i;t21
þ
X
n
i¼1
FE
i;t
þ 1
t
ð3Þ
where NF
i,t
are the net ?ows, r
ji
, is the trailing excess returns for either 1, 2 or 3
quarters, s
i,t
is the tracking error, Size
i,t
, is the log of the fund size and FE
i,t
is the ?xed
effect of ith fund. We estimated three separate regressions with the variable r
ji,t
being 1,
2 or 3 quarter excess returns.
Investment category name Mean SD Minimum Maximum
Australian equity 0.0219 0.0539 20.1359 0.1006
Equity balanced 0.0250 0.0578 20.1394 0.1157
Equity growth 0.0258 0.0579 20.1402 0.1128
Capital guaranteed 0.0103 0.0014 0.0078 0.0136
Cash 0.0105 0.0013 0.0085 0.0138
Fixed interest 0.0112 0.0091 20.0188 0.0231
Fixed rate 0.0101 0.0017 0.0016 0.0123
Managed balanced 0.0130 0.0323 20.0690 0.0596
Managed growth 0.0122 0.0324 20.0655 0.0621
Managed stable 0.0107 0.0125 20.0306 0.0298
Mortgage 0.0135 0.0013 0.0103 0.0169
Overseas 0.0018 0.0628 20.1295 0.1480
Overseas – American 20.0047 0.0856 20.2028 0.1977
Overseas – European 0.0052 0.0858 20.2239 0.2354
Overseas – ?xed int. and currency 0.0133 0.0141 20.0204 0.0461
Overseas – global 0.0039 0.0760 20.1618 0.1880
Overseas – Japan 0.0090 0.1024 20.2122 0.2519
Overseas – Paci?c 0.0198 0.1121 20.2022 0.2789
Property 0.0188 0.0333 20.0912 0.0875
Property – balanced 0.0219 0.0296 20.0706 0.0713
Property – growth 0.0254 0.0141 20.0113 0.0632
Property securities 0.0181 0.0642 20.1664 0.1225
Mixed portfolios 0.0105 0.0317 20.0835 0.0593
Table IV.
Summary statistics
of quarterly returns
(September 1998-June
2008)
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5. Results
An important result of this study is the statistically strong negative relationship
between the fund size and the net cash ?ows, which has been noted by a number of
other studies. The negative effect is more pronounced in the retail segment. Chen et al.
(2004) and Pollet and Wilson (2008) observe similar negative relationship between the
fund size and fund performance in the US. One possible explanation for this
phenomenon is that when funds grow, they do not increase the number of assets in the
portfolio and this may result in less than optimal allocation of funds. The implication
of this result is that investors, especially retail investors, should be considering the size
of the fund as a factor when they choose a fund.
The results of the panel regression of all retail managed funds are outlined in Table V.
Of the 15 categories of funds, 14 have a positive relationship between the net ?ows and
lagged past excess returns. The only exception is cash funds, which did not show any
signi?cant relationship between the lagged excess returns. The statistical signi?cance of
the coef?cients increases when the lagged returns are averages of the past two and three
quarters, indicatingthat investors are not onlyfocusedonimmediate past excess returns,
but also the cumulative excess returns for a number of quarters. The coef?cients of risk
variable are signi?cant only for cash funds and overseas funds. As expected the signs of
these coef?cients are negative indicating that the net ?ows to funds with high risk
increased. Average retail investor seems to be more in?uenced by the past performance
of the fund rather than the variability of the returns measured by the tracking error.
A possible explanation can be found in the way investors choose their funds using fund
ratings. Unlike the US mutual fund rating methodology, which until recently was
completely based on quantitative assessment, the two major rating agencies in Australia
(Morningstar and Standard & Poor’s) use a mixture of quantitative and qualitative
factors (Faff et al., 2007). Since risk is one of the quantitative variables, its relative weight
within the Australian mutual fund rating system may be lower than in the US.
The momentum of past net ?ows as measured by the lagged net ?ows shows
a statistically signi?cant positive effect. As noted by Frino et al. (2005), this particular
relationship between the past net ?ows and current quarter net ?ows is rather dif?cult
to explain. A possible explanation is that the positive relationship between the past net
?ows with the current period net ?ows can be due to the general growth in the
particular asset class. Gruber (1996) explained such a relationship may have been
due to the fact that investors are locked into a particular fund due to restricted choices
allowed by their pension accounts and this restriction may also be associated with the
effect of marketing and reputation of the fund.
The results of panel regressions of wholesale fund net ?ows are given inTable VI. It is
interesting to note that the effect of lagged excess returns on the net ?ows are only
signi?cant for nine of the 13 categories of investments and even where they are
signi?cant it is when the independent variable is the average excess return for either two
or three quarters. Unlike the retail funds the laggedexcess returns are signi?cant for cash
funds. One possible explanation for the difference between the two categories is that the
wholesale funds have a higher investment threshold and may attract more informed
investors and they may not base their investment decisions purely on past performance.
A more detailed examination of retail funds provides further insight into the
investor behavior. The results of the panel regression of superannuation retail funds
are displayed in Table VII. Out of the ten categories of funds only six exhibited the
Fund ?ows in
Australian
managed funds
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3
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4
.
8
6
1
1
)
*
*
*
(
c
o
n
t
i
n
u
e
d
)
Table V.
Fixed effects panel
regression of retail
managed fund net
?ows with past
excess returns and risk
ARJ
25,2
144
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
F
u
n
d
c
a
t
e
g
o
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y
b
j
(
t
-
s
t
a
t
.
)
c
(
t
-
s
t
a
t
.
)
d
(
t
-
s
t
a
t
.
)
e
(
t
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)
A
d
j
.
R
2
(
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6
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0
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5
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4
)
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6
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3
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6
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2
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4
4
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5
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5
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2
0
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2
2
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4
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6
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0
0
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0
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1
.
