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Mutual Fund Performance: An Analysis of Quarterly Portfolio Holdings
Abstract
This article employs the 1975-84 quarterly holdings of a sample of mutual funds to construct an estimate of their gross returns. This sample, which is not subject to survivorship bias, is used in conjunction with a sample that contains the actual (net) returns of the mutual funds. In addition to allowing the authors to estimate the bias in measured performance that is due to the survival requirement and to estimate total transaction costs, the sample is used to test for the existence of abnormal performance. The tests indicate that the risk-adjusted gross returns of some funds were significantly positive. Copyright 1989 by the University of Chicago.
... Market timing can be measured using either a holdingsbased or return-based method. The former method measures whether fund managers increase returns during a rising market (minimize loss during a market downturn) by allocating money among different assets (Grinblatt and Titman 1989;Graham and Harvey 1996;Daniel et al. 1997;Wermers 2000;Jiang et al. 2007). By comparing mutual fund portfolio composition with observed returns at the same frequency, we can examine whether portfolio holdings anticipate moves in the market and infer the fund's market timing ability. ...
... In addition, the TM and HM tests fail to distinguish abnormal performance attributed to market timing from performance due to security selection skills (Admati et al. 1986;Grinblatt and Titman 1989) since selectivity skills and market timing are negatively correlated (Jagannathan and Korajczyk 1986;Coggin et al. 1993;Goetzmann et al. 2000;Jiang 2003). Jagannathan and Korajczyk (1986) suggest that such an artificial negative correlation might be attributed to nonlinear payoff structures in options and option-like securities in fund portfolios. ...
... Here, the beta reflects both the precision of the forecast and the aggressiveness of the manager's response to informed information. Grinblatt and Titman (1989) suggest that fund managers with independent timing and selectivity information and nonincreasing absolute risk aversion would increase the market exposure, t , when the market return is favorable, that ...
We apply the nonparametric methodology of Jiang (Journal of Empirical Finance 10:399–425, 2003) to examine whether bond mutual funds can time the bond market by adjusting their portfolios' market exposure based on anticipated market movement. This approach offers several advantages over the widely used regression-based tests such as Treynor and Mazuy (Harvard Business Review 44(4):131–136, 1966) and Henriksson and Merton (The Journal of Business 54(4):513–533, 1981). In a comprehensive study covering the USA, UK, and China, we find some evidence of positive market timing of bond funds at the individual fund level. On average, bond funds show neutral to slightly negative market timing abilities. After controlling for public information, we find that a smaller number of bond funds successfully time the market based on private timing signals. In terms of categories, we find strong evidence of positive market timing for Government bond funds as a group, consistent with the findings of Huang and Wang (Management Science 60:2091–2109, 2014).
... From this perspective, starting with the work of Jensen (1968), there has been a large literature on the performance and persistence of equity funds in the US market. Most studies report poor performance of equity funds (Grinblatt and Titman, 1989;Wermers, 2000;Kacperczyk et al., 2005;French, 2008;Cremers and Petajisto, 2009). Similarly, studies in the Korean market generally report underperformance of equity funds (Yoo and Kim, 2012;Kim et al., 2020). ...
... Most of these studies report that active funds occasionally outperform their benchmarks before fees and expenses, but they fail to do so after deducting these costs. For instance, Grinblatt and Titman (1989) examine quarterly holdings of active funds from 1975 to 1984 and identify significant risk-adjusted returns for growth funds. However, these returns lose their significance after fees and expenses are accounted for. ...
This study investigates the performance distribution of passive funds in the Korean market and compares it with the performance distribution of active funds. The key findings are as follows, first, the performance distribution of passive funds has a thicker tail compared to that of active funds. There are passive funds that achieve outstanding performance, and both the false discovery rate (FDR) analysis and simulation analysis suggest that their outperformance is driven by managerial skill rather than luck. Second, passive fund performance is more persistent compared to active fund performance. Third, investors are less responsive to passive fund performance compared to active fund performance. The fund flow-performance relationship is significantly positive for active funds but not for passive funds. This implies that investors may not recognize the managerial skills of passive funds.
... Rehan (2020) defined the portfolio turnover as a financial ratio that shows the organization's efficiency in terms of how much income or revenue it generates by using its assets. The portfolio turnover firstly was introduced by Grinblatt & Titman (1989) and Droms & Walker (1996) to assess the equity fund performance. These were the first large-scale studies to look at the multivariate connection between investment performance and portfolio turnover. ...
