LIST OF FIGURE & GRAPH Figure 1.1: Summary the factors affecting fund performance 21 Figure 1.2: The conceptual framework 23 Graph 3.1: Total Asset Under Management AUM of investment fun
Significance of the study
A mutual fund, as defined by the Securities and Exchange Commission, is a company that pools money from multiple investors to invest in a diversified portfolio of stocks, bonds, or other assets Each investor owns shares that represent a portion of the fund's holdings This investment vehicle allows individuals to access a well-diversified portfolio with a relatively small investment, making mutual funds a popular choice in the finance industry, particularly in developed countries They serve as an effective alternative to traditional bank savings, playing a crucial role in the stable development of the stock market.
Established in 2003, the Vietnam Securities Investment Fund (VFMVF1) marked the inception of onshore funds in Vietnam, starting with a closed-ended structure and a fund size of 300 billion VND Over the past two decades, the fund management sector has witnessed remarkable growth, with the number of licensed securities investment funds soaring to 107 by the end of 2023, a significant increase from just 10 at the end of 2022 The average annual net asset value (NAV) growth for investment funds has exceeded 15% since 2011 By the end of 2023, the total assets under management by fund management companies are projected to reach approximately VND 639,000 billion, representing 6% of Vietnam's GDP and a nearly 16% increase from the previous year Despite this growth, a small fraction of Vietnamese private investors utilize funds for stock market investments, as indicated by data from the State Securities Commission.
Only 0.25% of the Vietnamese population invests in mutual funds and ETFs, a figure significantly lower than that of neighboring countries like Thailand and Malaysia This disparity highlights the substantial growth potential for the fund industry in Vietnam.
Institutional investors, particularly mutual funds, play a vital role in the steady and long-term growth of the stock market The performance of mutual funds is a key concern for investors, fund management boards, and regulatory agencies To enhance management effectiveness, attract investors, and foster a stable financial market, it is essential to evaluate and analyze the factors that influence mutual fund performance.
Research indicates that both macroeconomic and fund-level variables are crucial in identifying mutual funds that outperform the market (Banegas et al., 2013), with a significant focus on fund-specific factors However, in Vietnam, studies examining these influences remain limited, primarily emerging from research conducted since 2018.
2021, such as those conducted by Hoa & Dung (2019), and Nga & Trang (2022) As a result, I found the motivation to choose the topic “ASSESSING FACTORS
IMPACTING ON MUTUAL FUND PERFORMCE IN VIETNAM” for my graduation thesis.
Research objectives
The key objectives of the thesis include:
- Identify fund factors that influence mutual fund performance
- Evaluate the influence of each fund factor on mutual fund performance
- Recommendations for investors and proposed solutions to improve mutual fund performance
Research subject and research scope
The study focuses on the 10 mutual funds operating in Vietnam in the period from 2020 to 2023 Researched fund factors include: fund size, fund age, expense ratio, turnover, fund fees.
Research method
This thesis employs a mixed-methods approach, integrating qualitative and quantitative research techniques to achieve its objectives The author reviews existing literature to develop an optimal model specification and utilizes regression analysis methods, including Pooled OLS, Fixed Effects Model (FEM), and Random Effects Model (REM), to address the research questions Additionally, the study incorporates synthesis and analysis of data derived from financial statements.
Thesis structure
This thesis consists of the four following chapters:
LITERATURE REVIEW OF FACTORS IMPACTING ON
THEORETICAL BACKGROUND
A mutual fund, as defined by the SEC, is a company that gathers capital from multiple investors to invest in various securities, including stocks, bonds, and short-term debt instruments The total assets held by the mutual fund are referred to as its portfolio Investors purchase shares in these funds, with each share signifying a portion of ownership in the fund and its generated income (SEC, 2023).
Mutual funds are entities that collect funds from various investors and invest them in securities such as stocks, bonds, and short-term loans (Choudhary & Chawla,
A mutual fund aggregates capital from various investors to invest in financial assets, each with a specific investment objective like capital appreciation, high current income, or money market income These objectives are clearly stated by the mutual fund, allowing investors to select funds that align with their individual investment strategies (Reilly & Brown, 2020).
According to Clause 37, Article 4 of the Vietnam Securities Law 2019, a mutual fund is defined as a collective investment vehicle created from the capital contributed by investors, aimed at generating profits through investments in securities or other assets, including real estate Importantly, investors do not possess the authority to manage the fund's investment decisions on a daily basis.
A mutual fund is a financial institution that collects idle capital from various sources to invest in diverse assets such as stocks, bonds, and currencies These investments are expertly managed by a fund management company, a custodian bank, and other regulatory authorities, ensuring professional oversight and strategic allocation of resources.
Mutual fund managers invest in a diverse range of securities to achieve portfolio diversification, which reduces risk by balancing losses in some assets with gains in others Depending on the fund's objectives, investments can include equities, debts, and other asset classes like gold and real estate, spreading risk across various sectors This strategy ensures that even if one asset class underperforms in challenging market conditions, other classes can help stabilize the overall investment portfolio Mutual funds offer an affordable option for average investors to access professional money management and investment diversification similar to that enjoyed by large institutions and affluent individuals.