7
6
1
9
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3
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7
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1
4
.
8
8
3
8
)
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*
0
.
4
2
1
4
(
4
5
.
3
1
8
8
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0
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3
4
4
9
(
1
2
.
9
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4
3
)
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*
T
w
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a
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s
0
.
4
3
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8
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1
0
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5
2
7
4
)
*
*
*
2
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.
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4
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9
4
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4
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5
5
)
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4
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6
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s
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o
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a
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r
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5
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1
)
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6
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5
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5
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.
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e
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0
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3
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7
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3
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5
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8
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7
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9
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5
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2
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)
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a
r
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s
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4
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.
9
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4
)
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0
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0
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1
4
5
0
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1
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8
.
0
3
3
5
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3
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8
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7
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4
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r
o
p
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y
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e
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i
x
e
d
p
o
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l
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o
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)
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0
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0
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1
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w
o
q
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a
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t
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s
2
0
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0
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6
)
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0
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1
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1
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)
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4
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1
3
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1
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4
)
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3
6
5
4
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0
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4
4
4
7
)
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4
2
3
4
(
2
0
.
1
6
6
1
)
*
*
*
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
t
a
t
:
*
1
0
,
*
*
5
,
*
*
*
1
p
e
r
c
e
n
t
R
e
g
r
e
s
s
i
o
n
e
q
u
a
t
i
o
n
:
N
F
i
;
t
¼
b
j
r
j
i
;
t
þ
c
s
i
;
t
2
1
þ
d
S
i
z
e
i
;
t
2
1
þ
e
N
F
i
;
t
2
1
þ
X
n
i
¼
1
F
E
i
;
t
þ
1
t
w
h
e
r
e
N
F
i
,
t
a
r
e
t
h
e
n
e
t
?
o
w
s
,
r
j
i
i
s
t
h
e
c
u
m
u
l
a
t
i
v
e
e
x
c
e
s
s
r
e
t
u
r
n
s
f
o
r
e
i
t
h
e
r
1
,
2
o
r
3
q
u
a
r
t
e
r
s
,
s
i
,
t
i
s
t
h
e
t
r
a
c
k
i
n
g
e
r
r
o
r
,
S
i
z
e
i
,
t
i
s
t
h
e
l
o
g
o
f
t
h
e
f
u
n
d
s
i
z
e
a
n
d
F
E
i
,
t
i
s
t
h
e
?
x
e
d
e
f
f
e
c
t
o
f
i
t
h
f
u
n
d
;
t
h
r
e
e
s
e
p
a
r
a
t
e
r
e
g
r
e
s
s
i
o
n
s
a
r
e
e
s
t
i
m
a
t
e
d
w
i
t
h
t
h
e
v
a
r
i
a
b
l
e
r
j
i
,
t
b
e
i
n
g
1
,
2
o
r
3
q
u
a
r
t
e
r
e
x
c
e
s
s
r
e
t
u
r
n
s
a
n
d
t
h
e
c
o
e
f
?
c
i
e
n
t
s
o
f
e
a
c
h
r
e
g
r
e
s
s
i
o
n
f
o
r
e
a
c
h
o
f
t
h
e
i
n
v
e
s
t
m
e
n
t
c
l
a
s
s
e
s
a
r
e
g
i
v
e
n
a
b
o
v
e
Table V.
Fund ?ows in
Australian
managed funds
145
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
F
u
n
d
c
a
t
e
g
o
r
y
b
1
(
t
-
s
t
a
t
.
)
c
(
t
-
s
t
a
t
.
)
d
(
t
-
s
t
a
t
.
)
e
(
t
-
s
t
a
t
.
)
A
d
j
.
R
2
(
F
-
s
t
a
t
.
)
C
a
s
h
O
n
e
q
u
a
r
t
e
r
5
.
4
5
1
2
(
2
.
8
0
8
3
)
*
*
*
0
.
0
0
4
4
(
2
.
2
1
9
3
)
*
*
2
0
.
0
2
9
1
(
4
.
0
5
3
7
)
*
*
*
2
0
.
0
2
0
1
(
0
.
6
4
6
9
)
0
.
0
4
8
6
(
2
.
3
2
7
1
)
*
*
*
T
w
o
q
u
a
r
t
e
r
s
7
.
6
8
9
5
(
3
.
2
0
0
3
)
*
*
*
0
.
0
0
3
9
(
1
.
9
3
9
0
)
*
2
0
.
0
2
9
5
(
4
.
1
0
8
3
)
*
*
*
2
0
.
0
2
2
5
(
0
.
7
2
6
9
)
0
.
0
5
0
7
(
2
.
3
8
6
6
)
*
*
*
T
h
r
e
e
q
u
a
r
t
e
r
s
7
.
9
8
5
5
(
2
.
9
1
4
8
)
*
*
*
0
.
0
0
3
7
(
1
.
8
3
4
9
)
*
2
0
.
0
2
9
7
(
4
.
1
4
0
7
)
*
*
*
2
0
.
0
2
4
2
(
0
.
7
7
8
5
)
0
.
0
4
9
1
(
2
.
3
4
2
5
)
*
*
*
E
q
u
i
t
y
O
n
e
q
u
a
r
t
e
r
0
.
0
2
1
0
(
0
.
1
2
4
0
)
2
0
.
0
0
0
0
(
0
.
1
2
4
6
)
2
0
.
0
2
2
4
(
3
.
7
9
1
7
)
*
*
*
0
.
3
4
0
7
(
1
1
.
5
5
2
6
)
*
*
*
0
.
1
4
6
5
(
5
.
2
2
9
6
)
*
*
*
T
w
o
q
u
a
r
t
e
r
s
0
.
2
8
1
7
(
1
.
