Large Mutual Funds Research Articles

Mutual fund performance: the model for selecting persistent winners

Standard Fama-French-Carhart (FFC) models are widely used by academics to assess risk-adjusted fund performance versus market, size, style and momentum factors. However, they fail to reflect the industry standard, following which the performance of money managers is commonly evaluated relative to a corresponding benchmark and the peer group. In this paper, we introduce a new approach that augments the Carhart model and enables investors to identify the funds that outbid both the benchmark and the peer group. In addition, it allows discovering more certain winners by eliminating the under/outperformance of funds driven by the bias in the FFC factor construction. The application of our model is illustrated on Large Cap Value and Large Cap Growth US active equity mutual funds using contingency tables. The performance and persistence in performance are assessed by comparing our novel and the standard Carhart models. Our model identifies more winners than the Carhart; those winners earn higher returns net of benchmark and peer- group than the Carhart’s winners, and show persistence in performance 36 months ahead. The results are robust to different specifications of contingency tables, holding periods or style categories of funds.

Infectious disease outbreaks and the disposition effect of mutual fund investors

This study investigates the potential impact of the 2003 severe acute respiratory syndrome (SARS) epidemic on cognitive biases in capital markets, focusing on individual mutual fund investors’ trading behavior in the post-SARS era. Using a proprietary data set obtained from a large Chinese mutual fund family comprising comprehensive trading information, this research finds that individuals in areas experiencing severe SARS cases exhibit a stronger disposition effect after the end of the epidemic. It further indicates that unsophisticated investors are more vulnerable to the disposition effect and this mood regulation–induced behavior is irrational and related to behavioral biases, ultimately worsening investors’ circumstances. These results hold across a wide range of robustness checks.

Tradable Risk Factors for Institutional and Retail Investors

Abstract We construct tradable risk factors using combinations of large and liquid mutual funds (long leg) and ETFs (exchange-traded funds) (long and short legs), based on their holdings, for both retail and institutional investors. Exploiting a novel dataset, our tradable factors take into account ETF shorting costs. Assessing the performance of our tradable factors against standard “on-paper” factors, we uncover an implementation shortfall of 2–4 percent annually. Shorting fees and transaction costs contribute to 58 percent of the performance differential between tradable and “on-paper” factors, assigning a non-trivial role to the opportunity cost of not trading the exact “on-paper” portfolio.

A Research Perspective on Mutual Funds

This research explores mutual funds, which are investment pools where many people combine their money to buy a diversified portfolio of stocks, bonds, or other securities. The study investigates how mutual funds work, their benefits, and potential risks. By understanding these aspects, investors can make informed decisions about participating in mutual funds to achieve their financial goals. This research aims to provide a straightforward overview to help individuals navigate the world of mutual fund investments. However, a long-term investor has to consider other factors associated with such mutual funds (like asset under management, expenses ratio, number of stocks, and experience of the management) to finalise the selection of mutual funds. In this research paper, an attempt has been made to identify the relationship among the performance of selected equity mutual funds and the parameters considered by the investors for selecting the fund. 't-statistic’ has been used to identify such relationship. This research shows that there is no relationship between trailing return of any kinds of Equity mutual funds and the selected parameters by the investors. However, number of stocks and experience of management have a little impact on the rolling return of equity large cap mutual funds and Assets under management has a little impact on rolling return in case of mid-cap mutual fund only. Key Words: Investment Pools, Asset management companies, Mutual Funds, Trailing Return,

An Evaluation of Large Cap, Mid Cap, and Small Cap Mutual Funds: Return, Risk, and Investor Considerations

Investing in mutual funds presents a straightforward entry point into the stock market, particularly for novice investors. Regardless of one’s familiarity with stock markets or age, mutual funds offer accessible investment opportunities. However, selecting the most suitable mutual fund scheme can be challenging, given investors’ varying risk appetites and financial goals. This study aims to assist such investors grappling with scheme selection dilemmas by analysing mutual fund schemes of many types and determining which ones offer superior returns at lower risks. The research evaluates the risk and return profiles of various mutual fund schemes taken up for the study. Utilising various ratio like Jensen’s, Sharpe, and Treynor, present discussion compares the returns by considering the systematic and unsystematic risk of selected schemes within each category. The analysis spans 5 years, from April 01, 2017, to March 31, 2022, drawing data from secondary sources including Moneycontrol, journals, books, and official websites of relevant financial bodies. BNP Paribas Large Cap Fund (G) emerges as a top performer in the sphere of large cap funds according to Sharpe and Jensen’s measures, while Edelweiss Large Cap Fund-A(G) excels by Treynor ratio. Among mid cap schemes, Edelweiss Mid Cap Fund (G) consistently outperforms its peers across all evaluated ratios. In the small cap category, Axis Small Cap Fund-Regular (G) stands out for delivering the highest returns on the basis of Jensen’s, Sharpe and Treynor ratios. Ultimately, this study serves to guide investors 2024in navigating the complexities of mutual fund selection, offering insights into which funds align best with their risk-return preferences and investment objectives. Findings reveal distinct return patterns across fund categories, with specific funds outperforming peers based on various return metrics. The study concludes that while BNP Paribas Large Cap mutual Fund (G) excels in large cap schemes, Edelweiss Mid Cap mutual Fund (G) stands out among mid cap funds, and Axis Small Cap mutual Fund-Regular (G) leads in the small cap mutual funds category. Implications suggest that investors can make informed decisions based on risk-return preferences, with large cap funds offering stability, mid cap funds providing moderate returns, and small cap funds presenting opportunities for better growth with higher risk acceptance capacity.