Mutual funds are managed by professionals who develop investment strategies aligned with the fund's objectives outlined in its prospectus These experts select investments based on thorough research and an understanding of market conditions and individual company performance As economic conditions evolve, the fund may alter its investment mix to adopt either a more aggressive or defensive approach to achieve its goals (ICI viewpoints, 2020).
Mutual funds primarily exist in two forms: open-ended and closed-end mutual funds, both offering high liquidity Open-ended mutual funds enable investors to redeem their shares at the end of each trading day for the net asset value (NAV), which is updated daily This creates an arbitrage relationship between the fund's price and its underlying assets; if the fund's price falls significantly compared to its assets, investors are likely to redeem their shares In contrast, closed-end mutual funds do not allow redemptions directly but are traded on stock exchanges, enabling investors to sell their units at the current market price, thus providing liquidity options.
Mutual funds regularly handle sales, redemptions, and exchanges as part of their daily operations The transaction volume can vary over time due to several influencing factors (Bodie et al., 2014).
The net asset value (NAV) is the price per share at which shares are redeemed, calculated by taking the current market value of all a fund’s assets, subtracting liabilities, and dividing by the total number of outstanding shares The offering price of a fund includes the NAV per share plus any front-end sales charge, while a fund without a sales charge has an offering price equal to its NAV per share It is essential for the NAV to accurately reflect the current market value of the fund’s securities, provided that market quotations are readily available, with other assets priced at fair value as determined by the fund’s board of directors (ICI viewpoints, 2020).
Taouab and Issor (2019) identify various performance concepts such as growth, profitability, returns, productivity, efficiency, and competitiveness Additionally, performance can be assessed from a financial perspective, utilizing accounting indicators tied to profits (Carton & Hofer, 2006; Combs et al., 2005; Richard et al., 2009) Financial efficiency pertains to how effectively a business mobilizes, manages, and utilizes its capital within its operational processes.
Organizational effectiveness, as defined by Lebans & Euske (2006), encompasses both financial and non-financial indicators that assess how well a business meets its objectives and outcomes It is characterized as a dynamic metric that requires ongoing evaluation and interpretation Additionally, organizational effectiveness is understood through the correlation between current actions and future results.
In the realm of finance, fund performance is defined as the effectiveness and efficiency with which a manager or investor meets their return and risk objectives According to Maheswari and Dineshkumar (2019), this includes growth funds that aim for high returns.
Investors seeking capital gains often face substantial risks, while income funds aim to provide a combination of cash dividends and capital gains, making them generally less risky than growth funds Both income and growth funds prioritize cash dividends, with capital gains being a secondary focus In contrast, balanced funds strive to achieve a blend of income, growth, and stability.
Mutual fund performance, as defined by Sama (2022), reflects a portfolio manager's success in balancing various rates of return with acceptable risk levels Evaluating this performance involves not only assessing returns but also considering the associated risks over a specific timeframe Sehgal and Babbar (2017) further elaborate that performance encompasses the fund's growth through total return, net asset value, dividends, and capital gains distributions within a designated period Ultimately, the performance of mutual funds should align with the investment objectives outlined in the fund's prospectus.
The performance of a mutual fund reflects the fund management company's effectiveness in meeting its investment objectives, including profitability and risk management Evaluating operational performance is crucial for assessing a mutual fund's success, enabling investors to make informed choices aligned with their financial goals and risk tolerance.
1.1.2.2 Indicators in evaluating mutual fund performance
Empirical research
The literature on mutual fund performance has evolved over the years, with various studies providing insights into different aspects of this topic
Sharpe's (1966) study revealed a positive correlation between low expense ratios and fund performance He also explored the impact of fund size on performance, finding a positive relationship that was not statistically significant Sharpe suggested that in an inefficient market, larger funds benefit from greater resources, enhanced analysis, and lower analysis costs Consequently, in an efficient market, funds with the lowest expenses are expected to demonstrate superior performance.
Gruber (1996) highlighted the growing popularity of actively managed mutual funds despite evidence suggesting that index funds outperform them He attributed this trend to pricing mechanisms, noting that funds were sold at net asset value Gruber posited that management ability contributes to performance predictability, which is often overlooked in pricing His study concluded that investors should focus on funds with low expense ratios to maximize returns.
A 2000 study by Dahlquist et al examined the Swedish mutual fund industry, focusing on funds from 1993 to 1997 It analyzed various fund characteristics, including size, expense ratio, past performance, and flows, while excluding foreign investment funds The findings revealed a negative correlation between fund size and performance, as well as between fees and performance Additionally, the study concluded that actively managed funds tend to outperform passive funds.
A research is made on the mutual fund industry in Europe by Otten and Bams
A study conducted in 2002 analyzed 506 funds from various European countries between 1991 and 1998, revealing that smaller funds tended to achieve higher returns, indicating a negative correlation between fund size and performance Additionally, the research found no significant link between expense ratios and fund performance While a negative relationship between fund age and risk-adjusted performance was noted, significant results were only observed for funds based in the UK and Germany, with other findings being insignificant.
A study by Chen et al (2004) analyzed the performance of mutual equity funds in the US from 1962 to 1999 using regression models to assess the relationship between fund characteristics and performance The findings revealed a negative correlation between fund size and performance, as well as between expense ratio and performance Additionally, the study concluded that fund age and fund flow did not significantly impact performance Furthermore, it was determined that team-managed funds tend to underperform compared to those managed by individuals.