0
6
3
6
)
2
0
.
0
0
0
0
(
0
.
1
1
6
0
)
2
0
.
0
2
2
4
(
3
.
7
8
7
5
)
*
*
*
0
.
3
3
9
2
(
1
1
.
5
1
4
4
)
*
*
*
0
.
1
4
7
5
(
5
.
2
6
3
7
)
*
*
*
T
h
r
e
e
q
u
a
r
t
e
r
s
0
.
6
4
0
4
(
1
.
9
8
8
0
)
*
*
2
0
.
0
0
0
0
(
0
.
0
8
5
5
)
2
0
.
0
2
2
2
(
3
.
7
6
8
4
)
*
*
*
0
.
3
3
6
7
(
1
1
.
4
3
5
0
)
*
*
*
0
.
1
5
0
1
(
5
.
3
4
9
8
)
*
*
*
E
q
u
i
t
y
b
a
l
a
n
c
e
d
O
n
e
q
u
a
r
t
e
r
0
.
1
8
8
4
(
1
.
0
3
9
9
)
0
.
0
0
0
8
(
0
.
5
0
6
8
)
2
0
.
0
3
4
1
(
5
.
7
2
6
3
)
*
*
*
0
.
3
2
1
1
(
1
0
.
9
2
3
8
)
*
*
*
0
.
2
2
8
8
(
8
.
1
5
4
5
)
*
*
*
T
w
o
q
u
a
r
t
e
r
s
0
.
8
4
4
2
(
3
.
1
8
9
6
)
*
*
*
0
.
0
0
0
2
(
0
.
1
6
5
9
)
2
0
.
0
3
4
5
(
5
.
8
2
5
5
)
*
*
*
0
.
3
2
5
6
(
1
1
.
1
3
7
3
)
*
*
*
0
.
2
3
6
7
(
8
.
4
7
7
8
)
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(
c
o
n
t
i
n
u
e
d
)
Table VI.
Fixed effects panel
regression of wholesale
fund net ?ows with past
excess returns and risk
ARJ
25,2
146
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
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R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
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a
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y

2
0
1
6

(
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4
.
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)
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.
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)
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3
)
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0
.
5
5
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5
)
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4
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)
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2
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3
.
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)
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1
4
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2
(
4
.
6
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6
)
P
r
o
p
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r
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y
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e
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r
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4
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0
.
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.
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)
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3
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0
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5
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0
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6
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)
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7
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1
3
4
5
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3
.
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1
2
8
)
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1
7
7
6
(
6
.
1
0
1
3
)
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*
*
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
t
a
t
:
*
1
0
,
*
*
5
,
*
*
*
1
p
e
r
c
e
n
t
R
e
g
r
e
s
s
i
o
n
e
q
u
a
t
i
o
n
:
N
F
i
;
t
¼
b
j
r
j
i
;
t
þ
c
s
i
;
t
2
1
þ
d
S
i
z
e
i
;
t
2
1
þ
e
N
F
i
;
t
2
1
þ
X
n
i
¼
1
F
E
i
;
t
þ
1
t
w
h
e
r
e
N
F
i
,
t
a
r
e
t
h
e
n
e
t
?
o
w
s
,
r
j
i
i
s
t
h
e
c
u
m
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l
a
t
i
v
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e
x
c
e
s
s
r
e
t
u
r
n
s
f
o
r
e
i
t
h
e
r
1
,
2
o
r
3
q
u
a
r
t
e
r
s
,
s
i
,
t
i
s
t
h
e
t
r
a
c
k
i
n
g
e
r
r
o
r
,
S
i
z
e
i
,
t
i
s
t
h
e
l
o
g
o
f
t
h
e
f
u
n
d
s
i
z
e
a
n
d
F
E
i
,
t
i
s
t
h
e
?
x
e
d
e
f
f
e
c
t
o
f
i
t
h
f
u
n
d
;
t
h
r
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s
e
p
a
r
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m
a
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d
w
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t
h
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v
a
r
i
a
b
l
e
r
j
i
,
t
b
e
i
n
g
1
,
2
o
r
3
q
u
a
r
t
e
r
e
x
c
e
s
s
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e
t
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r
n
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a
n
d
t
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e
c
o
e
f
?
c
i
e
n
t
s
o
f
e
a
c
h
r
e
g
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e
s
s
i
o
n
f
o
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e
a
c
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t
h
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i
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m
e
n
t
c
l
a
s
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e
s
a
r
e
g
i
v
e
n
a
b
o
v
e
Table VI.
Fund ?ows in
Australian
managed funds
147
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
F
u
n
d
c
a
t
e
g
o
r
y
b
1
(
t
-
s
t
a
t
.
)
c
(
t
-
s
t
a
t
.
)
d
(
t
-
s
t
a
t
.
)
e
(
t
-
s
t
a
t
.
)
A
d
j
.
R
2
(
F
-
s
t
a
t
.
)
C
a
s
h
O
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e
q
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r
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e
r
0
.
1
8
9
9
(
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0
.
0
0
0
6
)
2
0
.
0
0
0
6
(
0
.
5
4
3
9
)
2
0
.
0
3
4
3
(
7
.
3
8
8
0
)
*
*
*
0
.
0
5
5
7
(
2
.
9
3
0
5
)
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1
4
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9
)
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w
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s
0
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0
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5
5
3
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0
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)
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5
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3
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5
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)
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1
7
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3
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7
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1
.
6
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3
)
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2
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0
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5
(
9
.
5
3
6
2
)
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2
3
8
7
(
1
5
.
3
7
5
8
)
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6
(
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0
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7
7
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)
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s
2
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8
(
1
.
7
1
4
5
)
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6
(
9
.
5
8
4
1
)
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5
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3
2
1
2
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4
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)
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5
(
9
.
