DOI: 10.5817/FAI2015-1-1 No. 1/2015
7
Modeling the Size of the Mutual Fund Industry
in Countries of Central and Eastern Europe
Oleksandra Lemeshko, Oldřich Rejnuš
Masaryk University
Faculty of Economics and Administration, Department of Finance
Lipová 5a, 601 00 Brno, Czech Republic
E-mail: lemeshko@mail.muni.cz, rejnus@econ.muni.cz
Abstract: The rapid growth and development of the mutual fund industry
throughout the world stimulated vast contemporary studies focusing on a wide
range of issues predominantly of microeconomic character, such as fund
performance, timing ability, fees and fund flows, thus leaving determinants and
attributes of mutual fund industry development beyond their research. The rare
relevant studies predict that development of the mutual fund industry depends
on a number of factors among which the predominant role belongs to
development of the economic and financial systems, and quality of governance
and regulatory basis. One essential condition of validity of this prediction is that
it is based upon a sample of developed economies, thus leaving a space for the
likelihood that under condition of developing or middle-income economies some
expectations may substantially deviate from the predication. This paper aims to
reevaluate the significance of the impact of individual macro- and
microeconomic factors, which were identified in previous studies, on size of
asset under management in the sample of high- and middle-income economies
of Central and Eastern Europe by means of regressing the total size of the
mutual fund industry and size of its separate components, such as equity, fixed
income and money market asset management over a number of independent
variables. The obtained results indicate that out of a wide range of factors, the
high explanatory power of which was stressed by earlier studies, only a small
group of them turned out to be significant in our research. In particular, it was
found that the size of the CEE mutual fund industry in general and the sizes of
its particular segments respond positively on increase of country openness to
trade and capital inflows, development and stability of local financial and capital
markets, improvement of quality of governance and regulatory basis. Also some
controversial evidence was obtained on the role of change in government
indebtedness for explaining the size of the mutual fund industry – in general,
there is a significantly positive impact of a decrease of central government debt
on the size of CEE asset management, however its sign is not consistent across
all subcategories of funds. Although the chosen sample does not cover as large
a number of countries as previous studies, it provides brief insight into the CEE
mutual fund industry, documenting important country and regional
characteristics.
Keywords: determinants, economic and financial system development,
governance
JEL codes: G23, O16
Financial Assets and Investing
8
1 Introduction
Currently asset management is one of the most fast growing segments of
international capital markets. Its rapid growth and development throughout the
world stimulated a vast contemporary studies on wide range of issues of mainly
microeconomic character, such as fund performance and timing ability, fees and
expenses, fund flows, exchange traded funds (ETF) and socially responsible
funds (SRF). However despite the increasing significance of asset management
there is, evidently, a lack of studies on its development and growth attributes.
The existing literature predicts that the mutual fund industry is more advanced
in countries with better developed and more stable capital markets and a
stronger regulatory basis (Beck et al., 2010; Čihák et al., 2012). The obtained
results confirm that a number of factors influence the growth and development
of the mutual fund industry such as national income and capital market liquidity
(Fernando et al., 2003), market returns and country openness (Klapper et al.,
2004). All these studies on both microeconomic characteristics and
macroeconomic determinants are structured upon developed economies, thus
leaving the space for substantial likelihood that under condition of developing
economies some expectations may substantially deviate from these
predications. In this sense the mutual fund industry in Central and Eastern
Europe (CEE) provides good opportunity for further research. Existing studies
structured upon CEE economies are rather scarce and restrict their interest to
banks and pension funds (Havrylchyk, 2009; Jackowicz and Kowalewski, 2012)
rather than mutual funds per se. As for development determinants and growth
attributes of CEE asset management, there is an evident gap in relevant
studies.
The existing literature predicts that the development of the mutual fund
industry depends on a number of factors among which the predominant role
belongs to development of economic and financial system and with quality
governance. This paper aims to reevaluate on a sample of high- and middleincome
CEE economies the impact of factors identified in previous studies. This
study departs from previous ones by using a new database of more than 5000
open-end equity, fixed income and money market mutual funds operating in
CEE during the last 13 years. Although the chosen sample does not cover as
large of a number of countries as previous studies, it provides an insight into
the CEE fund industry, documenting important country and regional
characteristics. Following established practice, for evaluation of the significance
of particular growth factors and development attributes the size of the mutual
fund industry, given by its market capitalization to GDP ratio is regressed by
means of pooled OLS over a number of independent variables, data on which
was collected for a sample of 11 countries for a 13 year time span.
This paper proceeds as follows: Section 2 reviews the existing studies dealing
with mutual fund industry in general and determinants of its development in
No. 1/2015
9
particular; Section 3 reports data used and methodology applied; Section 4
discusses the significance of impact of chosen determinants of mutual fund
development in CEE economies; and Section 5 concludes.
2 Overview of Literature on Mutual Fund Industry
Development
Vast contemporary studies on mutual funds focus on wide range of issues of
mainly microeconomic character, such as fund performance and timing ability,
fees and expenses, fund flows, exchange traded funds (ETF) and socially
responsible funds (SRF). All these studies are structured upon world samples.
To evaluate mutual fund performance practitioners and academics frequently
rely on various fund characteristics such as expenses and fees, past
performance, fund size and age, inflows, diversification and turnover. In
general, recent studies confirm this relationship. Among assumed
characteristics the highest relevance have past performance and fund size
(Agnesens, 2013). Additionally characteristics relating to quality of fund
management, structure of management team and corporate culture are also
relevant (Prather et al., 2004; Gottesman and Morey, 2006, 2012;
Karagiannidis, 2010, 2012). Knowledge spillovers experienced by funds
headquartered in large cities might be another relevant factor (Bell and Deng,
2013; Christoffersen and Sarkissian, 2009). Along with determinants of fund
performance modern studies deal with problematic market timing. There is
evidence that some of the best performing fund managers do possess shortterm
market timing abilities (Bollen and Busse, 2004; Benos and Jochec, 2011).
One actively investigated issue today is fund characteristics explaining total
expense ratio (Korkeamaki and Smythe, 2004; Geranio and Zanotti, 2005;
Adams et al., 2012). Studies estimating the extent to which mutual fund
portfolio trading of securities is triggered by investor flows, indicate that the
significance of this liquidity-induced portfolio trading activity is small and
behavior of fund investors is more consistent with contrarian rather than
momentum characteristics (Rakowski and Wang, 2009; Dubofsky, 2010). ETFs
and SRF are a recent and very successful financial innovation thus being
frequent subject of modern studies. Comparison of risk-adjusted performance of
ETFs and closed-end funds (CEF) confirms superior performance of ETFs
(Harper et al., 2006; Hughen and Mathew, 2009). Studies on SRF are focused
mainly on fund’s performance. Currently SRF are undergoing a catching up
phase and thus there is no evidence of significant differences in risk-adjusted
returns between SRF and conventional funds (Bauer et al., 2005; Benson and
Humphrey, 2008).
However despite such growth and development of the mutual fund industry,
there is an evident lack of studies on their determinants and attributes. The
existing literature predicts that the mutual fund industry is more advanced in
countries with better developed and more stable capital markets and a stronger
Financial Assets and Investing
10
regulatory basis (Beck et al., 2010). The obtained results confirm that highincome
economies experience higher growth rates of domestic mutual fund
industries relative to their middle-income neighbors, reflecting investor
confidence in market integrity and liquidity, and efficiency of local regulatory
systems (Fernando et al., 2003). However, the existing evidence on middleincome
economies comes mainly from the experience of Asian countries which
were hit by the East Asian crisis, thus imposing some uncertainty about
unbiasedness of the obtained results. As for other attributes of development of
the mutual fund industry there is empirical evidence of significant positive
correlation between local mutual fund growth rates and such variables as
market returns, country openness and common law (Klapper et al., 2004).