A study by Otten and Thevissen (2011) examined mutual equity funds in Europe from 1992 to 2006, revealing a positive correlation between fund size and performance However, conflicting findings regarding the relationship between size and fund performance prompt further exploration of this variable.
Ferreira et al (2013) did a study on the determinants of mutual fund performance across 27 countries The study focused on funds that invest in their domestic markets
The study employed the Carhart Four Factor Model to assess risk-adjusted performance, analyzing variables such as fund size, family size, age, fees, expenses, management structure, and the number of countries in which funds are sold The findings revealed significant differences between US funds and those from other countries, highlighting the unique characteristics of the US funds industry.
The fund market industry in the USA is larger and more established than in other countries Research indicates that smaller funds tend to outperform larger ones in the USA, while the opposite trend is observed in some other nations However, a positive relationship between fund size and performance has been identified for non-US funds Additionally, Ferreira et al (2013) found that non-US funds exhibit a negative correlation between expense ratios and performance This study also revealed a statistically significant negative relationship between fund age and performance, indicating that younger non-US funds generally achieve better results.
A study by Fama and French (1993) analyzed data from 2,384 mutual funds between 1970 and 1990, revealing that poor operational effectiveness correlates with high transaction fees Funds with transaction fees exceeding 2% experience a return rate that is 1.5% lower than those with fees below 0.5% This negative relationship between fund fees and performance is further supported by evidence from Europe (Petajisto, 2013).
Fan (2018) highlighted the importance of minimizing invisible costs through position-adjusted turnover ratio to enhance mutual fund performance In a study by Faadilah et al (2020) on Islamic equity mutual funds in Indonesia, it was revealed that while fund size and expense ratio did not significantly impact performance, a higher turnover ratio positively influenced fund outcomes.
A study by Kariuki et al (2014) revealed that macroeconomic variables significantly impact the performance of mutual funds with equity portfolios in Kenya, as licensed by the Capital Markets Authority The research identified five key independent variables—money supply, interest rate, inflation rate, GDP, and exchange rates—that collectively account for 70.9% of fund performance The findings indicate that money supply, interest rate, inflation rate, and GDP have a positive and significant influence on fund performance, while the exchange rate exerts a negative effect.
20 significantly influences fund performance among mutual funds operating in Kenya with equity portfolios licensed by the Capital Markets Authority
Gusni and Hamdani (2018) evaluated equity mutual fund performance and identified factors that affect mutual fund performance with 19 equity mutual funds from
From 2011 to 2015, a study in Indonesia analyzed the risk-adjusted performance of mutual funds, focusing on factors such as investment managers' market timing and stock selection skills, fund size, and inflation The findings revealed that only stock selection skill and inflation positively impacted equity mutual fund performance, while market timing skill and fund size had no significant effect.
In a study by Tulamy (2013) analyzing panel data from 11 mutual funds in Iran, a positive relationship was identified between exchange rates and fund returns Conversely, Singh et al (2011) discovered a negative correlation between exchange rates and stock returns for medium and large portfolios in Taiwan.
A study by Nguyen Thi Hoa et al (2019) examined the influence of country-level and fund-level factors on mutual fund performance in Vietnam from 2015 to 2018 The findings indicate a positive correlation between macroeconomic conditions and mutual fund performance Additionally, factors such as regulatory effectiveness, political stability, economic growth, and financial development at the country level also positively impact mutual funds Conversely, the study reveals varied effects of fund-level factors, noting that board size does not significantly affect mutual fund performance, while passive funds outperform active funds in the Vietnamese market.
The research of Nguyen Hong Nga et al., (2022) using the data of 11 open-ended mutual funds in Vietnam focuses on the effect of expense on the fund performance The
21 finding is that the expense ratio has a detrimental negative effect on the performance of open-ended funds in Vietnam in the period 2018 - 2021
Nguyen Hoai Loc's 2023 study assesses the performance of open-ended funds using the Treynor ratio, identifying key influencing factors such as fund manager proficiency, fund size, and macroeconomic variables like inflation and exchange rates Analyzing data from 14 open-ended funds between 2015 and 2022, the findings reveal that stock selection skills, inflation, and exchange rates significantly impact fund performance in the Vietnamese market However, factors like market timing skills and fund size do not appear to affect performance.
Research gap
Despite extensive research on fund performance primarily focusing on developed markets like the US, UK, and EU, there has been limited investigation into investment funds in Vietnam, particularly during periods of macroeconomic instability Additionally, a comprehensive analysis of the relationship between mutual fund performance and various fund variables is lacking This research aims to enlighten investors and the public on essential factors to consider when investing in equity mutual funds, while also providing valuable recommendations for both investors and fund administrators in Vietnam.
Research framework
A comprehensive literature review highlights the significant role of the mutual fund sector in the global expansion of capital markets, revealing several understudied areas in Vietnam The study's conceptual framework, illustrated in Figure 1.2, is based on factors affecting performance evaluation and prior research Utilizing the theoretical premise that stock prices reflect all relevant information, the author measures fund performance through stock price fluctuations, specifically using NAV growth as the dependent variable Independent variables include fund-specific characteristics such as size, age, fees, expense ratios, and turnover ratios.