... The high portfolio turnover indicates that investment managers accurately forecast market developments such as different current concerns, and equity funds with high turnover result in improved performance. However, equity funds with low turnover perform adversely (Grinblatt & Titman, 1989). ...
One of the issues that have an impact on the growth of Islamic Equity Funds is financial risk tolerance. While it is a fundamental issue that is directly related to Islamic Equity Fund’s manager performance. If investment managers perform better to cultivate Islamic Equity Funds, then the intention in investing within Islamic Equity Funds will be increased. This research aims to determine and provide information about Islamic Equity Funds' performance in Indonesia. It used quantitative statistical analysis to investigate the influence of stock selection skills, market timing ability, fund size, fund age, expense ratio, and portfolio turnover towards the Islamic Equity Funds performance. This study used annual data over the periods 2015-2020 which was obtained from the prospectus of each Islamic Equity Fund, Central Bank Indonesia (BI), and Statistics Indonesia (BPS). The result indicates that stock selection skill and expense ratio have a positive significant impact on the performance of Islamic Equity Funds, while market timing ability, fund age, and fund size have not a significant impact but the result revealed positive values. Otherwise, the portfolio turnover has a negative significant impact on Islamic Equity Funds' performance. Hence, it can be inferred that the higher investment managers ability to select its portfolio stock, the better return will be obtained and it can be inferred that the expense ratio of an equity fund reflects how much it pays for portfolio management, administration, marketing, and distribution, among other things. Originality/Value: This paper focuses on the issue that occur in Islamic equity funds which are very essential as an investment portfolio, and only a few papers have conducted research in this area. Therefore, knowing the key factors that influence the performance of Islamic equity funds can optimize their function and attract investors.
... This result is under the studies of Barberis and Thaler (2003), who stressed that investor preferences and aims significantly affect the form of investment outcomes. This is also supported by the conclusions of Fama and French (2007) and Grinblatt and Titman (1989), who also stressed the role investor objectives play in determining returns. Standardized estimates of 0.379 (t = 9.558, p =.001) and 0.321 (t = 8.195, p =.001) respectively demonstrated that Investment Structure (SI) and Investment Horizon (IH) both influenced IR. ...
Purpose- The objective of this study is to identify the factors that influence investors' perceptions and investment decisions by examining investment objectives (IO), Investment Returns (IR), investment structure (IS), and Investment Horizon (IH) on Investment Decisions (ID) for mutual fund investments in Nepal. This study seeks to provide valuable insights for fund managers, investors, and policymakers in the Nepalese mutual fund market. Design/Methodology/Approach- Data from 386 Nepalese mutual fund investors was collected quantitatively using a structured questionnaire. Analytical statistical approaches were utilized in structural equation modeling using AMOS. Path and mediation studies explored investment goals, returns, structure, horizon, and choices. Validity and reliability tests like Cronbach's Alpha protected constructs. The model fit was evaluated using RMSEA, CFI, CMIN/DF and SRMR. Findings- Results reveal that all four independent factors significantly influence investing choices and investment return is a major mediator. The largest direct influences on returns were those of investing goals and investment horizon, which then shaped choices. Strong internal consistency and dependability let the model show an excellent fit. Implications- Using these realizations, fund managers may create mutual funds that complement investor objectives, hence improving fund attractiveness and performance. Policymakers may regulate mutual funds to promote transparency and good judgment. Originality/Value- This research addresses Nepal's growing mutual fund market and meets a need for data on investing factors. A detailed strategy and robust methodology give informative research on developing financial market investment behavior. Int. J. Soc. Sc. Manage. Vol. 12, Issue-2: 89-98.
... Machine learning (ML) in finance, including studies on forecasting open-end fund performance using ML tools, is an emerging field. Most existing research on investment funds focuses on the persistence of performance among winning and losing funds, often influenced by various market factors or fund attributes (Brown & Goetzmann, 1995;Carhart, 1997;Cremers & Petajisto, 2009;Elton et al., 1996;Glode, 2011;Grinblatt & Titman, 1989;Hendricks et al., 1993;Kacperczyk et al., 2014;Kosowski, 2011 and lately (Cuthbertson et al., 2022;Dumitrescu & Gil-Bazo, 2018). These studies provide mixed evidence on fund performance persistence and rely on multiple linear regression models to assess the fund managers' skills. ...