Further studies suggest that the industry is larger in countries with wealthier
and more educated populations, where the industry is older and in which
defined contribution pension plans are more prevalent (Khorana et al., 2005).
Studies exploring the role of institutional and socio-cultural factors as further
determinants of differential development and growth rates of the mutual fund
industry indicate at insignificantly negative impact of unified financial service
industry regulatory framework, which is used by all member states of the
European Union, as well as a negative impact of widespread belief in work as
the legitimate source of monetary gain (Tulbure and Catarama, 2009).
Alongside evidence in favor of dependence on particular macroeconomic factors
there is also some evidence for some determination by microeconomic
characters such as competition and contestability within industry: fewer barriers
to entry and lower initial and redemption charges are positively associated with
a larger mutual fund industry (Ramos, 2009). Here it is necessary to state that
all above mentioned studies are structured upon world samples, which are
mainly represented by well developed economies. Thus interesting results would
be obtained by investigating the development of mutual fund industry in
developing economies, such as Brazil. It seems surprising, but common
variables like economic development, market returns and quality of regulation
were not found to be statistically significant, while financial innovations and
market risk did affect the relative development of the domestic mutual fund
industry (Varga and Wengert, 2010).
As for performance of individual sectors of the mutual fund industry, the
existing evidence indicates that, on average: (1) equity and fixed income funds
underperform relative to benchmark, which is the result of fund managers’
weak selection skills and successful timing strategies; (2) more concentrated
equity funds perform better, that is, investment ability is more evident among
equity fund managers who hold portfolios concentrated in a few industries; (3)
high yield fixed income funds exhibit persistence in their monthly returns; (4)
money market funds returns are considered as immune to runs and financial
instability (Pastor and Stambaugh, 2001; Breloer et al, 2012; Ammann et al,
2010; Huij and Derwall, 2007; Jank and Wedow, 2008). Existing studies on
No. 1/2015
11
development of individual sectors of the mutual fund industry indicate that, on
average: (1) all three categories of funds grow faster in countries with better
macroeconomic performance and higher investors’ confidence in the integrity of
local capital markets; (2) equity funds are more developed in countries where
investors have higher risk tolerance and where there are lower transaction
costs; (3) fixed income funds are the dominating category of funds in countries
in which reforms of social security and pension systems are taking place; (4)
money market funds grow faster in countries, where there is a constant
monitoring of explicit and implicit guarantees issued by the banking sector; (5)
once investors switch into equity funds, they are unlikely to return to fixed
income or money market funds as long as equity returns are higher in real
terms and their volatility is not intolerably high (Klapper, 2004; Thapa and
Poshakwale, 2010, 2012; Poshakwale and Thapa, 2011; Narulita and Parwada,
2012).
All these studies on both microeconomic characteristics and macroeconomic
determinants are structured upon developed economies. Thus the probability
that under conditions of developing economies some expectations derived from
the evidence of developed economies may either not to fulfill or even have an
opposite effect - such probability cannot be excluded. In this sense the growing
economic significance and fragmentation of the European mutual fund industry
provides a good opportunity for relevant research. All studies on both
development and particular characteristics of the European mutual fund
industry can be conventionally divided into two groups – studies structured
upon evidence from matured EU economies and studies structured upon
developed and developing economies of Central and Eastern Europe (CEE). As
other distinct features it is possible to point that: (1) all these studies have
been conducted either at the individual country level, e.g., for funds that invest
in Germany, UK or Italy (Walter and Weber, 2006; Cuthbertson and Nitzsche,
2013; Cuthbertson et al, 2008; Geranio and Zanotti, 2005), or on the group
country level, e.g. EU-15 (Bengtsson and Delbecque, 2011); (2) all these
studies focus mainly on individual characteristics of European mutual funds, in
particular on their performance (Banegas et al., 2013; Vidal-García, 2013), and
leave out their macroeconomic determinants and attributes. Thus based on
review of recent and sometimes all existing studies it is possible to conclude
that there is a large gap in research of functional characteristics and growth
determinants of mutual fund industry in countries of Central and Eastern Europe
(CEE). Former communist and currently developed and developing market
economies of CEE, having among themselves EU and non-EU members, provide
an excellent opportunity to test whether the relationship between maturation of
national economical and financial systems and mutual fund industry
development, also holds in less efficient markets. Relevant studies structured
upon CEE economies are rather scarce and restrict their interest to banks
(Havrylchyk, 2009; Jackowicz et al., 2011) and pension funds (Bakker and
Financial Assets and Investing
12
Gross, 2004; Aspalter, et al, 2009) rather than mutual funds per se. Rest
scientific issues from CEE economies remain practically unknown. Rare existing
modern studies indicate that equity market development and competition in the
banking sector play a significant positive role in sparing overall economic
growth and asset management industry of CEE economies independently from
their economic association (Bakker and Gross, 2004; Cojocaru et al., 2011).
Recent country studies on funds confirm overall short-term performance
persistence of Hungarian equity mutual funds (Erdos and Ormos, 2009;
Dariusz, 2011). There is evidence of slight outperformance of Polish funds
relative to international funds due to informational advantages of local over
foreign investors, and presence of market timing ability (Białkowski and Otten,
2011). As for determinants and attributes of CEE mutual fund industry growth,
so far to our knowledge there is no a single study on this subject.
3 Data and Methodology
This paper aims to reevaluate on a sample of developed and developing CEE
economies the impact of factors identified in previous studies and presented
above. For research design purposes and on the basis of World Bank income
approach, 11 CEE economies have been divided into two groups – high-income
CEE economies with $801.08 billion of total GDP or $13,517 per capita,
comprising Poland, Czech Republic, Slovakia, Hungary, Slovenia and Estonia,
and middle-income CEE economies with $1,169.56 billion of total GDP or
$6,199 per capita, comprising Latvia, Lithuania, Russia, Ukraine and Belarus.
This study departs from previous ones by using a new database of more than
5,000 open-end equity, fixed income and money market mutual funds operating
in CEE in the time-window of 2000-2014. Although the chosen sample does not
cover as large of a number of countries as previous studies, it provides an
insight into the CEE fund industry, documenting important country and regional
characteristics. Following established practice, the average marginal effect of
longitudinal data (cross-sectional, that is, for 11 entities in the sample, and
times-series, that is, for 13 observation periods) was analyzed by means of
fixed effect estimator with 95% statistical significance. The longitudinal data
used was of both raw and ready-made character and it was collected from
various sources: (1) data for variables referring to capital market and mutual
fund industry development was partly derived from Bloomberg and partly
provided by Investment Company Institute (ICI), European Securities
and Markets Authority (ESMA), and European Fund and Asset Management
Association (EFAMA); (2) data for variables of economic and social development
was derived from the World Bank (WB) and International Monetary Fund (IMF)
databases - World Development Indicators (WDI) and International Financial
Statistics (IFS), as well as from the United Nations Organization (UNO)
database; (3) data for variables of quality of regulatory basis and governance
was derived from database by Kaufmann et al. (2009) – The Worldwide
Governance Indicators, 2013 Update (See Table 1 and Table 2). The applied
No. 1/2015
13
approach was comprised by the following sequence of steps: (1) identification
of the full range of potential determinants and choice of representative variables
(proxies) on the basis of empirical evidence and existing studies; (2) setting up,
adjusting the database (especially in the case of Bloomberg, raw data which
required manual corrections for outliers), dropping out of observations with
missing values; (3) specification of the model (choice of its functional form and
type, that is, pooled OLS versus fixed effect or random effect estimator); (4)
check of the obtained estimates for robustness.