DATA AND METHODOLOGY
Data
This article analyzes 10 prominent open-ended mutual fund management companies in Vietnam from 2020 to 2023, utilizing a dataset of 480 observations The secondary data is sourced from the funds' monthly reports and official websites Selected funds must have been operational prior to January 2020 and provide detailed reports on their investment activities from January 2020 to December 2023.
In 2023, significant fluctuations in the global financial market, driven by the COVID-19 pandemic, the Russia-Ukraine war, and various macroeconomic factors, have created an ideal environment to assess the adaptability and performance of mutual funds amidst these challenges.
Hypothesis development
In alignment with the beliefs regarding fund performance outlined in Chapter 1, the author selects several key variables likely to influence fund performance to achieve the study's objectives The research hypothesis is formulated based on these considerations.
Hypothesis Expectation Research support the hypothesis
H1 There is a positive relationship between the fund’s age and its performance
Gregory et al., (1997), Simutin (2014), Rao et al
H2 There is a positive relationship between the
25 fund’s size and its performance
(2013), Bauer R et al., (2002), Ansari H & Shah FM (2016) H3 There is a negative relationship between the fund’s expenses ratio and its performance
Sharpe (1966), Ippolito (1989), Elton et al (1993), Gruber
(2011) H4 There is a negative relationship between the fund fees and fund performance
Prather et al., (2004); Dellva & Olson (1998); Elton, et al., (1993); Golec (1996), Edelen et al (2013) H5 There is a negative relationship between turnover and fund performance
Research model
The author's research uses a linear regression model to analyze factors that impact research variables The model uses a general formula summarized as:
Xn: independent variable or explanatory variable
The Yi variable is the growth of NAV of fund Based on the hypothesis development and previous research, the econometric model is illustrate as below:
R it = 0 + 1 * Age it + 2 *Size it + 3 *Expense it + 4 *Fees it + 5 *Turnover it + it
R it : NAV growth rate of fund i in month t
Age it : Age of fund i in month t
Size it : Size of fund i in month t
Expense it : Expense ratio of fund i in month t
Fees it : Fees of fund i in month t
Turnover it : Turnover ratio of fund i in month t
Variables
This study evaluates the performance of open-ended mutual funds in the Vietnamese stock market by analyzing the growth rate of the fund's Net Asset Value (NAV), following methodologies established by Babalos et al (2009) and Hoa & Dung (2019).
R it R it : average return of the fund
NAVit: Net Asset Value of fund i this month
NAVit-1: Net Asset Value of fund i the month before
The age of a mutual fund, measured in months from its establishment to the data collection date, can influence its performance Younger funds often encounter higher start-up costs due to diseconomies of scale, which may impact their overall returns Additionally, the initial cash flows of these funds significantly affect transaction costs, further complicating their financial outcomes.
The performance of mutual funds can be influenced by their age, with newer funds potentially requiring a learning period for optimal returns (Gregory et al., 1997) Investors may achieve higher profits by selecting funds with a longer track record, as these funds often demonstrate better performance over time Conversely, if a fund's performance diminishes as it ages, it may be prudent for investors to avoid older funds (Webster, 2001).
The fund size, determined by the total value of outstanding Fund Certificates at the end of each month, significantly influences mutual fund performance While larger funds can benefit from cost efficiencies due to fixed expenditures constituting a smaller portion of overall expenses and generating higher management fees for the fund house, research indicates that larger funds often experience diseconomies of scale, leading to underperformance compared to their smaller counterparts.
The operating expense ratio of a mutual fund indicates the proportion of operating expenses relative to its average net asset value Numerous studies have demonstrated that this ratio significantly influences the fund's performance.
Fund fees are essential costs that investors incur when investing in mutual funds, and these fees can differ significantly among various funds This research will focus on calculating fund fees, specifically examining two primary types: broker fees and clearing settlement fees.
The portfolio turnover ratio reflects the extent to which a fund's investment portfolio is adjusted over a specified period, with a higher ratio signifying more frequent restructuring This "turnover" occurs when mutual fund managers buy and sell equities to optimize the portfolio, which can lead to transaction fees and potential tax implications for investors While elevated turnover rates can increase costs such as brokerage and custody fees, they do not inherently indicate poor fund quality Typically, lower turnover rates are associated with higher quality investments, whereas growth funds, which engage in more active trading, usually exhibit higher turnover rates.
No.Variable Definition Measurement Source
The growth of fund in term of net asset value (NAV)
Age Fund age Number of months since the fund lauch date
Size Fund size Total value of outstanding
Expense The ratio of a fund's operating expenses to its average net asset value
Fees The fees that investors have to pay for transaction
Clearing settlement fee and broker fee payable
Turnover The fund's investment portfolio changes (rotates) during the period
(Total purchase value + Total sales value)/( 2 x Average net asset value during the period)
Methodology
The study employs various regression techniques, including the Pooled OLS model, Fixed Effects Model (FEM), Random Effects Model (REM), and FGLS model, to analyze the factors influencing the data and their respective impact levels The author tests these methods to determine the most suitable regression approach If defects are found in the FEM or REM models, the FGLS method will be utilized; otherwise, the optimal choice will be either FEM or REM.
Pooled OLS (Pooled OLS) regression method
Pooled Ordinary Least Squares (Pooled OLS) is the initial regression method employed due to its simplicity and ease of use This technique operates under the assumption that the intercept and slope coefficients remain constant over time for the observed samples However, a significant drawback of Pooled OLS is its potential to yield biased and meaningless estimates, as it fails to account for the unique factors affecting the research subject To enhance the model's validity and address the limitations of Pooled OLS, the author plans to utilize Fixed Effects Model (FEM) or Random Effects Model (REM) methods.