5
4
6
2
)
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2
3
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2
(
1
5
.
3
3
9
0
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2
5
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4
(
1
0
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6
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9
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q
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e
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r
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9
4
0
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8
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9
0
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0
0
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0
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3
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1
1
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2
(
2
6
.
5
5
8
3
)
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3
2
2
1
(
3
2
.
7
0
5
2
)
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3
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0
(
1
5
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9
5
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9
)
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w
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s
0
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1
8
)
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0
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0
0
(
0
.
1
8
0
4
)
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4
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6
(
2
6
.
7
8
2
5
)
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*
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0
.
3
2
0
3
(
3
2
.
5
7
4
4
)
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3
7
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1
(
1
6
.
0
2
1
2
)
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h
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e
q
u
a
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s
0
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4
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1
6
(
7
.
4
5
3
1
)
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*
2
0
.
0
0
0
0
(
0
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2
3
0
3
)
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0
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4
7
9
(
2
6
.
9
5
5
7
)
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*
0
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3
1
7
5
(
3
2
.
2
8
9
0
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3
7
4
7
(
1
6
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0
5
8
6
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*
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i
x
e
d
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r
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0
0
0
0
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0
.
2
3
2
4
)
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0
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8
0
(
7
.
7
8
5
7
)
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3
4
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4
(
1
8
.
9
1
5
5
)
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(
1
0
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6
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8
1
)
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w
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q
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s
0
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5
0
1
9
)
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0
0
0
0
(
0
.
2
0
1
3
)
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7
.
8
4
1
5
)
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3
4
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6
(
1
8
.
8
2
4
0
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0
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6
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1
8
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s
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6
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8
0
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1
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7
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8
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8
7
)
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9
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8
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7
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1
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3
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6
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7
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)
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n
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d
b
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n
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2
9
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6
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7
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(
1
3
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)
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s
0
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1
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0
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1
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1
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.
6
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c
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t
i
n
u
e
d
)
Table VII.
Fixed effects panel
regression of
superannuation retail
fund net ?ows with past
excess returns and risk
ARJ
25,2
148
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b
o
v
e
Table VII.
Fund ?ows in
Australian
managed funds
149
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
positive relationship between the lagged excess returns and the net fund ?ows. Part of
the reason for this may be that the superannuation investors are disadvantaged by the
fact that their investment choices are determined by their employment contracts.
A careful examination of the results indicates that there may be some difference
between the investors who may be choosing a particular type of investment. For
example, there is evidence that the investors who chose equity and overseas and
property investments clearly increased the cash net ?ows to those funds that
performed well. In contrast, investors in cash, managed growth and managed stable
funds did not increase the net ?ows based on the past performance. At the same time
the investors who chose capital guaranteed and managed stable funds are also
sensitive to the riskiness of these funds. In the case of capital guaranteed the increased
risk had a positive effect on the net ?ows. A possible explanation is that since the
capital is guaranteed, investors are willing to take additional risk with capital
guaranteed funds; whereas managed stable fund investors reduced their net ?ows into
funds with high risk, showing a certain level of risk aversion. Investors in overseas
funds show evidence of both the return chasing and risk aversion characteristics.
To compare the behavior of various retail investors only ten of the categories that
are common to all investor groups are tested. The results of the panel regression for
non-superannuation retail funds are provided in Table VIII. The results show
signi?cant contrast with the superannuation investors. Since almost a quarter of the
non-superannuation retail funds are invested in cash funds, it is natural to assume that
the investors into those funds may be more sensitive to the excess returns and risk.
The results appear to support this view. The lagged average excess returns for two and
three quarters have a signi?cant positive effect on the net ?ows. On the other hand, the
risk measure had a negative effect on the net ?ows. Another distinction is the
coef?cients of equity and overseas funds. Unlike the superannuation funds the lagged
average excess returns did not have a positive effect on the non-superannuation fund
net ?ows.
The results of the panel regressions of retirement income retail funds are presented
in Table IX. It can be assumed that of all the retail investors, this particular group may
be the most risk averse, but the risk coef?cients did not have any signi?cant negative
effect on any of the categories. In the case of cash funds the risk variable has a strong
positive effect on the net ?ows, which is an indication of risk taking behavior. A study
by Speelman et al. (2007) shows that older and wealthier investors are willing to take
more risk. For eight out of the ten categories the effect of lagged excess returns had a
positive effect on the net ?ows.
6. Conclusions
The Australian managed fund industry has grown tremendously in the past two
decades. The compulsory superannuation system in Australia is likely to be a primary
driver behind this growth. This paper considers the various segments of the managed
funds market to see if there is any signi?cant difference in the way assets are allocated
into various asset categories. The study also tests if investors base their investment
decisions only on past performance of the funds. The results show that there is
signi?cant difference in asset allocation between the retail and wholesale segments, with
retail investors preferring less risky investments and a lower preference for overseas
investments than wholesale investors. There are also differences in the way the
ARJ
25,2
150
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
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R
S
I
T
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A
t

2
1
:
1
6

2
4

J
a
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a
r
y

2
0
1
6

(
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)
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2
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(
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0
.
2
3
4
1
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*
*
*
(
c
o
n
t
i
n
u
e
d
)
Table VIII.
Fixed effects
panel regression of
non-superannuation retail
fund net ?ows with past
excess returns and risk
Fund ?ows in
Australian
managed funds
151
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
F
u
n
d
c
a
t
e
g
o
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y
b
1
(
t
-
s
t
a
t
.
)
c
(
t
-
s
t
a
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.
)
d
(
t
-
s
t
a
t
.
)
e
(
t
-
s
t
a
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.
)
A
d
j
.
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2
(
F
-
s
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a
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e
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0
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(
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.
2
6
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6
)
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7
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5
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2
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6
.