Malmquist Productivity Change of Mutual Funds in Tanzania

This study utilized Data Envelopment Analysis to assess the efficiency of six mutual funds in Tanzania spanning from 2018 to 2022. The analysis explores efficiency changes, technical advancements, scale efficiency, and total factor productivity. The results revealed significant trends of Mutual funds, on average, demonstrate a 3 percent increase in total factor productivity, signifying enhanced output relative to inputs attributed to improved management practices, technology integration, and operational enhancements. Conversely, technical efficiency change experiences by 2.7 percent decline, indicating that certain funds struggle to optimize inputs, potentially due to shifts in management strategies, resource allocation, or market variations. Further differentiation between large and small mutual funds reveals that larger entities exhibit more favorable productivity changes. This disparity is ascribed to economies of scale, improved investment prospects, and reduced transaction costs for larger funds. The study underscores substantial implications for mutual fund managers and the industry. Positive improvements in efficiency change, scale efficiency change, and total factor productivity indicated an overall positive trend in the mutual fund industry. Emphasizing economies of scale can enhance efficiency and overall outcomes, urging regulatory bodies to provide guidance on achieving economies of scale and fostering better practices. This research offers valuable insights into the mutual fund landscape, emphasizing the critical importance of adapting to evolving market dynamics and incorporating technology to maximize efficiency and success.

Performance Evaluation of Selected Open-Ended Mutual Fund Schemes in India

Abstract: Mutual funds are considered as the best investment option because they offer a higher return with little risk. The study’s main aim is to evaluate the performance of selected large and small cap equity mutual fund schemes. The performance has been analysed in terms of return and risk using risk-adjusted performance measures. The present study is descriptive and secondary data has been collected from the website of BSE, NSE and Mutual funds. The analysis shows that “HDFC Top 100 Fund - Growth Option - Direct Plan” is top large cap mutual funds scheme and “Tata Small Cap Fund-Direct Plan-Growth” is top small cap mutual funds scheme among the selected funds as per Sharpe, Treynor and Jenson ratio.

A study on performance of selected large cap mutual funds in India

Mutual funds are introduced in the Indian financial system with a view to providing comparatively safer investments at the doorstep of common investors. This study has tried to understand the performance of selected large-cap mutual funds in India. For study purposes, five large cap mutual funds have been selected. The secondary data has been considered for the performance analysis, and it was achieved by using various tools and techniques like Average return, Standard deviation, Beta, Sharpe ratio, Jensen ratio, and Treynor ratio. The findings show that SBI Bluechip Fund, Canara Robeco Bluechip Fund, and Kotak Bluechip Fund outperformed the other funds. A mutual fund is a scheme in which several people invest their money for a common financial cause. The collected money is invested in the capital market, and the money earned is divided based on the number of units they hold. The mutual fund industry started in India in a small way with the UTI Act, which created what was effectively a small savings division within the RBI. Over a period of 25 years, this grew fairly successfully and gave investors a good return, and therefore, in 1989, as the next logical step, public sector banks and financial institutions were allowed to float mutual funds, and their success emboldened the government to allow the private sector to foray into this area. The advantages of mutual funds are professional management, diversification, economies of scale, simplicity, and liquidity.

A Study on the Performance of Mutual Funds of Indian AMCs

A mutual fund is a pool of money managed by an Asset Management Company (AMC) that collect funds from different individuals as well as institutional investors, and invest those funds in various securities, capital assets such as bonds, real estates, stocks as well as in mutual funds. Most of the Asset Management Companies have different categories of equity mutual funds depending upon the risk associated with such investments. In this case, trailing return and rolling return indicate the performance of a mutual fund. However, a long-term investor has to consider other factors associated with such mutual funds (like asset under management, expenses ratio, number of stocks, and experience of the management) to finalise the selection of mutual funds. 
 In this research paper, an attempt has been made to identify the relationship among the performance of selected equity mutual funds and the parameters considered by the investors for selecting the fund. 't-statistic’ has been used to identify such relationship.
 This research shows that there is no relationship between trailing return of any kinds of Equity mutual funds and the selected parameters by the investors. However, number of stocks and experience of management have a little impact on the rolling return of equity large cap mutual funds and Assets under management has a little impact on rolling return in case of mid-cap mutual fund only.