Fixed Factor Effects Method (FEM)
The Fixed Effects Model (FEM) method examines the relationship between explanatory variables and residual units, allowing for the separation of unit correlation effects from the explanatory variables This approach aims to provide a precise estimation of the actual impacts that explanatory variables have on the dependent variable.
This method is represented by the following general model:
The REM method differs from the FEM method in that changes in units within the FEM are interconnected, whereas the REM method features irregular changes that do not influence the regressors.
This method is represented by the following general model:
C i in this model is considered a random variable, has no rules and is represented as follows: C i = C + i
From this, the formula of REM is:
No research model can completely eliminate unobserved variables, making the selection of an appropriate estimation method crucial The Pooled OLS method is ideal when all necessary variables are included in the research model However, if there are omitted variables, two scenarios arise: if observed and unobserved variables are related, the Fixed Effects Model (FEM) yields optimal results; conversely, if they are unrelated, the Random Effects Model (REM) is more suitable After applying these regression methods, further tests are conducted to determine the most appropriate model.
The F-test tests whether the influence of fixed factors is equal to 0 or not to find an appropriate regression model between the two Pooled OLS and FEM methods
The Hausman test examines whether autocorrelation exists between random errors and independent variables to find an appropriate regression model between the two methods FEM and REM
The Pooled OLS model may yield misleading coefficients, making it suboptimal for regression analysis To address this issue, Fixed Effects Model (FEM) and Random Effects Model (REM) can be employed; however, these methods also carry the risk of defects that could compromise the effectiveness of the regression results Consequently, this thesis will implement two tests to evaluate the integrity of the regression models derived from FEM and REM methodologies.
Wald test: check and detect the phenomenon of heteroskedasticity
Wooldridge test: check and detect autocorrelation phenomenon
If the initial tests indicate that the model is functioning correctly, the FEM or REM method will be selected for regression analysis However, if these tests reveal any issues with the regression results, the FGLS method will be employed to enhance the research model.
RESULTS AND DISCUSSION
Overview of mutual fund in Vietnam
The establishment of securities investment funds is crucial for the long-term viability of the stock market in Vietnam The Vietnam Securities Investment Fund (VFMVF1), the first onshore fund, was launched in 2003 as a closed-ended fund with an initial size of 300 billion VND Over nearly two decades, the fund management industry has experienced significant growth in the number of funds, total assets under management, and the variety of investment fund types The evolution of Vietnam's fund industry can be categorized into two primary stages.
Between 2003 and 2010, the landscape of securities investment funds began to take shape, marked by the establishment of several fund management companies, including Vietcombank Fund Management (VCBF), Bao Viet Fund Management, and MB Capital During this period, the majority of funds were private, with only six public close-ended funds available: VFMVF1, VFMVF2, VFMVF4, PruBF1, MAFPF1, and ACBGF.
Since 2011, following the financial crisis, the investment fund landscape has evolved significantly, with a notable rise in open-ended stock investment funds, which now dominate the market Currently, there are 43 licensed fund management companies operating under the State Securities Commission This era has seen a qualitative shift in investment funds, with private and closed-end funds being increasingly replaced by mutual funds, including open-ended funds, ETFs, and real estate investment funds The introduction of ETFs has notably enhanced market liquidity and broadened investment opportunities for investors Between 2009 and 2019, the global asset scale of managed ETFs surged nearly 400%, reaching approximately 11.4 trillion USD by November 2019.
19, 2019, showing the role of ETFs In Vietnam, the number of ETFs has increased significantly, including both foreign ETFs and domestic ETFs
By the end of 2023, the total assets under management by fund management companies in Vietnam are projected to reach VND 639,000 billion, representing 6% of the country's GDP and a nearly 16% increase from 2022 However, only VND 68,000 billion, or 11% of these assets, is allocated to investment funds, while the trust portfolio constitutes the remaining 89%, totaling approximately VND 571,000 billion.
Graph 3.1: Total Asset Under Management (AUM) of investment funds in
Vietnam in period 2013 – 2023 (unit: billion VND)
(Source: State Securities Commission of Vietnam)
As of the end of 2023, the total number of licensed securities investment funds has reached 107, marking an increase of 10 funds from the end of 2022 and nearly doubling since the end of 2020 This growth reflects a significant average annual increase in the net asset value (NAV) of investment funds.
Since 2011, the annual growth rate has exceeded 15%, with ETF funds experiencing remarkable growth in recent years Notable examples include the DCVMVVN Diamond ETF Fund, E1VFVN30 ETF Fund, and SSIAM VNFIN Lead ETF Fund.
Graph 3.2: Quantity and total net asset value of investment funds in Vietnam in the period 2011-2023 (unit: billion VND)
(Source: State Securities Commission of Vietnam)
Vietnam's fund management organizations have demonstrated successful operations, evidenced by the significant growth in assets under management and the increasing investment capital they have attracted This sector plays a crucial role in enhancing investor-market interactions and generating the stable, long-term capital essential for the development of the stock market, while also facilitating its gradual integration with other markets.