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w
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5
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s
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7
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2
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0
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5
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1
2
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2
0
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0
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9
5
(
2
.
7
2
0
4
)
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0
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2
8
4
0
(
6
.
3
9
1
3
)
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2
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1
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(
6
.
4
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6
6
)
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*
P
r
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e
q
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7
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1
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.
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6
0
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(
4
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9
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1
8
)
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*
*
T
w
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q
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s
1
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0
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.
6
2
3
1
)
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*
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2
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.
0
0
1
5
(
1
.
1
0
7
4
)
2
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0
4
1
1
(
2
.
5
8
6
2
)
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0
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1
5
6
8
(
2
.
3
4
4
6
)
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1
8
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5
(
5
.
1
6
2
3
)
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*
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h
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e
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a
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s
1
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1
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8
3
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.
2
4
2
6
)
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2
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0
0
1
2
(
0
.
9
4
8
3
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0
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4
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2
.
5
2
2
6
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1
5
3
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(
2
.
2
8
2
0
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0
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1
7
4
9
(
4
.
9
5
2
2
)
*
*
*
M
i
x
e
d
p
o
r
t
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o
l
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o
s
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n
e
q
u
a
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t
e
r
0
.
4
6
5
2
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1
.
6
0
3
4
)
2
0
.
0
0
0
0
(
0
.
0
8
0
5
)
2
0
.
0
7
3
5
(
1
1
.
3
9
9
6
)
*
*
*
0
.
3
0
0
4
(
1
0
.
3
2
4
1
)
*
*
*
0
.
5
7
6
9
(
3
2
.
2
6
0
6
)
*
*
*
T
w
o
q
u
a
r
t
e
r
s
0
.
7
2
9
9
(
1
.
5
1
4
4
)
2
0
.
0
0
0
1
(
0
.
1
8
7
4
)
2
0
.
0
7
3
2
(
1
1
.
3
3
1
0
)
*
*
*
0
.
3
0
0
8
(
1
0
.
3
3
2
2
)
*
*
*
0
.
5
7
6
7
(
3
2
.
2
3
3
3
)
*
*
*
T
h
r
e
e
q
u
a
r
t
e
r
s
0
.
3
0
7
5
(
0
.
5
0
2
7
)
2
0
.
0
0
0
0
(
0
.
1
3
9
0
)
2
0
.
0
7
3
8
(
1
1
.
3
8
9
9
)
*
*
*
0
.
2
9
9
5
(
1
0
.
2
7
2
6
)
*
*
*
0
.
5
7
5
1
(
3
2
.
0
3
2
5
)
*
*
*
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
t
a
t
:
*
1
0
,
*
*
5
,
*
*
*
1
p
e
r
c
e
n
t
R
e
g
r
e
s
s
i
o
n
e
q
u
a
t
i
o
n
:
N
F
i
;
t
¼
b
j
r
j
i
;
t
þ
c
s
i
;
t
2
1
þ
d
S
i
z
e
i
;
t
2
1
þ
e
N
F
i
;
t
2
1
þ
X
n
i
¼
1
F
E
i
;
t
þ
1
t
w
h
e
r
e
N
F
i
,
t
a
r
e
t
h
e
n
e
t
?
o
w
s
,
r
j
i
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e
c
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a
t
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e
x
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e
s
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e
t
u
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i
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e
r
1
,
2
o
r
3
q
u
a
r
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r
s
,
s
i
,
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i
s
t
h
e
t
r
a
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k
i
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e
r
r
o
r
,
S
i
z
e
i
,
t
i
s
t
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e
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o
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o
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t
h
e
f
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n
d
s
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e
a
n
d
F
E
i
,
t
i
s
t
h
e
?
x
e
d
e
f
f
e
c
t
o
f
i
t
h
f
u
n
d
;
t
h
r
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e
s
e
p
a
r
a
t
e
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e
g
r
e
s
s
i
o
n
s
a
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s
t
i
m
a
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d
w
i
t
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t
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e
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a
r
i
a
b
l
e
r
j
i
,
t
b
e
i
n
g
1
,
2
o
r
3
q
u
a
r
t
e
r
e
x
c
e
s
s
r
e
t
u
r
n
s
a
n
d
t
h
e
c
o
e
f
?
c
i
e
n
t
s
o
f
e
a
c
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g
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e
s
s
i
o
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f
o
r
e
a
c
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o
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t
h
e
i
n
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m
e
n
t
c
l
a
s
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e
s
a
r
e
g
i
v
e
n
a
b
o
v
e
Table VIII.
ARJ
25,2
152
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
F
u
n
d
c
a
t
e
g
o
r
y
b
1
(
t
-
s
t
a
t
.
)
c
(
t
-
s
t
a
t
.
)
d
(
t
-
s
t
a
t
.
)
e
(
t
-
s
t
a
t
.
)
A
d
j
.
R
2
(
F
-
s
t
a
t
.
)
C
a
s
h
O
n
e
q
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t
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r
2
0
.
0
2
1
7
(
0
.
0
1
7
7
)
0
.
0
5
0
8
(
2
.
6
6
4
4
)
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*
2
0
.
0
3
0
2
(
4
.
3
7
0
0
)
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1
6
6
0
(
5
.
8
6
8
0
)
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4
0
(
5
.
4
1
5
8
)
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*
T
w
o
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s
2
1
.
2
8
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1
7
(
2
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8
0
5
1
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0
3
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6
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4
.
4
2
9
4
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1
6
5
5
(
5
.
8
6
9
0
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1
4
4
4
(
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.
4
3
0
1
)
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*
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T
h
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r
s
2
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4
7
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6
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1
7
4
2
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0
5
2
7
(
2
.
8
5
6
4
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0
3
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9
(
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.
4
7
0
5
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1
6
5
3
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5
.
8
6
6
1
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1
4
5
0
(
5
.