The primary motivation of this study is to empower individual investors with a data-driven strategy for finding long-term investment returns by leveraging recurrent neural networks (RNNs) to forecast fund performance and construct dynamic portfolios. Specifically, we use RNN to forecast the returns of open-end investment funds and build a portfolio of top-performing funds based on these forecasts. Using a sample of 71 equity, fixed income, hybrid and money market funds in the Polish market from 2005 to 2022, we train the network over five years to generate annual logarithmic return forecasts for each fund. These forecasts underpin a straightforward long-term investment strategy: at the end of each forecasted year, funds with positive returns are added to the portfolio. In subsequent years, the portfolio is adjusted by retaining or adding high-performing funds and removing underperforming ones. Our findings reveal that this strategy delivers higher returns than passive investing or traditional regression-based models, making it a viable long-term option for individual investors aiming to secure their retirement. By showcasing its superiority over conventional methods, the study offers a practical and adaptable solution for achieving financial security in dynamic market environments.
... Grinblatt and Titman (1994) show that the choice of benchmarks matters much more for performance inferences than the choice of measures. On the other hand, if fund holding data are available, holdings-based measures (e.g., Grinblatt and Titman, 1989;Daniel, Grinblatt, Titman, and Wermers, 1997) are more robust to benchmark error. This paper does not consider holdings-based measures. ...
Alpha-based performance evaluation may fail to capture correlated residuals due to model errors. This paper proposes using the Generalized Information Ratio (GIR) to measure performance under misspecified benchmarks. Motivated by the theoretical link between abnormal returns and residual covariance matrix, GIR is derived as alphas scaled by the inverse square root of residual covariance matrix. GIR nests alphas and Information Ratio as special cases, depending on the amount of information used in the residual covariance matrix. We show that GIR is robust to various degrees of model misspecification and produces stable out-of-sample returns. Incorporating residual correlations leads to substantial gains that alleviate model error concerns of active management.
... This theory stipulates that stocks with smaller market capitalization tend to ourperform larger stocks, and by construction, naive diversification gives more exposure to smaller cap stocks compared to capitalization weighting. Empirical support for the superior performance of equal weighted portfolios relative to capitalization weighting include Lessard (1976), Roll (1981), Ohlson and Rosenberg (1982), Breen, Glosten, and Jagannathan (1989), Grinblatt and Titman (1989), Korajczyk andSadka (2004), Hamza, Kortas, L'Her, andRoberge (2007) and Pae andSabbaghi (2010). Furthermore, DeMiguel, Garlappi, andUppal (2007) show the strong performance relative to optimized portfolios. ...
A widely applied diversification paradigm is the naive diversification choice heuristic. It stipulates that an economic agent allocates equal decision weights to given choice alternatives independent of their individual characteristics. This article provides mathematically and economically sound choice theoretic foundations for the naive approach to diversification. We axiomatize naive diversification by defining it as a preference for equality over inequality and derive its relationship to the classical diversification paradigm. In particular, we show that (i) the notion of permutation invariance lies at the core of naive diversification and that an economic agent is a naive diversifier if and only if his preferences are convex and permutation invariant; (ii) Schur-concave utility functions capture the idea of being inequality averse on top of being risk averse; and (iii) the transformations, which rebalance unequal decision weights to equality, are characterized in terms of their implied turnover.
... Assets Under Management (AUM) for Mutual Funds represent the total value of assets, including stocks, bonds, and other investments, managed by a mutual fund on behalf of its investors (Titman, 1989). ...
This research paper aims to present an extensive analysis of Large-cap class-A mutual funds spanning a period of 25 years. Using this historical data, the study presents the readers with the observed patterns and trends in these mutual funds. The data has been sourced from two major data repositories for mutual fund and finance data-WRDS (Wharton Research Data Services) and YF (Yahoo Finance). The study involves the use of statistical methodologies like Sharpe Ratio and Volatility; and analytical methodologies like CUSUM and Clustering. Along with this quantitative analysis, the paper also encompasses qualitative data like Assets Under Management, Turnover Ratio and Management Information for all the funds used. This helps gain insights into the influence of these factors on the performance of the mutual funds. This paper mainly discusses how all the aforementioned factors influence the mutual fund trajectories with the help of effective visualizations and machine learning-based analysis over a span of 25 years, hence developing an efficient pipeline.