In the Vietnamese securities market, a small fraction of private investors choose to invest in funds According to data from the State Securities Commission, as of March 31, 2023, only 212,636 investors were involved in open funds.
With only 35,581 investors participating in ETF funds, representing just 0.25% of the Vietnamese population, Vietnam's engagement in this investment vehicle is significantly lower than that of neighboring countries like Thailand and Malaysia Several factors contribute to this notably low participation rate.
Currently, there is no formalized procedure for distributing fund certificates in Vietnam, as the Law on Credit Institutions prohibits banks from doing so directly, requiring them to use subsidiaries instead This limitation restricts banks from leveraging their extensive networks Securities firms focus primarily on brokerage services and have not prioritized fund certificate distribution Additionally, emerging online platforms account for only a small fraction of the total distribution value of fund certificates Furthermore, individual investors in Vietnam often lack knowledge about personal financial management and do not view investing as a vital tool for financial control Many still question the long-term benefits of investment funds, perceiving stocks mainly as short-term, speculative opportunities Lastly, the diversity of fund offerings in Vietnam is limited, with available investment methods primarily centered around stock, bond, or balanced fund investments due to a scarcity of investment tools.
Despite the global rise of ESG (environment, social, and governance) funds, Vietnam has yet to embrace the trend of environmental investing The investment strategies of these funds lack clear differentiation, with few products outlining specific methods such as investing in large-cap or mid-cap securities or adopting growth versus value investing approaches Many funds do not utilize their own reference indices, opting instead to rely on the VNindex Additionally, investors often struggle to distinguish between open-end fund products and exhibit a limited understanding of asset allocation techniques and investment instruments.
In general, despite some progress over the years, investment funds' operations in Vietnam remain restricted in comparison with the potential of the market The function of
The investment fund sector, consisting of 38 funds, plays a crucial role in attracting capital, guiding individual investors, and enhancing stock market stability, yet it remains underappreciated Compared to the overall trading volume of stocks, warrants, and bonds, the number of funds listed on the Stock Exchange is minimal, indicating substantial potential for growth within the industry To realize this potential, all stakeholders in the fund value chain—including investors, securities companies, fund managers, regulatory agencies, and management firms—must collaborate to ensure the sector evolves alongside the economy, supports consistent stock market growth, and emerges as a vital source of capital.
Descriptive analysis
Variable N Minimum Maximum Mean Std.deviation
Table 3.3 presents the average values, standard deviations, minimum, and maximum values of the research variables in the model from 2020 to 2023, offering a comprehensive overview of both dependent and independent variables based on a sample of 480 mutual funds.
The return of funds measure by NAV growth in 4 years recorded an average of 1,37% per month The maximum number is about 7,65%, which recorded on
In August 2020, the VINACAPITAL-VFF fund faced challenges, while the VEOF fund hit a low of -29.92% in March 2020, coinciding with the onset of the Covid-19 pandemic The macroeconomic conditions negatively affected both funds, yet their performance outcomes varied significantly, highlighting the influence of internal fund management issues For Vietnamese investors, mutual fund returns appear less appealing compared to alternative investment options, such as the stock market, which offers higher yields, or banks, which provide similar returns with lower risk.
The average expense ratio for funds is 0.01959, indicating that operating expenses represent approximately 1.959% of the average monthly total net asset value The highest recorded expense ratio is 3.51% for the SSISCA fund in February 2021, while the lowest is 0.13% for the BVFED fund in January.
The turnover ratio of the funds ranged from 0 to 4,008.8, with an average of 58.69%, indicating the frequency of trading based on the fund's investment strategy A higher turnover ratio suggests more active trading, potentially increasing transaction costs The average fund size is 217.05 billion VND, with Vinacapital-VFF being the largest fund, valued at 797.5 billion VND as of March 2021 Additionally, the funds in the sample vary in age, with an average age of approximately 27.8 months, or just over two years.
Correlation analysis
R Age Expense Fees Turnover Size
Table 3.4 presents the correlation coefficient matrix for the research model's variables The Expense variable has the strongest negative impact on the dependent variable (R) at -54.23%, while the Age variable shows the weakest association, with a correlation coefficient of -2.27% Overall, the correlations between the independent variables and the dependent variable align closely with the theoretical framework outlined in Chapter 1, with the exception of the correlation involving the Age variable.
In analyzing the relationship between independent variables, correlation coefficients tend to be relatively low The strongest correlation is observed between the Fees and Turnover variables, with a value of 44.91% Conversely, the weakest correlation occurs between Age and Fees, which is recorded at -0.66%.
Since every variable's coefficient is less than 0.8, multi-collinearity does not exist This outcome is encouraging for regression analysis using FEM, REM, and Pool OLS
To be more precise, the author determines the severity of multicollinery using the variance inflation factor (VIF technique) Multicollinery is present if the value is higher than 10 (Pallant, 2016)
The VIF test result demonstrates that there is no value larger than 10, indicating the absence of multicollinearity
Table 3.5: VIF test for multicollinearity between variables
Variable Turnover Fees Size Expense Age
Regression results
Table 3.6: Regression results of Pool OLS, FEM, REM
Note: p_value of estimated regressors are presented in parentheses
The regression results using Pool OLS, FEM, and REM methods, presented in Table 3.6, reveal that most factor correlations with Rit align with the author's initial hypotheses, with the exception of the Age variable in the FEM and REM models The R-squared value across all three models is approximately 36%, indicating that the independent variables account for 36% of the variance in the dependent variable Notably, the Turnover variable is statistically insignificant in all three models, while the Age variable is significant at the 5% level in the FEM model but not in the Pooled OLS and REM models Additionally, the variables Expense, Fees, and Size demonstrate statistical significance at the 1% level across all models.