4
5
1
4
)
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a
p
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r
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9
2
8
5
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1
3
7
1
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0
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0
0
2
7
(
1
.
2
8
7
0
)
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1
7
6
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4
.
1
8
4
1
)
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0
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3
5
0
6
(
1
5
.
9
7
7
2
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2
(
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2
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7
1
8
8
)
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*
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T
w
o
q
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s
1
.
1
4
3
2
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8
0
8
3
)
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0
0
2
1
(
1
.
0
3
3
6
)
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0
1
7
8
(
4
.
2
1
4
1
)
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0
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3
4
8
4
(
1
5
.
8
7
9
4
)
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3
(
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2
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6
7
1
2
)
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*
*
T
h
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e
q
u
a
r
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s
1
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8
6
2
4
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8
1
5
3
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0
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2
7
(
1
.
3
1
7
4
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1
7
7
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4
.
2
0
9
3
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3
4
8
0
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1
5
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8
9
6
2
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3
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3
(
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2
.
8
3
3
7
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q
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O
n
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r
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3
5
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1
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5
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7
6
7
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1
5
3
6
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9
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7
.
5
2
7
4
)
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2
8
1
9
(
1
9
.
3
0
4
7
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3
6
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7
(
1
4
.
0
2
2
6
)
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*
*
T
w
o
q
u
a
r
t
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r
s
0
.
4
9
4
1
(
5
.
4
1
0
3
)
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*
*
0
.
0
0
0
0
(
0
.
2
6
9
1
)
2
0
.
0
5
3
4
(
1
7
.
6
8
8
3
)
*
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*
0
.
2
7
8
0
(
1
9
.
0
4
7
3
)
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3
6
1
0
(
1
3
.
9
8
0
9
)
*
*
*
T
h
r
e
e
q
u
a
r
t
e
r
s
0
.
7
7
5
0
(
6
.
7
7
4
8
)
*
*
*
0
.
0
0
0
0
(
0
.
2
2
9
2
)
2
0
.
0
5
3
9
(
1
7
.
8
7
9
3
)
*
*
*
0
.
2
7
5
1
(
1
8
.
8
8
5
6
)
*
*
*
0
.
3
6
4
1
(
1
4
.
1
5
4
9
)
*
*
*
F
i
x
e
d
i
n
t
e
r
e
s
t
O
n
e
q
u
a
r
t
e
r
0
.
2
4
8
4
(
1
.
6
0
0
7
)
0
.
0
0
0
1
(
0
.
8
7
3
5
)
2
0
.
0
4
0
6
(
6
.
6
9
0
1
)
*
*
*
0
.
4
1
5
7
(
1
4
.
1
3
3
3
)
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*
*
0
.
4
0
6
5
(
1
5
.
3
8
7
1
)
*
*
*
T
w
o
q
u
a
r
t
e
r
s
0
.
6
3
4
0
(
2
.
6
4
4
1
)
*
*
*
0
.
0
0
0
1
(
0
.
9
5
8
6
)
2
0
.
0
4
1
5
(
6
.
8
4
4
4
)
*
*
*
0
.
4
1
5
4
(
1
4
.
1
9
0
6
)
*
*
*
0
.
4
1
0
2
(
1
5
.
6
1
0
2
)
*
*
*
T
h
r
e
e
q
u
a
r
t
e
r
s
0
.
5
6
4
9
(
1
.
8
5
4
5
)
*
0
.
0
0
0
1
(
0
.
8
5
2
3
)
2
0
.
0
4
1
6
(
6
.
8
2
6
2
)
*
*
*
0
.
4
1
1
2
(
1
4
.
0
1
7
4
)
*
*
*
0
.
4
0
7
3
(
1
5
.
4
3
1
3
)
*
*
*
M
a
n
a
g
e
d
b
a
l
a
n
c
e
d
O
n
e
q
u
a
r
t
e
r
0
.
3
0
1
7
(
3
.
6
3
4
9
)
*
*
*
0
.
0
0
0
0
(
0
.
0
7
5
1
)
2
0
.
0
1
3
4
(
4
.
7
7
7
6
)
*
*
*
0
.
4
8
5
4
(
3
4
.
6
1
2
6
)
*
*
*
0
.
3
9
7
5
(
1
7
.
6
7
7
5
)
*
*
*
T
w
o
q
u
a
r
t
e
r
s
0
.
5
8
0
3
(
4
.
7
7
5
0
)
*
*
*
0
.
0
0
0
0
(
0
.
0
5
4
0
)
2
0
.
0
1
3
0
(
4
.
6
1
4
5
)
*
*
*
0
.
4
8
4
5
(
3
4
.
6
3
9
1
)
*
*
*
0
.
3
9
9
2
(
1
7
.
7
9
7
1
)
*
*
*
T
h
r
e
e
q
u
a
r
t
e
r
s
0
.
7
7
2
4
(
5
.
0
2
6
5
)
*
*
*
0
.
0
0
0
0
(
0
.
0
3
3
6
)
2
0
.
0
1
2
6
(
4
.
4
8
0
0
)
*
*
*
0
.
4
8
2
3
(
3
4
.
5
1
4
8
)
*
*
*
0
.
3
9
9
6
(
1
7
.
8
2
7
9
)
*
*
*
M
a
n
a
g
e
d
s
t
a
b
l
e
O
n
e
q
u
a
r
t
e
r
0
.
3
7
3
5
(
3
.
7
5
9
8
)
*
*
*
0
.
0
0
0
0
(
0
.
7
5
6
5
)
2
0
.
0
1
5
4
(
6
.
9
2
5
3
)
*
*
*
0
.
4
3
4
0
(
2
8
.
6
7
7
8
)
*
*
*
0
.
5
0
2
9
(
2
5
.