... Meanwhile, risk-based explanations, initially explored by Levy (1967) and later questioned by Jensen and Bennington (1970), led to a broader investigation into the risk factors associated with momentum, challenging traditional models like the CAPM (Capital Asset Pricing Model). Grinblatt and Titman (1989) observed behavioral biases favoring relative strength, setting the stage for Jegadeesh and Titman's seminal work in 1993, which documented significant momentum profits and challenged traditional risk models. Subsequent research by Rouwenhorst (1998), Moskowitz and Grinblatt (1999), and Grundy and Martin (2001) further reinforced the robustness of momentum effects across different markets and sectors. ...
Background: This study provides a bibliometric analysis of momentum investment strategies, examining their historical evolution, behavioral dynamics, and the challenges faced by professionals in equity markets. It aims to explore the persistent profitability of momentum strategies amidst market fluctuations and the significant influence of behavioral biases on trading decisions.
Methods: Employing a Bibliometric Analytical framework, the study systematically maps the knowledge structure of momentum investment strategies. It utilizes the Dimensions database for scholarly journal searches and examines peer-reviewed research publications spanning from 1993 to 2024. This method enables the identification of key research works, emerging trends, and an assessment of the literature's impact.
Results: The research reveals the persistent profitability of momentum strategies despite market changes, highlighting the significant role of behavioral biases in trading decisions. This work contributes to both academic discourse and practical investment strategy development, offering insights into exploiting momentum's transformative potential in dynamic equity markets.
Conclusion: This study contributes to both academic discourse and practical investment strategy development by offering evidence-based insights into the effectiveness of momentum
... Meanwhile, risk-based explanations, initially explored by Levy (1967) and later questioned by Jensen and Bennington (1970), led to a broader investigation into the risk factors associated with momentum, challenging traditional models like the CAPM (Capital Asset Pricing Model). Grinblatt and Titman (1989) observed behavioral biases favoring relative strength, setting the stage for Jegadeesh and Titman's seminal work in 1993, which documented significant momentum profits and challenged traditional risk models. Subsequent research by Rouwenhorst (1998), Moskowitz and Grinblatt (1999), and Grundy and Martin (2001) further reinforced the robustness of momentum effects across different markets and sectors. ...
Background: This study provides a bibliometric analysis of momentum investment strategies, examining their historical evolution, behavioral dynamics, and the challenges faced by professionals in equity markets. It aims to explore the persistent profitability of momentum strategies amidst market fluctuations and the significant influence of behavioral biases on trading decisions.
Methods: Employing a Bibliometric Analytical framework, the study systematically maps the knowledge structure of momentum investment strategies. It utilizes the Dimensions database for scholarly journal searches and examines peer-reviewed research publications spanning from 1993 to 2024. This method enables the identification of key research works, emerging trends, and an assessment of the literature's impact.
Results: The research reveals the persistent profitability of momentum strategies despite market changes, highlighting the significant role of behavioral biases in trading decisions. This work contributes to both academic discourse and practical investment strategy development, offering insights into exploiting momentum's transformative potential in dynamic equity markets.
Conclusion: This study contributes to both academic discourse and practical investment strategy development by offering evidence-based insights into the effectiveness of momentum
... The study indicated that the funds' market risk exposures changed in response to market indications, but the fund managers failed to time the market correctly. Grinblatt and Titman (1989) reported that certain mutual funds consistently achieved abnormal returns by selecting assets that provided positive excess returns. Richard A. Ippolito (1989) found that, overall, mutual funds offer better returns. ...
According to the present findings, the majority of individuals are afraid to invest in newer types of investments like mutual funds and instead choose to mitigate risk by choosing less risky investment options like recurring deposits and similar products. Additionally, those who invest in mutual funds choose high-risk portfolios and schemes while simultaneously wanting to use components with a moderate level of risk. Another observation is that the majority of working women do not favour these kinds of investments. The study's primary goal is to determine how investors see mutual funds. High returns, security, tax exemption, flexibility, liquidity, risk diversification, market trend, choice of plan, dependability, and affordability are the primary factors influencing investment behaviour. Mutual funds invest in a range of financial instruments, including stocks, bonds, and shares, by pooling funds from different participants. These are managed by a qualified fund manager, and dividends are used to pay returns. Some plans promised fixed returns with no risk, while others offered payouts based on price and market changes. The acquisition or sale of mutual funds must be made in units and is based on NAV (Net Asset Value), taking exit and entry load factors into consideration. This study looked at how customers perceived mutual funds, including the plans they preferred, the schemes they chose, and the justifications for those decisions. It also looked at various investment options that consumers preferred alongside and in addition to mutual funds. Comparable to bank savings plans, recurring deposits, bonds, and stocks. During COVID-19 very minor effect on the mutual funds which are very important sources for the general peoples.