To determine if the FEM or OLS model is a better fit for the study, the author performs Fisher's test Hypothesis:
HO: There is no difference between the subjects or times
H1: There is a difference between different objects or times
The p-value of 0.000, which is significantly lower than 1%, provides strong evidence to reject the null hypothesis (H0) in favor of the alternative hypothesis (H1) Consequently, the regression model utilizing the Fixed Effects Model (FEM) method is determined to be more optimal compared to the Pooled Ordinary Least Squares (OLS) approach.
A acceptable model between FEM and REM is selected using this test Hypothesis:
HO: There is no correlation between the explanatory variables and the random components (the REM model is suitable)
H1: There is a correlation between the explanatory variables and the random elements (the FEM model is suitable)
P-value = 0.0077 smaller than 1%, so HO is rejected FEM is chosen in this test
The F-Tests and Hausman test indicate that the Fixed Effects Model (FEM) is the most suitable technique for analyzing the determinants affecting mutual fund performance using this type of panel data Nonetheless, the FEM method may not be the most optimal choice, as potential defects could still arise in the model Therefore, the author continues to investigate the presence of autocorrelation and heteroskedasticity within the FEM framework.
Ho: There is constant variance
H1: The variance is not constant
Since p = 0.0000 < 0.01 At the 1% level of significance, this model has Heteroskedasticity
Since p = 0.1055 > 0.05 At the 5% level of significance, this model has no autocorrelation
The findings from the tests indicate the presence of heteroskedasticity in the Fixed Effects Model (FEM), which may lead to biased regression estimates To address this issue, the author employs the Feasible Generalized Least Squares (FGLS) approach, as recommended by Judge, Hill et al (1988) This method effectively corrects for such imperfections, enhancing the significance of the results Consequently, the FGLS technique is utilized to improve the efficiency of the research model, with the subsequent table presenting the regression coefficients and p-values after applying the FGLS model.
Table 3.7: FGLS fixed regression model results
Discussion the research’s finding
The study reveals a negative correlation between the Expense ratio and Turnover ratio of mutual funds and their performance in Vietnam, while Size positively correlates with Net Asset Value growth rate Notably, the Expense factor significantly impacts mutual fund performance, whereas fund fees and age show no significant relationship with the dependent variable These correlations are derived from the FGLS fixed regression model at a 1% significance level.
Expense ratio and fund performance
The analysis reveals a significant negative relationship between the Operating Expense Ratio and mutual fund performance, indicated by an estimated coefficient of -7.88, a standard error of 0.555, and a P-value of 0.000, which is below the 1% significance level This suggests that a 1% increase in the operating expense ratio leads to a 7.88% decrease in the growth rate of the mutual fund's net asset value, highlighting the importance of controlling operating expenses to enhance fund performance High operating expenses adversely affect after-tax profits, limiting the growth of net asset value These findings align with similar conclusions drawn in previous global fund case studies, including research by Carhart (1997), Dahlquist et al (2000), and Ferreira et al (2013).
Research results have shown that the size of a fund has a positive impact on the fund efficiency, similar to the findings of Tangjitprom N (2014), Ferreira MA et al.,
Research indicates that a 1% increase in fund size correlates with a growth rate of net asset value (NAV) by approximately 0.0000475%, highlighting the advantages of larger funds These large-scale funds leverage their superior resources to capitalize on market opportunities, optimize resource utilization, and drive productivity in businesses Additionally, they possess a competitive edge in financial capital, human resources, and reputation compared to smaller and medium-sized funds Notably, large mutual funds tend to employ value and momentum strategies more frequently, further enhancing their market position.
Research indicates a negative correlation between turnover ratio and mutual fund performance, with a 1% increase in turnover leading to a 0.0427421% decrease in NAV growth Investors should consider the turnover ratio, as it significantly impacts fund performance, costs, and risks High turnover rates incur transaction costs like brokerage fees and spreads, which can detrimentally affect fund performance Frequent buying and selling of securities due to high turnover raises these costs, aligning with findings from previous studies by Carhart (1997), Wermers (2000), and Jan and Hung (2003).
Table 3.8: Summarize the findings of the research
Variable Expectation Finding Hypothesis result
Note: (+) impact in the same direction, (-) impact in the opposite direction, (N/A) not statistically significant (Source: Author’s estimation)
Table 3.6 highlights the factors impacting mutual fund performance in Vietnam from 2020 to 2023, including Expenses, Age, Size, Fees, and Turnover The size of the fund positively affects its operational efficiency, aligning with initial expectations Conversely, Expenses and Turnover negatively impact mutual fund performance, which also meets initial predictions In contrast, Age and Fees show little to no influence on economic development programs, contrary to initial expectations of their positive or negative effects Overall, the study's results align with existing research and closely adhere to the original research hypothesis.
CONCLUSION AND RECOMMENDATION
Conclusion
This study analyzes the factors influencing mutual fund performance in Vietnam from 2020 to 2023, focusing on a sample of ten prominent mutual funds Utilizing a regression model, it examines the relationship between key variables—operating expense ratio, asset turnover, fund size, fund age, and fund fees—against fund returns.