A mutual fund, also widely known as assets under management (AUM), stands
for a market value of assets that an investment company manages on behalf of
its investors. Aggregate assets under management of a group of investment
companies operating within an economy at a given overall market price level in
a given time period is defined as mutual fund industry. There are many ways
how to measure mutual fund industry – in terms of number of funds either
domiciled or available (or both) for local and foreign investors, funds’ total
assets or funds’ net assets. Although all these indicators provide good
measurement of mutual fund industry which is consistent over time and
between countries, nevertheless it has poor evaluating power due to absolute
nature of the indicators used. Absolute indicators do not allow evaluation of the
role and significance of any economic unit or system in terms of a whole
country’s economy or social welfare. In contrast, relative indicators view any
economic unit or system as a component of a larger group of economic units or
a super system, for example, a country’s economy or social welfare allow
evaluation of the role and significance of the former (i.e. an economic unit or
system) in the development and growth of the latter (i.e. a group of economic
units or a super system) (Vinkler, 2012). One relative measure of size of a
country’s mutual fund industry accepted worldwide is market value of total
assets under management of operation in the country mutual funds as fraction
of the country’s GDP. This measurement is used by both academicians
(Fernando et al., 2003; Klapper et al., 2004; Khorana et al., 2005; Tulbure and
Catarama, 2009) and practitioners (The Global Financial Development Database
2013 by Čihák et al. (2012) from the WB; Asset Management Annual Report:
Facts and Figures 7th
Annual Review by group of experts from EFAMA). In our
research we will follow this approach.
The existing literature predicts that development of mutual fund industry
depends on a number of factors among which the predominant role belongs to
the development of economic and financial systems and quality of governance.
In particular, existing studies confirm that, on average, financial intermediaries
are larger, more active and more efficient in high-income countries with lower
income heterogeneity (Demirguc-Kunt, 2011). Further it is natural to assume
that financial intermediaries will be larger in countries, where consumers are
better educated and have better access to information (both printed and online
sources), financial institutions and markets (Khorana et al., 2005). Besides
Financial Assets and Investing
14
overall economic development, openness to trade and capital flows, being an
indicator of integration with international capital and goods markets, is
particularly important for promotion of countries’ financial systems and asset
management (Čihák et al., 2012). In this context it is important not to forget
that openness is closely interconnected with risk to cross-border financial
contingency and crisis (Laeven and Valencia, 2012). In light of the above stated
it is expected that while analyzing determinants of asset management
development it is necessary to operate with such explanatory variables as GDP
per capita and Gini index, literacy rate, average number of newspapers and
internet users per capita, total trade to GDP ratio, sovereign debt to GDP ratio,
FDI to GDP ratio, and financial crisis dummy variable (See Table 1).
Emergence and development of asset management can be viewed as a further
stage of financial system maturation. Thus while investigating fund industry
development a number of explanatory variables referring to financial system
development should be taken into consideration: size of capital market, its
turnover and liquidity, size of banking sector and its ability to transfer funds,
bank concentration ratio, size of insurance sector, real interest rates, return of
local exchange index and its volatility (Fernando et al., 2003; Klapper et al.,
2004; Beck et al., 2010; Demirguç-Kunt, 2011; Čihák et al., 2012) (See Table
1).
No. 1/2015
15
Table 1 Chosen attributes of CEE mutual fund industry growth and development
Variable Description Reference Source
Panel A. Economic growth and development characteristics
Log GDP per capita* Log of annual country GDP per one inhabitant. Klapper et al. (2004) WDI, IMF
GDP growth rate* Annual growth rate of country GDP. Klapper et al. (2004) WDI, IMF
Gini index*
A measure of country
residents’ annual income distribution. It is the
most popular measure of inequality, widely used
by UNO, WB, IMF.
Fernando et al. (2003),
Klapper et al. (2004),
Khorana et al. (2005)
UNO
Literacy rate*
The percentage of the population age 15 and
above who can, with understanding, read and
write a short, simple statement on their
everyday life. It is one of the most popular
measures of human capital development, widely
used by UNO, WB, IMF.
Khorana et al. (2005) WDI, UNO
Newspapers per capita*
The average number of newspapers available in
the country per one inhabitant.
Khorana et al. (2005) WDI, UNO
Internet users per capita*
The average number of internet users in the
country per one inhabitant.
Khorana et al. (2005) WDI, UNO
Total trade to GDP ratio*
Country exports and imports to GDP. It stands
for country openness to trade.
Laeven and Valencia (2012)
Laeven and Valencia
(2012),
IMF, WDI
Sovereign debt to GDP
ratio*
Bonds issued by a country central government
in a foreign currency to GDP.
Čihák et al. (2012) WDI, IMF
FDI to GDP ratio*
Country foreign direct investments to GDP. It
stands for country openness to capital flows
Čihák et al. (2012) WDI, IMF
Financial crisis*
Dummy variable, 1 - for no crisis and 0 - for
crisis.
Laeven and Valencia (2012),
Čihák et al. ( 2012)
Laeven and Valencia
(2012),
IMF
Panel B. Financial market development characteristics
Cap to GDP ratio* Market capitalization of listed stocks to GDP in Fernando et al. (2003), Demirguc-Kunt
Financial Assets and Investing
16
the country. Klapper et al. (2004) (2011), WDI, IMF
Total shares traded to
GDP ratio**
Turnover of listed stocks to GDP in the country.
It stands for capital market liquidity.
Fernando et al. (2003),
Klapper et al. (2004)
Demirguc-Kunt
(2011), WDI, IMF
Total shares traded to
Cap ratio**
Turnover of listed stocks to market
capitalization. It stands for capital market
turnover.
Fernando et al. (2003),
Klapper et al. (2004)
Demirguc-Kunt
(2011), WDI, IMF
Total bank assets to GDP
ratio*
Total commercial bank assets to GDP in the
country. It stands for a size of banking industry.
Fernando et al. (2003),
Klapper et al. (2004)
Demirguc-Kunt
(2011), WDI, IMF
Share of total bank assets
held by top three banks*
Share of total bank assets held by top three
banks to total commercial bank assets in the
country. It stands for bank concentration.
Fernando et al. (2003),
Klapper et al. (2004)
Demirguc-Kunt
(2011), WDI, IMF
Total bank credits to total
bank deposits ratio*
Private credit by deposit money banks as a
share of demand, time and saving deposits in
deposit money banks in the country.
Khorana et al. (2005)
Demirguc-Kunt
(2011), WDI, IMF
Total life and non-life
insurance assets to GDP
ratio*
Total life and non-life insurance assets to GDP in
the country. It stands for a size of insurance
industry.
Khorana et al. (2005)
Demirguc-Kunt
(2011),
Real interest rates*
Average annual deposit rates adjusted for
annual inflation rate.
Fernando et al. (2003),
Klapper et al. (2004),
Khorana et al. (2005)
Bloomberg
Return of local MSCI**
Annual average of the MSCI monthly return
index of real local
market return. It is the most commonly used
indicator of market performance. It stands for a
return of local stock market.
Fernando et al. (2003),
Klapper et al. (2004),
Khorana et al. (2005)
Bloomberg
Volatility of local MSCI**
Annual standard deviation of the MSCI monthly
return index of
real local market return. It is the most
commonly used indicator of market volatility. It
stands for volatility of local stock market.
Fernando et al. (2003),
Klapper et al. (2004),
Khorana et al. (2005)
Bloomberg
Panel C. Quality of governance characteristics
Voice and accountability*
Reflects country citizens’ perceptions of the
extent of their capability
to effect their government selection.
La Porta et al. (1998),
Klapper et al. (2004),
Khorana et al. (2005),
Kaufmann et al.
(2009), WB
No. 1/2015
17
It also stands for citizens’ assessment of
freedom of expression, freedom of association,
and a free media.
Kaufmann et al. (2009)
Political stability*
Reflects country citizens’ perceptions of the
probability of unconstitutional overthrow and
government default, including terrorism.
La Porta et al. (1998),
Klapper et al. (2004),
Khorana et al. (2005),
Kaufmann et al. (2009)
Kaufmann et al.