A STUDY ON CONSUMER PERCEPTION ABOUT GROWTH OF MUTUAL FUNDS

Mutual Funds were introduced in the Indian financial system with a view to provide comparatively safer investment at the doorstep of the common investors. In this study researcher has tried to understand the performance of selected large cap mutual funds in India. For the study purpose 15 large cap mutual funds has been selected. The Secondary data has been considered for the performance analysis and it was achieved by using various tools and techniques like average return, standard deviation, beta, Sharpe ratio, Jensen ratio and Trey nor ratio. The findings depict that DSP Top 100 Equity Fund, ICICI Prudential Blue chip Equity Fund and LIC MF Large cap Fund showed highest return among the selected funds.

A Nash bargaining solution for a multi period competitive portfolio optimization problem: Co-evolutionary approach

This study focuses on proposing a Nash bargaining model to solve a novel multi-period competitive portfolio optimization problem for large investors in the stock market who want to maximize their terminal wealth while taking into account competitors' profits. In this study, a Competitive Portfolio Model (CPM) is developed in accordance with the Cournot competition principle for a static, non-cooperative, and non-zero-sum game with complete information. Transaction costs, risk-free assets and cash are also included to match real-world conditions. Also, three criteria including the average value at risk, the mean absolute semi-deviation, and entropy are considered to control the investment risk in the model. Moreover, due to common constraints between players (free floating shares of risky assets) in stock markets, this study falls into the category of Generalized Nash Equilibrium Problems (GNEP). Therefore, to overcome the problem, a Cooperative Co-evolutionary Algorithm (CCA) based on Particle Swarm Optimization (PSO) is customized and used. A few experimental tests and a numerical example with descriptive analytics (using real data from two large mutual funds who invest in the Iranian Stock Exchange market) are used to evaluate the feasibility of the proposed model and the efficiency of the design algorithm. After solving the model, for each time period, investors' trading strategies (trading signals and stock volume in their portfolio) are determined. The results show that the volume of transactions due to the market power of an investor has a significant effect on the terminal wealth of competitors. Also, the results of sensitivity analysis show that profit-making is inversely related to the degree of risk aversion of investors.

Predictive Analysis of Mutual Fund Investment Using Sustainability Index Evidence from Indian Stock Market

This study is an attempt to predict the price movement between S & P BSE GREENEX and selected open ended equity mutual fund categories traded at stock exchanges in India. Daily data over the last 5 years were taken and the sample period is from January 1, 2016 to January 1, 2021. The authors use a set of econometric models such as dynamic lag vector auto regression stochastic process model, Cointegration, Granger causality test and Variance Decomposition to substantiate the existence of long run and short run association between the dependent and independent variables selected. The study shows clear evidences of cointegration between S & P BSE GREENEX and selected mutual fund categories, which is an indication of the existence of long run equilibrium relationship between the variables. The empirical investigation also proved the traces of bi-directional and uni-directional Granger- casual effect between the variables. The findings of the study show that S & P BSE GREENEX and large cap mutual fund categories have strong price movement relationship compared to mid-cap funds, which shows a marginal relationship and relatively very weak relationship with small cap funds.

MANAGERIAL ABILITIES AND FACTOR INVESTMENT STYLE PERFORMANCES OF MALAYSIAN MUTUAL FUND MANAGERS

Background and Purpose: Studies focusing on mutual fund managerial abilities and investment style strategies are still scarce in the literature. Thus, this study aims to provide new evidence and insights into the managerial abilities and investment style performances of Malaysian fund managers.
 
 Methodology: A total of 444 Malaysian equity mutual funds (EMFs) were evaluated using Carhart’s model incorporated with Treynor-Mazuy (T-M) and Henriksson-Merton (H-M) market timing models for the study period, from January 1995 to December 2017.
 
 Findings: Fund managers displayed superior stock selection skills with 32 percent and 43 percent of funds for T-M and H-M respectively, with perverse market timing ability which accounted for 39 percent and 42 percent of funds for T-M and H-M respectively. Perverse timing ability had reduced the superior stock-picking skills of fund managers. This suggests that the EMFs performance could further improve if respective fund managers perform better in market timing ability. The finding also indicates that size effect (SMB) and value effect (HML) play significant roles in investment style strategies, while results of momentum factor (WML) propose that Malaysian fund managers have followed the contrarian strategy.
 
 Contributions: This study contributes in several ways especially in the literature of portfolio management as the evidence is obtained from the largest mutual funds sample size and the longest study period. Moreover, this study also used the highest frequency data to study the effects of market timing which were overlooked in previous studies.
 