6
7
5
5
)
*
*
*
T
w
o
q
u
a
r
t
e
r
s
0
.
4
1
3
6
(
2
.
8
7
3
3
)
*
*
*
0
.
0
0
0
0
(
0
.
8
1
6
5
)
2
0
.
0
1
5
5
(
6
.
9
6
9
0
)
*
*
*
0
.
4
3
2
7
(
2
8
.
5
7
2
5
)
*
*
*
0
.
5
0
1
8
(
2
5
.
5
6
3
9
)
*
*
*
(
c
o
n
t
i
n
u
e
d
)
Table IX.
Fixed effects panel
regression of retirement
income retail fund net
?ows with past excess
returns and risk
Fund ?ows in
Australian
managed funds
153
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
F
u
n
d
c
a
t
e
g
o
r
y
b
1
(
t
-
s
t
a
t
.
)
c
(
t
-
s
t
a
t
.
)
d
(
t
-
s
t
a
t
.
)
e
(
t
-
s
t
a
t
.
)
A
d
j
.
R
2
(
F
-
s
t
a
t
.
)
T
h
r
e
e
q
u
a
r
t
e
r
s
0
.
5
3
7
4
(
3
.
0
2
4
1
)
*
*
*
0
.
0
0
0
0
(
0
.
7
8
7
6
)
2
0
.
0
1
5
4
(
6
.
9
3
7
8
)
*
*
*
0
.
4
3
2
5
(
2
8
.
5
7
0
2
)
*
*
*
0
.
5
0
2
0
(
2
5
.
5
8
0
8
)
*
*
*
O
v
e
r
s
e
a
s
O
n
e
q
u
a
r
t
e
r
0
.
3
7
7
9
(
5
.
5
6
0
2
)
*
*
*
2
0
.
0
0
0
1
(
0
.
7
0
8
0
)
2
0
.
0
3
0
1
(
6
.
2
9
8
3
)
*
*
*
0
.
4
1
4
4
(
2
1
.
9
8
7
0
)
*
*
*
0
.
2
9
9
0
(
1
0
.
3
6
1
8
)
*
*
*
T
w
o
q
u
a
r
t
e
r
s
0
.
6
5
0
5
(
6
.
5
7
4
4
)
*
*
*
2
0
.
0
0
0
1
(
0
.
7
0
6
7
)
2
0
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0
2
8
8
(
6
.
0
2
7
3
)
*
*
*
0
.
4
0
6
6
(
2
1
.
6
6
8
3
)
*
*
*
0
.
3
0
3
5
(
1
0
.
5
6
5
2
)
*
*
*
T
h
r
e
e
q
u
a
r
t
e
r
s
0
.
5
9
6
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Table IX.
ARJ
25,2
154
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
superannuation, retirement income and discretionary funds are invested. Discretionary
investors prefer the cash asset category, while superannuation investors preferred the
managed segment. Retirement income investors also preferred managed funds followed
bycapital guaranteed funds. The results of our study are similar to the evidence reported
in US managed funds industry studies.
There is clear evidence that investors base their decisions primarily on past
performance of the funds, with the retail segment showing higher level of reallocation
of investments based on past performance compared to the wholesale segment. The
return chasing behavior is more pronounced in the preferred cash asset category of
each of these groups. For example, the discretionary investors preferred assets over
other classes of investments and showed strong return chasing behavior in this
category. There is relatively less evidence of reaction to risk among the managed fund
investors. Part of the problem may be the dif?culty in de?ning the risk as it may be
perceived by investors. The Australian managed funds industry is dominated by
superannuation investments. Superannuation is the primary retirement savings for
most Australians who wish to rely on self-funded retirement. The Australian federal
government by its policies, has been pushing to reduce individuals’ reliance on public
pension and encourage self-funded retirement. Evidence of investments based on past
performance in the Australian managed funds industry may be of concern to policy
makers as misallocation of investments by uniformed investors may erode their
retirement savings, thereby, leaving public sector with an insuf?ciently funded
government pension liability. Additionally this study makes important contributions
in understanding the investor behavior in Australian managed funds industry. Such an
understanding is likely to be of value to fund managers who seek to inform investors of
their performance and use performance information for marketing purposes. Investors
of the managed funds will also bene?t from understanding of how this industry
operates from our ?ndings. Finally, our ?ndings are of importance for policy makers in
terms of understanding investor behavior and developing appropriate policy
responses, especially in light of those policies aimed at providing investors with
more choices and ease of moving their investments across superannuation funds.
Notes
1. Based on AFG Global Funds Management Index, in June 2007, Australians had an average
of A$63,794 per person invested in managed funds compared to the next highest amount of
A$43,458 in the US.
2. The existing studies look at only certain asset classes within the managed fund industry or
a certain segment, such as, superannuation funds. This study covers all asset classes within
the wholesale and retail segments, as well as, the superannuation, discretionary and
retirement funds within the retail segment.
3. Superannuation contributions are retirement savings for individuals and cannot be
withdrawn prior to retirement (or on reaching a particular age) except under special
circumstances.
4. This statement and interpretation are correct for the study period; introduction of Future of
Financial Advice reforms with effect from July 1, 2012 imposes restrictions on commissions
and soft dollar fees paid to advisors.
5. Investment category classi?cations are based on the description provided by the vendors.
Fund ?ows in
Australian
managed funds
155
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
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t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
6. Tracking error is measured as the annualised standard deviation of the differences between
the portfolio return and the benchmark return. Benchmark return in this case is the mean
return of the industry. In separate analysis we use an Australian stock market index in the
model but it creates multicollinearity problems. Choice of using mean return of funds is more
appropriate because investors of managed funds are restricted to investing in managed
funds because of requirement for superannuation investors and for investors of
discretionary funds, it is a self-imposed choice to invest in managed funds.