(2009), WB
Government
effectiveness*
Reflects country citizens’ perceptions of the
quality of public services provided and public
polices implemented.
La Porta et al. (1998),
Klapper et al. (2004),
Khorana et al. (2005),
Kaufmann et al. (2009)
Kaufmann et al.
(2009), WB
Regulatory quality*
Reflects country citizens’ perceptions of the
quality of government policies aimed at
promotion of private initiative.
La Porta et al. (1998),
Klapper et al. (2004),
Khorana et al. (2005),
Kaufmann et al. (2009)
Kaufmann et al.
(2009), WB
Control of corruption*
Reflects country citizens’ perceptions of the
extent to which public power is exercised for
private gain.
La Porta et al. (1998),
Klapper et al. (2004),
Khorana et al. (2005),
Kaufmann et al. (2009)
Kaufmann et al.
(2009), WB
*
**
Annual data
Annualized data on the basis of monthly data, own computation
Financial Assets and Investing
18
Table 2 Descriptive statistics for chosen variables
All economies
High-income
economies
Middle-income
economies
Median IQR* Median IQR Median IQR
Panel A. Mutual fund industry development characteristics
All mutual funds (MF), bln USD 385.47 1329.70 536.16 1282.70 133.47 1265.20
Equity MF, bln USD 128.25 498.13 199.66 467.64 15.46 521.55
Fixed income MF, bln USD 62.08 124.05 102.84 174.28 15.99 86.08
Money market MF, bln USD 8.41 34.28 11.61 59.78 2.01 22.07
Panel B. Economic growth and development characteristics
GDP per capita, thsd USD 9.08 0.76 9.33 0.39 8.52 1.04
GDP growth rate, % 5.01 2.03 2.01 3.10 7.58 3.15
Gini index 30.84 8.87 27.25 7.69 34.00 8.83
Literacy rate, % 99.46 0.38 99.49 0.61 99.62 0.27
Newspapers per capita 695.56 760.20 335.35 261.33 1109.00 347.43
Internet users per capita 39.10 45.33 53.17 33.49 23.30 39.25
Total trade to GDP ratio, % 120.39 46.59 139.17 37.95 109.29 31.15
Sovereign debt to GDP ratio, % 31.00 30.30 37.20 23.98 19.59 25.86
FDI to GDP ratio, % 5.33 4.76 4.25 5.10 3.50 4.99
Financial crisis, 1 or 0 1 0 1 0 1 1
Panel C. Financial market development characteristics
Cap to GDP ratio, % 24319.00 20836.00 20000.00 16224.00 12937.00 28261.00
Total shares traded to GDP ratio, % 781.22 986.04 625.99 1199.60 97.45 218.06
No. 1/2015
19
Total shares traded to Cap ratio, % 2907.70 4219.70 3108.50 4301.30 647.67 1971.00
Total bank assets to GDP ratio,% 42.21 34.59 52.02 26.99 29.62 28.16
Share of total bank assets held by top
three banks, %
68.88 23.34 69.77 15.09 72.71 29.62
Total bank credits to total bank deposits
ratio, %
122.36 68.41 90.60 66.17 117.90 61.00
Total life and non-life insurance assets
to GDP ratio, %
236.61 173.50 313.75 79.30 151.00 89.70
Real interest rates, % 2.09 5.68 3.94 2.80 1.05 11.14
Return of local MSCI, points 627.58 603.08 461.16 735.76 600.00 593.43
Volatility of local MSCI, points 82.53 110.87 49.58 88.67 66.91 108.76
Panel D. Quality of governance characteristics
Voice and accountability, points 74.41 33.17 79.38 7.72 41.35 48.32
Political stability, points 67.93 24.63 75.47 15.05 52.40 36.53
Government effectiveness, points 73.17 34.79 77.62 7.34 40.67 47.50
Regulatory quality, points 77.94 39.39 80.95 9.94 39.71 49.88
Control of corruption, points 64.39 40.64 70.37 12.80 29.19 43.76
*IQR – interquartile range
Source: Own computations
Financial Assets and Investing
20
The ultimate group of factors that should be taken into consideration are the
ones referring to quality of governance and regulatory basis. On the basis of
studies by La Porta et al. (1998) and Kaufmann et al. (2009) it is natural to
assume that demand for mutual funds will be higher, if the legal system is
stronger. Following La Porta et al. (1998) and Kaufmann et al. (2009) for
evaluation the impact of quality of governance and regulatory basis on
mutual fund industry development the following explanatory variables are
used: (1) voice and accountability; (2) political stability; (3) government
effectiveness; (4) regulatory quality; (5) rule of law; and (6) control of
corruption (See Table 1).
For analyzing the assumed relationship between the chosen dependent
variable, that is, mutual fund industry size, and groups of chosen explanatory
variables – variables standing for economic growth and development,
financial and capital markets growth and development, and quality of
governance and regulatory basis – multivariate OLS for panel data is used:
= + +. . . + (1)
where: Y – mutual fund industry development; Xi – explanatory variables
referring to particular characteristics of economic and financial markets
development, and quality of governance; βi – estimates referring to direction
and strength of examined relationship.
The chosen repressors are checked for relevance by means of t-statistic, Fstatistic
and Information Criteria, that is, Akaike’s Information Criterion (AIC)
and Schwarz’s Bayesian Information Criterion (BIC). Out of 33 chosen
repressors only 25 turned to be relevant (See Table 1 and Table 2). Further
by means of F-statistics test, Breusch-Pagan test, Haussman test the
functional form of panel data regression was chosen – pooled OLS (the other
two testing variants were fixed effect and random effect OLS). Finally, the
represented regressions – for attributes explaining the total size of whole
asset management in CEE, for local equity mutual fund industry, and for local
fixed income and money markets mutual fund industries – are checked for
robustness by means of Durbin-Watson and Breusch-Pagan tests.
4 Results and Discussion
Having on average $385.47 billion of assets under management (AUM) in EUmember
and CIS-member states and growing at an annual rate of 35%, CEE
fund industry along with Latin American counterpart occupies the leading
position among the emerging mutual fund industries in the world having
Islamic and Asian fund industries lagging behind (Table 2 and Lemeshko and
Mukhacheva, 2014). A number of factors contributed to such outstanding
growth, among which the prominent role was played by rapid economic and
No. 1/2015
21
financial system development of CEE states: $1.97 billion of cumulative
regional GDP and $1.069.15 billion of regional market capitalization, growing
at an average annual rate of 5% and 27% respectively, which are nearly
twofold of EU’s average. Although such development is rapid and overall
regional progress in building local capital markets is impressive, the
development of fund industries within CEE varies from state to state: on the
one hand, there are four EU-member states, which are most important in
terms of industry development – Poland, the Czech Republic and Hungary whose
funds value account for more than 75% of that of CEE; and on the
other one there are CIS-member states, led by Russia, whose funds growth
account for more than 80% of that of CEE. Thus taking into account the
gradually growing importance of CEE fund industry for the world asset
management and high heterogeneity inside the group this paper aims is to
identify the key determinants of such rapid growth and variety of
development patterns.
Before presenting the obtained results it is necessary to state that majority of
factors, on the explanatory power of which many earlier existing studies
insisted, did not confirm in our research. Among factors, whose impact at
95% significance has not proved itself, there are national income
heterogeneity, literacy and mass media coverage rates, susceptibility to
financial contingency and crisis, capital market turnover and degree of bank
concentration and intermediation in transfer of funds – these variables were
dropped from the constructed regression due to low level of their low
explanatory power.
On the basis of the obtained results, presented in Table 3, we find a strong
positive relationship between mutual fund industry size, given by AUM to GDP
ratio, and national income, openness to trade and national government
indebtedness. This trend is common for all CEE economies - both EU-member
states (especially strong cases are Poland, the Czech Republic and Hungary)
and CIS-members states (Russia) – and it is consistent with earlier findings
by Klapper et al. (2004), Khorana et al. (2005), Demirguc-Kunt (2011).