 Keywords: Adjusted carhart, Malaysian market, market timing, mutual fund, stock selection.
 
 Cite as: Ling, P-S., & Abdul-Rahim, R. (2021). Managerial abilities and factor investment style performances of Malaysian mutual funds. Journal of Nusantara Studies, 6(1), 118-135. http://dx.doi.org/10.24200/jonus.vol6iss1pp118-135

Rating a Robo-Rater

Since 2011, Morningstar has issued Morningstar Analyst Ratings on many of the largest mutual funds in the United States. In June 2017, Morningstar launched the Morningstar Quantitative Rating™ to provide a forward‐looking rating on all mutual funds. Morningstar uses a “robo‐rater” machine‐learning model to assign Morningstar Quantitative Ratings. However, the “robo‐rater” cannot utilize the complete set of information available to Morningstar's analyst as it cannot process “soft information.” The purpose of this study is to evaluate if and how this “robo‐rater” is conducive to mutual fund selection. I find no evidence that the “robo‐rater” offers value to investors beyond its assessment of mutual fund expenses and I find that its inability to process “soft information” makes the Morningstar Quantitative Rating™ much less useful than the Morningstar Analyst Rating™. I also examine the relationship between Morningstar Quantitative Rating™ and mutual fund flows and find that the “robo‐rater” has little to no influence on investors' choice of mutual funds. Paper is available through the Wiley Online Library at https://onlinelibrary.wiley.com/doi/full/10.1002/cfp2.1090

Diversification Within Large Cap Equity Mutual Funds in India

We ask whether a portfolio of large-cap mutual funds in India generates any diversification benefits as compared to holding a single large-cap index tracking exchange-traded fund. Using a mix of traditional measures like correlation and covariance of excess returns, and measures like tracking error, information ratio, and active share, we show that there are limited diversification benefits in a portfolio of two or more large-cap funds. A majority of the funds have similar risk return characteristics and negative information ratios versus a NIFTY100 tracking ETF. A cross-sectional analysis of active shares of the funds at the end of June 2020 shows that underlying holdings of funds are crowded together and funds do not have significant active share.

English

English

Investor ideology

We estimate institutional investor preferences from proxy voting records. The W-NOMINATE method maps investors onto a left-right dimension based on votes for fiscal year 2012. Public pension funds and other investors on the left support a more social and environment-friendly orientation of the firm and fewer executive compensation proposals. “Money-conscious” investors appear on the right. The proxy advisor ISS makes voting recommendations that place it center, to the left of most large mutual funds. A second dimension reflects a more traditional governance view, with management-disciplinarian investors, the proxy advisor Glass Lewis among them, pitted against more management-friendly ones.

ETF use among actively managed mutual fund portfolios

It is well known that actively managed mutual funds use exchange-traded funds (ETFs), although current research has yet to establish the benefits of these positions. Focusing on ETF type, we investigate whether or not ETFs impact portfolio management. Funds using benchmark ETFs see reductions in cash holdings, particularly during periods of large flows, and lower tracking error. In contrast, non-benchmark ETF positions improve the performance of large mutual funds investing in micro-cap stocks while also reducing portfolio risk. While studies caution against the extensive use of ETFs, we conclude that ETFs can provide tangible benefits for funds when considering the type of ETF used.

Air pollution, behavioral bias, and the disposition effect in China

Inspired by the recent health science findings that air pollution affects mental health and cognition, we examine whether air pollution can intensify the cognitive bias observed in the financial markets. Based on a proprietary data set obtained from a large Chinese mutual fund family consisting of complete trading information for more than 773,198 accounts in 247 cities, we find that air pollution significantly increases investors’ disposition effects. Analysis based on two plausible exogenous variations in air quality (the vast dissipation of air pollution caused by strong winds and the Huai River policy) supports a causal interpretation. Mood regulation provides a potential mechanism.

Vanguard Versus Fidelity: Multidimensional Comparison of the Index Funds and ETFs of the Two Largest Mutual Fund Families

This paper compares Vanguard and Fidelity on 21 comparable funds in five aspects: performance, tax-efficiency, cost, diversification, benchmark and tracking precision. The conclusions are as follows: first, for pre-tax return, the difference between Vanguard and Fidelity is small, but Vanguard is the clear winner in after-tax return; second, Vanguard is much more tax-efficient than Fidelity; third, for the cost, Fidelity has lower expense ratio than Vanguard in all sample funds, while Vanguard has lower turnover, and both Vanguard and Fidelity have their own short-term redemption fee policy; fourth, Vanguard funds are more diversified which should reduce uncompensated risk; fifth, Fidelity funds have higher tracking precision to their benchmarks than Vanguard funds, but the difference is very small.