The findings indicate a negative correlation between operating expense ratio and asset turnover with fund returns, suggesting that funds with higher expenses and turnover tend to underperform Conversely, larger funds demonstrate a positive correlation with performance, implying that they benefit from economies of scale Additionally, the study found no significant relationship between fund age, fund expenses, and mutual fund performance.
Recommendation
4.2.1 Recommendation for the fund managers
In light of the study's findings, the author provides fund managers with the following suggestions to enhance fund performance
Fund managers should prioritize managing the operating expense ratio, which includes costs such as management fees, custody fees, supervising fees, fund administration fees, and transaction fees Research indicates that a 1% increase in the operating expense ratio can lead to a 7.88% decline in fund performance, highlighting the significant impact of operating expenses on profitability With an average expense ratio of 1.96% identified in the study, fund managers can use this figure as a benchmark to evaluate their fund's operating expenses against similar funds, thereby assessing their competitive position and striving to control this ratio effectively.
To optimize operating costs, managers should implement strategies such as negotiating with service providers to reduce management fees and utilizing advanced technology for process automation Additionally, selecting brokers with low transaction fees and employing effective investment strategies can minimize transaction expenses Fund managers must also focus on controlling marketing and sales costs by leveraging cost-effective marketing channels and streamlining sales processes for greater efficiency.
To improve investment efficiency, it's crucial to understand the negative correlation between asset turnover and fund profitability, where higher asset turnover often leads to diminished earnings This trend may arise from increased transaction costs, prompting fund managers to focus on short-term gains rather than sustainable, long-term profitability To address this challenge, fund managers should adopt strategic investing methods to identify high-yield opportunities while effectively managing risks Regular and thorough market analysis is vital for recognizing potential investments and making informed decisions Additionally, leveraging modern analytical tools can enhance investment strategies and optimize profits.
To enhance fund performance, managers should prioritize expanding fund scale, as research indicates a positive correlation between size and performance Larger funds benefit from superior positions and resources, enabling them to leverage market opportunities and optimize asset utilization Achieving stable and sustainable profits is essential for attracting investors, alongside providing transparent reporting and clear operational information to build trust Ultimately, offering a diverse range of expert customer services is vital to cater to the varied needs and investment goals of different investor groups.
To build a strong and reputable brand, a fund must focus on enhancing investor confidence, which can be influenced by the fund's age and perceived operational experience Fund managers should prioritize establishing a respectable brand by providing transparent information about investment efficiency, operating expenses, and associated risks, while maintaining consistent performance A successful communication strategy is essential for reaching the target market, utilizing channels such as newspapers, social media, and websites Additionally, engaging in community events can help foster relationships with stakeholders and increase brand awareness.
Understanding the characteristics of mutual funds is essential for investors to make informed decisions about selecting and investing in the right fund Here are some key tips for investors to consider.
Investors should consider several key factors before investing in mutual funds, including the fund's size, turnover ratio, and expense ratio The operating expense ratio is particularly crucial as it significantly impacts fund performance and, consequently, investor profits The average operating expense ratio for open-end mutual funds is 1.96%, serving as a benchmark for investment decisions If a fund's operating expense ratio remains stable and below this average, it may indicate a favorable condition that could enhance expected returns for investors.
When selecting a mutual fund for investment, it is advisable for investors to focus on those with low expense and turnover ratios, as studies show a negative correlation between mutual fund performance and asset turnover ratio A higher asset turnover ratio can negatively affect the fund's performance.
Before investing in a fund, potential investors should understand its asset turnover ratio, which is influenced by the fund's investment strategy Generally, it is advisable to select funds with an asset turnover ratio lower than the market average Additionally, comparing the fund's returns, risks, and operating costs with similar funds is essential for evaluating performance Investors must also consider their own investment objectives, determining whether they are pursuing long-term or short-term goals, and assess their risk tolerance to choose a mutual fund that aligns with their investment strategy.
Investors should prioritize diversifying their holdings by allocating funds across multiple mutual funds to mitigate risk It is crucial for them to regularly monitor fund performance and evaluate returns, rather than relying solely on fund managers By comparing a fund's performance with similar funds and the overall market, investors can determine its consistency in generating strong returns Additionally, assessing risk through the fund's net asset value (NAV) volatility is essential Key indicators for this evaluation include the expense ratio and turnover ratio, which provide valuable insights into fund management efficiency.
Limitations of the thesis and suggestions for future research
The research has notable limitations, primarily due to the modest sample size of just 10 mutual funds in the Vietnamese stock market, as many funds are newly established and lack sufficient data Additionally, the performance measurement of these stock investment funds relies solely on the growth of their net asset value (NAV) Future studies could enhance the findings by incorporating data from a broader range of funds and utilizing alternative performance metrics such as the Sharpe Ratio, Treynor Ratio, or Jensen’s alpha.
The study employs multi-factor models, including the Fama-French 3-factor model and the Carhart 4-factor model, to analyze the influence of fund factors on mutual fund performance Future research should consider both internal and external factors for a more holistic evaluation of mutual fund performance Furthermore, as this research is limited to the period from 2020 to 2023, expanding the time frame in future studies could yield more accurate insights.
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