Further we find that such relationship holds within a subsample of highincome
CEE economies, but partly fails for their middle-income counterparts,
whose asset management benefits from growth in national income, but
suffers from increase in sovereign debts made by their national governments.
This can be explained by the decreasing rate of return on fixed income assets
hold by local mutual funds, which is the predominant type of assets among
mutual funds in middle-income CEE economies. We also find that for the
development and growth of mutual fund industry in the middle-income
economies the important role play countries’ openness to FDI and access to
Internet, which is consistent with findings by Tulbure and Catarama (2009).
Financial Assets and Investing
22
This can be explained by low rate of people savings in such economies as
Russia and Ukraine, and, thus, higher dependence on foreign investment
inflows from abroad.
As for attributes given by development of financial systems in CEE
economies, so we find a strong positive impact of growth in local stock
markets liquidity and return, and bank assets to GDP ratio, which is common
for all CEE economies. Further within both high- and middle-income
subgroups we find a strong negative impact of growth in stock market
volatility and real interest rate on development and growth of local mutual
fund industries. All these findings are consistent with evidence provided by
Beck et al. (2010) and Čihák et al. (2012) and it can be explained by the
crucial roles of capital markets as the major targets and banks as major
providers of investments for asset management in general and for CEE
mutual fund industry in particular.
The ultimate group of factors, which could potentially explain the difference in
growth and development patterns of mutual fund industry across developed
and developing CEE economies, constitutes those measuring development of
regulatory basis and quality of governance. So we find that development and
growth of local asset management across all CEE economies is strongly
positively influenced by increase in freedom of expression and association,
including free media, increase in quality of public and civil services provided
by local authorities, and increase in formulation, implementation and longterm
commitment to sound policies aimed at promotion of individual initiative
and entrepreneurship. These results are consistent with evidence provided by
Klapper et al. (2004) and Khorana et al. (2005). Surprisingly, but we also
find the strongly opposite effect of political stability: on average, mutual fund
industries grow faster in those CEE economies, where there is higher
probability of unconstitutional overthrow and government takeover. This
could be the case of Russian and Ukrainian asset management under which
conditions of abnormal political risk and risk of national government default
offers high risk premiums, and, thus above-average local funds
outperformance.
No. 1/2015
23
Table 3 Determinants of mutual fund industry size in CEE economies, pooled OLS
All economies High-income economies Middle-income economies
Intercept 521.77 2878.92*** 635.30 7617.72*** 2494.93 7525.95 454.14* 722.06*
log GDP/capita (const. P, USD pc 2005) 37.050*** 184.874** 577.681** -39.472*** -11.303** 588.577** 46.175*** 86.927** 209.737***
(Ex+Im)/GDP (%) -1.978 2.711* 8.747** -3.897* 7.480 4.278 0.349 -1.529** 0.344
Central government debt / GDP (%) 14.553*** 15.285*** 10.266* 16.533*** 18.536*** 29.571** 0.184 0.896 -4.138*
FDI net/GDP (%) 16.778*** 0.566 -5.200 13.513** -2.826 -9.516 12.060*** 13.380** 22.017***
log Internet users (per 100 inhabitants) 6.046** 1.167 5.414 12.835*** 3.776 -1.351 2.320*** 2.126** 9.382**
Cap gross/GDP (%) -0.001 -0.001 -0.002 0.017 -0.001 0.040*
Turnover ratio (Stocks traded/Cap) 0.020 0.032 0.030* 0.040 -0.001 -0.002
Liquidity ratio (Stocks traded/GDP) 0.033* 0.075* 0.228 0.001* -0.017 -0.049
MSCI return 0.718*** 1.017*** 0.963*** 1.110** 0.103 0.151*
MSCI volatility -0.326** -0.093* -1.299* -0.907* -0.026 -0.111*
Real interest rate (%) -0.552** 5.557** -4.313* -39.466** -2.627 -7.313*
Bank assets gross/GDP (%) 4.476** 6.686** 5.304 8.654** 1.353** 2.173**
Insurance assets gross/GDP (%) 0.078 2.206 1.088 -2.711 0.024 0.124
Voice of accountability 22.813** 37.127*** 8.371*
Political Stability -17.093** 38.892*** -2.008**
Government Effectiveness 6.789* 25.283* 3.566*
Regulatory Quality 38.809** 89.239* 12.978*
Rule of Law -15.967 -13.885 -18.822
Control of Corruption -23.348 -20.898 7.868
R2, adj. 0.355 0.539 0.578 0.397 0.490 0.605 0.601 0.660 0.787
Number of observations 143 143 143 78 78 78 65 65 65
Table shows results for pooled OLS regressions with White’s standard errors.
*, **, and *** show significance at 10%. 5% and 1%.
Source: Own computation
Financial Assets and Investing
24
Table 4 Determinants of equity mutual fund industry size in CEE economies, pooled OLS
All economies High-income economies Middle-income economies
Intercept -408.56* -139.68 351.840** 370.950* -375.600* 947.360 -621.940* -256.300* -231.540**
log GDP/capita (const. P, USD pc 2005) 82.978** 133.104* -505.312* -361.508*** 518.784* -171.44** 689.927** 446.463 299.174
(Ex+Im)/GDP (%) 2.222 4.525* 4.254** 4.225 5.599 9.198 4.947 -10.526 -4.341
Central government debt / GDP (%) -22.128*** -20.681* -16.013** -25.569*** -11.939** -13.049** -1.244 -15.266*** -19.019***
FDI net/GDP (%) 20.884* 9.527 3.785* 18.080* 1.937*** 8.333* 81.388* 15.467* 59.897*
log Internet users (per 100 inhabitants) 13.972 10.673 10.102 11.472 1.981 18.515 4.749** 11.430* 15.088*
Cap gross/GDP (%) -0.001 0.001 0.025 0.040 -0.013 -0.008
Turnover ratio (Stocks traded/Cap) 0.089 ** 0.038* 0.044*** 0.041** 0.006** 0.023*
Liquidity ratio (Stocks traded/GDP) -0.350* -0.236 -0.230 * -0.305* -0.285* -0.436
MSCI return 5.173*** 5.535*** 6.213*** -0.841*** 7.760* 13.011**
MSCI volatility -2.197*** -13.405** -67.772*** -48.667* -11.230* 14.164*
Real interest rate (%) 0.506** 0.299* 0.157* -0.233* 1.175 0.643*
Bank assets gross/GDP (%) 2.691* 1.818 1.651 * 1.185 1.379 0.456*
Insurance assets gross/GDP (%) 0.103 -8.738 0.024 50.663 2.076 0.841
Voice of accountability -14.959* -21.853* -0.974*
Political Stability 14.388*** 113.439*** 13.928*
Government Effectiveness 1.689** 76.260* 66.722**
Regulatory Quality 23.896* -5.550 -24.992*
Rule of Law 6.032 13.050 -42.420
Control of Corruption 351.840 947.360 21.452
R2, adj. 0.2291 0.2973 0.3310 0.2196 0.2782 0.3060 0.2991 0.4696 0.4624
Number of observations 143 143 143 78 78 78 65 65 65
Table shows results for pooled OLS regressions with White’s standard errors.
*, **, and *** show significance at 10%, 5% and 1%.