References
Agnew, J. and Balduzzi, P. (2010), “The response of aggregate 401(k) trading to asset returns”,
unpublished manuscript, Boston College, Boston, MA.
Bailey, W., Kumar, A. and Ng, D. (2011), “Behavioral biases of mutual fund investors”, Journal of
Financial Economics, Vol. 102, pp. 1-27.
Benson, K.L., Gallagher, D.R. and Teodorowski, P. (2007), “Momentum investing and the
asset allocation decision”, Accounting and Finance, Vol. 47, pp. 571-98.
Bilson, C., Frino, A. and Heaney, R. (2005), “Australian retail fund performance persistence”,
Accounting and Finance, Vol. 45, pp. 25-42.
Capon, N., Fitzsimons, G.J. and Prince, R.A. (1996), “An individual level analysis of the
mutual fund investment decision”, Journal of Financial Services Research, Vol. 10,
pp. 59-82.
Chen, J., Hong, H., Huang, M. and Kubik, J.D. (2004), “Does fund size erode mutual fund
performance? The role of liquidity and organization”, American Economic Review, Vol. 94,
pp. 1276-302.
Del Guercio, D. and Tkac, P.A. (2002), “The determinants of the ?ow of funds of managed
portfolios: mutual funds vs pension funds”, Journal of Financial and Quantitative Analysis,
Vol. 37, pp. 523-57.
Drew, M.E., Stanford, J.D. and Veeraraghavan, M. (2002), “Selecting Australian superannuation
funds: a retail investor’s perspective”, Journal of Financial Services Marketing, Vol. 7,
pp. 115-28.
Faff, R.W., Parwada, J.T. and Poh, H.-L. (2007), “The information content of Australian managed
fund ratings”, Journal of Business Finance & Accounting, Vol. 34, pp. 1528-47.
Frino, A., Heany, R. and Service, D. (2005), “Do past performance and past cash ?ows explain
current cash ?ows into retail superannuation funds in Australia?”, Australian Journal of
Management, Vol. 30 No. 2, pp. 229-44.
Fry, T., Heaney, R. and McKeown, W. (2007), “Will investors change their superannuation fund
given the choice?”, Accounting & Finance, Vol. 47, pp. 267-83.
Gerrans, P. (2004), “Australian fund ratings and individual investors”, Australian Journal of
Management, Vol. 29, pp. 87-107.
Gharghori, P., Sujoto, C. and Veeraraghavan, M. (2008), “Are Australian investors smart?”,
Australian Journal of Management, Vol. 32, pp. 525-44.
Goetzmann, W.N. and Peles, N. (1996), “Cognitive dissonance and mutual fund investors”,
Journal of Financial Research, Vol. 20, pp. 145-58.
Gruber, M.J. (1996), “Another puzzle: the growth in actively managed mutual funds”, Journal of
Finance, Vol. 51, pp. 783-810.
Ippolito, R.A. (1992), “Consumer reaction to measures of poor quality: evidence from the mutual
fund industry”, Journal of Law & Economics, Vol. 35, pp. 45-70.
ARJ
25,2
156
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
1
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
Lynch, A.W. and Musto, D.K. (2003), “How investors interpret past fund returns”, Journal of
Finance, Vol. 58, pp. 2033-58.
Phillips, P.J. (2011), “Will self-managed superannuation fund investors survive?”, Australian
Economic Review, Vol. 44, pp. 51-63.
Pollet, J.M. and Wilson, M. (2008), “How does size affect mutual fund behavior?”, The Journal of
Finance, Vol. 63, pp. 2941-69.
Sawicki, J. (2001), “Investors’ differential response to managed fund performance”, The Journal of
Financial Research, Vol. 24, pp. 367-84.
Sensoy, B.A. (2009), “Performance evaluation and self-designated benchmark indexes in the
mutual fund industry”, Journal of Financial Economics, Vol. 92, pp. 25-39.
Sharpe, W.F. (1992), “Asset allocation: management style and performance measurement”,
Journal of Portfolio Management, Vol. 18 No. 2, pp. 7-19.
Sialm, C., Starks, L. and Zhang, H. (2012), “De?ned contribution pension plans: sticky or
discerning money?”, unpublished manuscript, University of Texas, Austin, TX.
Sirri, E.R. and Tufano, P. (1998), “Costly search and mutual fund ?ows”, Journal of Finance,
Vol. 53, pp. 1589-622.
Speelman, C.P., Clark-Murphy, M. and Gerrans, P. (2007), “Decision making clusters in retirement
saving: preliminary ?ndings”, Australian Journal of Labour Economics, Vol. 10, pp. 115-27.
Watson, J., Wickramanayke, J. and Premachandra, I.M. (2011a), “The value of Morningstar
ratings: evidence using stochastic data envelopment analysis”, Managerial Finance,
Vol. 37, pp. 94-116.
Watson, J.R., Delaney, J. and Wickramanayake, J. (2011b), “Australian superannuation fund
ratings: what investors need to know”, available at SSRN:http://ssrn.com/
abstract¼1913997 (accessed August 22).
Further reading
Bergstresser, D. and Poterba, J. (2002), “Do after-tax returns affect mutual fund in?ows?”, Journal
of Financial Economics, Vol. 63, pp. 381-414.
Ivkovic, Z. and Weisbenner, S. (2009), “Individual investor mutual fund ?ows”, Journal of
Financial Economics, Vol. 92, pp. 223-37.
Watson, J. and Wickramanayke, J. (2012), “The relationship between aggregate managed fund
?ows and share market returns in Australia”, Journal of International Financial Markets,
Institutions and Money, Vol. 22, pp. 451-72.
Corresponding author
Rakesh Gupta can be contacted at: R.gupta@grif?th.edu.au
Fund ?ows in
Australian
managed funds
157
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