Source: Own computation
No. 1/2015
25
Table 5 Determinants of fixed income mutual fund industry size in CEE economies, pooled OLS
All economies High-income economies Middle-income economies
Intercept -934.63 -103.62* -699.19** -405.74* -435.19 -996.73*** -18.56* 112.783* 217.150
log GDP/capita (const. P, USD pc 2005) 108.385* 107.913** 74.307** 443.347*** 471.918* -119.28* 7.761 -3.082 -21.082*
(Ex+Im)/GDP (%) 0.362 0.839* 0.923*** 0.448 1.046** 1.885** -0.487* -0.636** -0.814***
Central government debt / GDP (%) 0.810* 2.357** 2.484* 1.435* -3.794** -4.734** 0.060 0.575 0.285*
FDI net/GDP (%) -1.841*** -2.536 -2.609** -1.034*** -2.126 -2.795 * -2.140** -0.213 0.312***
log Internet users (per 100 inhabitants) 0.445* -0.338 -0.290* -0.769 -1.499 0.279 2.129* 1.864* 1.599
Cap gross/GDP (%) 0.000 0.001 -0.003 -0.003 0.000 0.000*
Turnover ratio (Stocks traded/Cap) -0.025* -0.023* -0.013* -0.011** 0.001* -0.002**
Liquidity ratio (Stocks traded/GDP) 0.057* 0.047 0.038* 0.001 -0.003 0.015
MSCI return 1.095*** 0.798** 1.370*** 0.553** -0.803** -0.715*
MSCI volatility 0.616* 1.687* -5.357** -5.335* -0.496* -1.073*
Real interest rate (%) 0.056* 0.019* 0.130* 0.142* 0.071* 0.041*
Bank assets gross/GDP (%) -0.296* -0.202** -0.282 -0.563 0.004* -0.059*
Insurance assets gross/GDP (%) -10.62 0.382 35.19 -1.269 11.84 -0.060
Voice of accountability -1.868* 0.963* 0.927**
Political Stability 4.388** 9.324*** 0.190**
Government Effectiveness -8.618 -3.796* 0.232
Regulatory Quality 7.712** 9.854 0.739
Rule of Law -1.325 9.165* -0.653
Control of Corruption -69.19 -99.73 21.150
R2, adj. 0.2707 0.3376 0.4244 0.3369 0.3941 0.6281 0.6197 0.7333 0.7378
Number of observations 143 143 143 78 78 78 65 65 65
Table shows results for pooled OLS regressions with White’s standard errors.
*, **, and *** show significance at 10%, 5% and 1%.
Source: Own computation
Financial Assets and Investing
26
Table 6 Determinants of money market mutual fund industry size in CEE economies, pooled OLS
All economies High-income economies Middle-income economies
Intercept -286.41 -320.68* -196.20** -136.17 -175.07* -162.71*** -66.73* 12.348* 38.397**
log GDP/capita (const. P, USD pc 2005) 28.658* 25.246** 13.728** 143.136** 172.112** 134.846*** 7.106 2.367** -2.151
(Ex+Im)/GDP (%) 0.198** 0.526* 0.531* 0.200 0.930 0.549* 0.016 -0.284 -0.242*
Central government debt / GDP (%) 0.817** 1.245** 1.346** -1.222*** 1.698** -2.720* 0.184** 0.061** 0.064*
FDI net/GDP (%) 1.628** 0.723** 0.653** 1.991*** 0.619 0.412* 0.229*** -0.125** 0.575**
log Internet users (per 100 inhabitants) 0.200 -0.096 -0.009 -0.011 -0.551 -0.251 0.428 0.518 0.389
Cap gross/GDP (%) 0.000 0.001 0.000* 0.001 0.000 0.000
Turnover ratio (Stocks traded/Cap) -0.003* -0.001 0.002* 0.000 -0.001* -0.001*
Liquidity ratio (Stocks traded/GDP) 0.009* -0.005 0.000* -0.006 -0.003 -0.005
MSCI return 0.495*** 0.427** 0.701*** 0.602*** -0.081** 0.001**
MSCI volatility 0.070* 1.482** -3.769* -1.906** 0.236* 0.002**
Real interest rate (%) 0.027 0.010 0.054* 0.023* 0.020* 0.007*
Bank assets gross/GDP (%) 0.019 0.103*** 0.061* -0.109* 0.015* -0.006*
Insurance assets gross/GDP (%) 0.194 -1.462 0.014 -2.750 0.348 -0.353
Voice of accountability 0.928* 2.421* 0.116*
Political Stability 0.891*** 2.567*** 0.759**
Government Effectiveness 2.393* 2.695** 0.312*
Regulatory Quality 2.505** 0.151** 0.322**
Rule of Law 1.202 7.834 0.016
Control of Corruption 1.201* 5.798* 0.895*
R2, adj. 0.3184 0.3563 0.4597 0.3751 0.4879 0.6506 0.5421 0.6572 0.6630
Number of observations 148 148 148 78 78 78 65 65 65
Table shows results for pooled OLS regressions with White’s standard errors.
*, **, and *** show significance at 10%, 5% and 1%.
Source: Own computation
DOI: 10.5817/FAI2015-1-2 No. 1/2015
27
If we consider attributes of development and growth of particular segments of the
mutual fund industry, such as equity, fixed income and money market mutual
funds, these attributes are very close to the ones which we observed in case of
overall CEE asset management, but with some exceptions. In general, there is a
significant positive relationship between decrease of central government debt,
development of local financial and capital markets, improvement of quality of
governance and development of local equity mutual funds. Growth of national
government indebtedness negatively effects the development of local equity
mutual funds in all CEE economies, while increase of inhabitants’ disposable
income stimulates growth of local equity asset management. The effect of the
later one is more significant in high-income economies, while the effect of the
former is more significant in middle-income economies. This can be explained by
higher share of fixed income and money markets mutual funds in middle-income
CEE economies, thus higher sensitivity of local asset management to changes in
central government debt, and higher share of equity mutual funds in highincome
CEE economies: when there is an increase in national government
indebtedness in middle-income CEE economies there is reorientation in capital
flows – there is a dry up of capital inflows for local equity funds in favor of capital
inflows for local fixed income and money market funds; in the case of highincome
economies, the local population has better investment opportunities
offered by local stockmarkets, thus delegating their savings to local equity asset
managers. An increase in local stock market turnover and liquidity as well as local
stock market return and volatility has a positive impact on development of equity
mutual funds in all CEE economies, however in high-income economies this
impact is higher than in their middle-income counterparts. Growth of local
banking industry is equally important for development of equity asset
management in both income groups. As for quality of governance and regulatory
basis, political stability and government effectiveness are the most important
determinants of growth of equity mutual funds in all CEE economies.
As for the segment of fixed income mutual funds, in general, there is a significant
positive relationship between an increase of country openness to trade and capital
inflows, development and stability of local financial and capital markets,
improvement of quality of governance and development of local fixed income
asset management. In particular, an increase of national economy’s openness to
trade and FDI is crucially important for growth of local fixed income funds. This is
true for both income groups. Additionally to this common regional condition, for
development of fixed income funds in high-income economies the increase of the
central government debt plays an important role. This can be explained by the
fact that fixed income funds are the predominant type of funds in CEE and the
main type of their assets are government bonds and eurobonds (Lemeshko and
Mukhacheva, 2014). Besides economic development, development of local
financial and capital markets is also important for growth of local fixed income
assets management: there is a significant positive relationship between increase
in local stock market return, turnover and liquidity with simultaneous decrease in
Financial Assets and Investing
28
its volatility on growth of fixed income mutual funds in all CEE economies.
However, in high-income CEE economies this impact is higher rather than in their
middle-income counterparts. This can be explained by higher degree of
interconnection between high-income CEE economies and their financial and
capital markets in comparison with middle-income CEE economies. Contrary to
this, development of the banking industry is more beneficial for middle-income
economies’ fixed income mutual funds, which can be again explained by higher
role of the banking sector rather than capital markets in development of middle
income CEE economies. As for quality of governance and regulatory quality, like
in case of equity mutual funds, political stability and regulatory quality are the
most significant factors for growth of fixed income asset management, which is
equally important in both income groups.
Likewise in previous cases of equity and fixed income mutual funds, the
development and growth of the last, but not the least segment of CEE asset
management industry, that is, money market mutual funds, is substantially
effected by increase of country openness to trade and capital inflows,
development and stability of local financial and capital markets, improvement of
quality of governance. In general, there is a significant positive relationship
between increase in inhabitants’ disposable income, country’s openness to trade
and FDI and growth of money market mutual funds in all CEE economies.
Increase in local stock markets return is another factor of CEE money market
funds development. Here it is necessary to mention, that although the impact of
stock market return is similar in high- and middle CEE economies, nevertheless
its volatility has a different impact: money market funds in high-income CEE
economies grow faster under condition of low stock market volatility, while
middle-income CEE economies require some degree of volatility for growth. This
can be explained by higher growth potential of stock markets from middle-income
economies and its interconnection with growth potential of local money market
asset management. Likewise in case of equity and fixed income mutual funds,
development of banking sector is equally important for growth of money market
mutual funds in both income groups. As for quality of governance, so in case of
money market mutual funds extension it is the most crucial role (in comparison
with cases of equity and fixed income mutual funds) – five out of six basic
attributes of quality of governance and regulatory basis are required - voice and
accountability, political stability, government effectiveness, regulatory quality and
control of corruption. This can be explained by the particularly demanding
regulatory and legislative environment, which is necessary for effective operation
of money market mutual funds and connected with this high risk for wellfunctioning
of national economies.
The obtained evidence on equity, fixed income and money market funds is in
compliance with previous findings of Klapper et al. (2004), Khorana et al. (2005),
Tulbure and Catarama (2009). In general it is possible to conclude, that all
categories of mutual funds as well as the whole asset management industry in
No. 1/2015
29
the CEE positively respond on between increase of country openness to trade and
capital inflows, development and stability of local financial and capital markets,
improvement of quality of governance and regulatory basis. Effect of change in
national government indebtedness is controversial: its increase represents a
source for further growth in the case of fixed income and money market funds
from middle-income economies, while in the case of local equity funds it creates a
kind of barrier; as for high-income asset management its decrease is more
favorable for all categories of funds rather than its increase.
5 Conclusions
The fast changing world of international capital markets and asset management
industry during the last decade experienced emergence and rapid development of
new players from Central and Eastern Europe. These high- and middle-income
CEE economies have all chances to become powerful competitors for their
counterparts from developing economies in the world, and provide good
investment opportunities for investors from developed economies.
The existing literature predicts that development of mutual fund industry depends
on a number of factors among which the predominant role belongs to economic
and financial system development and quality of governance and regulatory
basis. This paper reevaluates on the sample of high- and middle-income CEE
economies the impact of factors identified in previous studies. This study departs
from previous ones by using a new database of more than 5000 open-end equity,
fixed income and money market mutual funds operating in CEE during the last 13
years. Although the chosen sample does not cover as large number of countries
as previous studies, it provides an insight into CEE fund industry, documenting
important country and regional characteristics. Following established practice, for
evaluation of significance of particular growth factors and development attributes
the size of the mutual fund industry, given by its market capitalization to GDP
ratio is regressed by means of pooled OLS over a number of independent
variables, data on which was collected from a wide range of sources.
The obtained results have two dimensions. First of all, many factors, the high
explanatory power of which was stressed by earlier studies, turned out to be
insignificant in our research. Among factors, whose impact at 95% significance
has not proved itself, there are national income heterogeneity, literacy and mass
media coverage rates, susceptibility to financial contingency and crisis, capital
market turnover and degree of bank concentration and intermediation in transfer
of funds. This can be explained by the earlier stated fact that relevant studies
were structured mainly upon mature economies and, thus, their generalizations
and prediction may not work in the environment of developing economies. The
second dimension is confirmation of significance of a rather small number of
factors, whose role in development of asset management works in both
developed and developing economies. In particular, there was found a strong
Financial Assets and Investing
30
positive relationship between mutual fund industry size and national income,
openness to trade and national government indebtedness. Further a strong
positive effect of growth was found in local stock markets liquidity and return,
bank assets to GDP ratio, and indices referring to voice and accountability,
government effectiveness, regulatory quality, and a strong negative impact of
growth in stock market volatility, real interest rate and political stability on
development and growth of local mutual fund industries.
As for particular segments of the mutual fund industry, such as equity, fixed
income and money market funds, the earlier mentioned relationships hold within
these segments with some exceptions and particularities. In general it is possible
to conclude, that all categories of mutual funds in the CEE positively respond to
increase of country openness to trade and capital inflows, development and
stability of local financial and capital markets, improvement of quality of
governance and regulatory basis. As for particularities, so for growth of CEE
equity mutual fund industry an important role is played by the decrease of central
government debt, while for fixed income mutual fund industry the opposite
condition is true (i.e. increase in central government debt). This situation is
especially controversial in middle-income CEE economies. The growth of the
money market mutual fund industry is substantially effected by the increase of
country openness to trade and capital inflows and improvement of quality of
governance. The latter is especially important for all CEE economies - five out of
six basic attributes of quality of governance and regulatory basis are required.
The obtained results might be extended by further study of CEE funds riskadjusted
ability to beat the market and, if any, determinants of it.
Acknowledgements
Support of Masaryk University within the project MUNI/A/1127/2014 “Analýza,
tvorba a testování modelů oceňování finančních, zajišťovacích a investičních aktiv
a jejich využití k predikci vzniku finančních krizí” is gratefully acknowledged.
References
Adams, J. C., Mansi, S. A. and Nishikawa, T. (2012). Are mutual fund fees
excessive? Journal of Banking & Finance, 36(8), pp. 2245–2259.
Agnesens, J. (2013). A statistically robust decomposition of mutual fund
performance. Journal of Banking & Finance, 37(10), pp. 3867–3877.
Ammann, M., Kind, A. and Seiz, R. (2010). What drives the performance of
convertible-bond funds? Journal of Banking & Finance, 34(11), pp. 2600–2613.
Aspalter, C., Jinsoo, K. and Sojeung, P. (2009). Analysing the Welfare State in
Poland, the Czech Republic, Hungary and Slovenia: An Ideal-Typical Perspective.
Social Policy & Administration, 43(2), pp. 170–185.
No. 1/2015
31
Bakker, M.–R. and Gross, A. (2004). Development of non-bank financial
institutions and capital markets in European union accession countries. World
Bank Working Paper no. 28. Available at: https://ideas.repec.org/b/wbk/wb
pubs/15030.html.
Banegas, A., Gillen, B., Timmermann, A. and Wermers, R. (2013). The cross
section of conditional mutual fund performance in European stock markets.
Journal of Financial Economics, 108(3), pp. 699–726.
Bauer, R., Koedijk, K. and Otten, R. (2005). International evidence on ethical
mutual fund performance and investment style. Journal of Banking & Finance,
29(7), pp. 1751–1767.
Beck, T., Demirgüç-Kunt and Levine, R. (2010). Financial Institutions and Markets
across Countries and over Time. World Bank Economic Review, 24(1), pp. 77-92.
Bell, G. G. and Deng, S. (2013). Beyond clusters: How regional geographic
signature affects firm value and risk. Canadian Journal of Administrative Sciences,
30(2), 71–85.
Bengtsson, E. and Delbecque, B. (2011). Revisiting the European asset
management industry. Financial Markets, Institutions & Instruments, 20(4), pp.
163–190.
Benos, E. and Jochec, M. (2011). Short term persistence in mutual fund market
timing and stock selection abilities. Annals of Finance, 7(2), pp. 221–246.
Benson, K. L. and Humphrey, J. E. (2008). Socially responsible investment funds:
Investor reaction to current and past returns. Journal of Banking & Finance,
32(9), pp. 1850–1859.
Białkowski, J. and Otten, R. (2011). Emerging market mutual fund performance:
Evidence for Poland. The North American Journal of Economics and Finance,
22(2), pp. 118–130.
Bollen, N. P. B. and Busse, J. A. (2004). Short-Term Persistence in Mutual Fund
Performance. The Review of Financial Studies, 18(2), pp. 569–597.
Christoffersen, S. E. K. and Sarkissian, S. (2009). City size and fund
performance. Journal of Financial Economics, 92(2), pp. 252–275.
Čihák, M., Demirgüç-Kunt, S., Feyen, E. and Levine, R. (2012). Benchmarking
Financial Development Around the World. World Bank Policy Research Working
Paper 6175.
Cojocaru, L., Hoffman, S. D. and Miller, J. B. (2011). Financial development and
economic growth in transition economies: Empirical evidence from the CEE and
CIS countries. University of Delaware, Working Paper 2011-22.
Financial Assets and Investing
32
Cuthbertson, K., and Nitzsche, D. (2013). Performance, stock selection and
market timing of the German equity mutual fund industry. Journal of Empirical
Finance, 21, pp. 86–101.
Cuthbertson, K., Nitzsche, D. and O’Sullivan, N. (2008). UK mutual fund
performance: Skill or luck? Journal of Empirical Finance, 15(4), pp. 613–634.
Dariusz Filip, D. F. (2011). Performance Persistence of Equity Funds in Hungary.
Contemporary Economics, 5(1), pp. 18-34.
Demirgüç-Kunt, A., Feyen, E. and Levine, R (2011). The Evolving Importance of
Banks and Securities Markets. World Bank Policy Research Working Paper 5805.
Dubofsky, D. A. (2010). Mutual fund portfolio trading and investor flow. Journal of
Banking & Finance, 34(4), pp. 802–812.
Erdős, P. and Ormos, M. (2009). Return calculation methodology: Evidence from
the Hungarian mutual fund industry. Acta Oeconomica, 59(4), pp. 391–409.
Fernando, D., Klapper, L., Sulla, V. and Vittas, D. (2003). The global growth of
mutual funds. World Bank Development Research Group Working Paper No. 3055.
Available at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=636417.
Geranio, M. and Zanotti, G. (2005). Can mutual funds characteristics explain
fees? Journal of Multinational Financial Management, 15(4-5), pp. 354–376.
Gottesman, A. and Morey, M. (2012). Mutual fund corporate culture and
performance. Review of Financial Economics, 21(2), pp. 69–81.
Gottesman, A. A. and Morey, M. R. (2006). Manager education and mutual fund
performance. Journal of Empirical Finance, 13(2), pp. 145–182.
Harper, J. T., Madura, J. and Schnusenberg, O. (2006). Performance comparison
between exchange-traded funds and closed-end country funds. Journal of
International Financial Markets, Institutions and Money, 16(2), pp. 104–122.
Havrylchyk, O. (2009). Will Western European Banks pull out of Central and
Eastern Europe? La Lettre du CEPII, (288).
Hughen, J. C. and Mathew, P. G. (2009). The efficiency of international
information flow: Evidence from the ETF and CEF prices. International Review of
Financial Analysis, 18(1-2), pp. 40–49.
Huij, J. and Derwall, J. (2007). “Hot Hands” in bond funds. Journal of Banking &
Finance, 32(4), pp. 559-572.
Jackowicz, K. and Kowalewski, O. (2012). Crisis, internal governance mechanisms
and pension fund performance: Evidence from Poland. Emerging Markets Review,
13(4), pp. 493–515.
Jackowicz, K., Kowalewski, O. and Kozlowski, L. (2011). The Short and Long
Term Performance Persistence in the Central European Banking
No. 1/2015
33
Industry. Contemporary Economics, 5(4). Available at: https://ideas.repec.org/a/
wyz/journl/id224.html.
Jank, S. and Wedow, M. (2008). Sturm und Drang in money market funds: when
money market funds cease to be narrow. Deutsche Bundesbank Research Centre
Discussion Paper Series No 20/2008. Available at: https://ideas.repec.org/p/zbw
/bubdp2/200820.html.
Karagiannidis, I. (2010). Management team structure and mutual fund
performance. Journal of International Financial Markets, Institutions and Money
20(2), pp. 197–211.
Karagiannidis, I. (2012). The effect of management team characteristics on risktaking
and style extremity of mutual fund portfolios. Review of Financial
Economics, 21(3), pp. 153–158.
Kaufmann, D., Kraay, A. and Mastruzzi, M. (2009). Governance Matters VIII:
Aggregate and Individual Governance Indicators, 1996-2008. World Bank Policy
Research Working Paper 4978.
Khorana, A., Servaes, H. and Tufano, P. (2005). Explaining the size of the mutual
fund industry around the world. Journal of Financial Economics, 78(1), pp. 145–
185.
Klapper, L., Sulla, V. and Vittas, D. (2004). The development of mutual funds
around the world. Emerging Markets Review, 5(1), pp. 1–38.
La Porta, R., Lopez-de-Silanes, F., Shleifer, A. and Vishny, R. W. (1998). Law and
finance. Journal of Political Economy, 106(6), pp. 1113–1155.
Laeven, L. and Valencia F. (2012). Systemic Banking Crises Database. IMF
Economic Review, 61, pp. 225–270. DOI: 10.1057/imfer.2013.12.
Lemeshko O. and Mukhacheva G. (2014). Emerging markets mutual funds
performance evaluation: Evidence from the Central and Eastern Europe. In SGEM
Conference on Political Sciences, Law, Finance, Economics and Tourism Conference
Proceedings - Volume II Finance, pp. 241-248. DOI: 10.5593/
sgemsocial2014B22.
Narulita, W. A. and Parwada, J. T. (2012). Evolution of a mutual fund market:
Empirical analysis of simultaneous growth and decline by fund category in
Indonesia. Journal of International Financial Markets, Institutions and Money,
22(5), pp. 1217–1236.
Poshakwale, S. and Thapa, C. (2011). Investor protection and foreign equity
portfolio investments. Global Finance Journal, 22(2), pp. 116–129.
Prather, L., Bertin, W. J. and Henker, T. (2004). Mutual fund characteristics,
managerial attributes, and fund performance. Review of Financial Economics,
13(4), pp. 305–326.
Financial Assets and Investing
34
Rakowski, D. and Wang, X. (2009). The dynamics of short-term mutual fund
flows and returns: A time-series and cross-sectional investigation. Journal of
Banking & Finance, 33(11), pp. 2102–2109.
Ramos, S. B. (2009). The Size and Structure of the World Mutual Fund Industry.
European Financial Management, 15(1), pp. 145–180.
Thapa, C. and Poshakwale, S. (2010). International equity portfolio allocations
and transaction costs. Journal of Banking and Finance, 34(11), pp. 2627–2638.
Thapa, C. and Poshakwale, S. (2012). Country-specific equity market
characteristics and foreign equity portfolio allocation. Journal of International
Money and Finance, 31(2), pp. 189-211.
Tulbure, N. and Catarama, D. (2009). Institutional and Socio-Cultural Factors
Explaining the Development of Mutual Funds. A Cross-Country Analysis. MPRA
Paper. Available at: http://mpra.ub.uni-muenchen.de/20341/.
Varga, G. and Wengert, M. (2010). The growth and size of the Brazilian mutual
fund industry. Munich Personal RePEc Archive. Available at: http://mpra.ub.uni-
muenchen.de/21581/.
Vidal-García, J. (2013). The persistence of European mutual fund performance.
Research in International Business and Finance, 28, pp. 45–67.
Vinkler, P. (2012). The case of scientometricians with the “absolute relative”
impact indicator. Journal of Informetrics, 6(2), pp. 254-264.
Walter, A. and Moritz Weber, F. (2006). Herding in the German mutual fund
industry. European Financial Management, 12(3), pp. 375–406.