... When the transaction costs were taken into consideration, equal-weight portfolios did not outperform the optimized portfolios with a weekly rebalancing scheme. However, with a quarterly rebalancing scheme, the equalweight portfolio outperforms the optimized portfolio (Grinblatt & Titman, 1989). According to Statman (1987), when the number of randomly chosen equities in the portfolio is between 30 -40 the equal-weight strategy has been shown to reduce the risk of the portfolio. ...
Purpose: Portfolio optimization is a process in which the capital is allocated among the portfolio assets such that the return is maximized while the risk is minimized. Portfolio construction and optimization has long been an active research area in finance. For the portfolios with highly correlated assets, the performance of traditional risk-based asset allocation methods such as, the mean-variance (MV) method is limited because quadratic optimizers require an inversion of the covariance matrix of the portfolio to distribute weight among the portfolio assets. Methods: A possible solution to the limitations of traditional risk-based asset allocation methods can be provided by a hierarchical clustering-based Machine Learning method because it uses hierarchical relationships between the covariance of assets in the portfolio to distribute the weight, and inversion of the covariance matrix is not required. A comparison of the performance of a simple non-optimization technique called the Equal-weight (EW) method to the two optimization methods, the Mean-variance method and the HRP method, which is a machine learning method, was conducted in this research. Results: It was found that in terms of cumulative returns, the equal-weight method has outperformed several more sophisticated optimization techniques, the mean-variance method, and the HRP method. For most of the period, the Sharpe ratio of the HRP method was observed to be similar to the mean-variance method and equal-weight method. Implications: This research supports the idea that HRP is a feasible method to construct portfolios with correlated assets because the performance of HRP is comparable to the performances of the traditional optimization method and the non-optimization method.
... Third, we heed the growing number of calls to start differentiating between long-term and short-term institutional investors (e.g., Connelly et al., 2010), thereby further shedding light on the profile of institutional investors that are attracted to invest in ethical companies. Studies have reported heterogeneous investment preferences among institutional investors (e.g., Gillan & Starks, 2007;Goyer & Jung, 2011) suggesting that what attracts institutional investors is still open to debate (e.g., Aguilera et al., 2016;Gibson et al., 2004;Grinblatt & Titman, 1989). Fourth, this study offers managerial contributions by showing that public companies need to effectively-rather than ceremonially-adopt sound governance structures, invest in socially responsible activities, and commit to ethical business practices because they can increase their likelihood of being included on ethics indices, therefore allowing them to send positive and credible signals about their ethical compass and granting them access to valuable institutional investments. ...
Our research investigates how the inclusion of a company on an independent ethics index affects its attractiveness to institutional investors. Using a sample of 864 U.S. firms over the 2010–2018 period, we find that institutional investors significantly increase their holdings in companies in the quarter that they are included on the ethics index and maintain larger holdings in the four quarters following the inclusion on the Ethisphere list relative to pre‐inclusion period, with dedicated institutional investors being more swayed to invest than transient investors. This paper adds to the emerging literature on intermediate signaling by showing that a firm's inclusion on an ethics index reduces information asymmetry with institutional investors. Our evidence suggests that public companies should effectively, rather than ceremonially, adopt sound governance structures and invest in socially responsible activities, as these actions can increase their likelihood of being included on ethics indices. By doing so, these firms send credible signals about their ethical compass, granting them access to valuable institutional investments.
... Chen et al. (2004) reinforce the inverse relationship between fund size and returns for various performance benchmarks and attribute the adverse scale effects to lack of liquidity and organizational diseconomies. In contrast, Grinblatt and Titman (1989) find mixed evidence that fund returns decline with fund size. Otten and Bams (2002) also report a positive relationship between size and fund abnormal performance for European mutual funds. ...
We examine the performance and market timing ability of actively managed Chinese stock mutual funds and investigate how fund characteristics and fund flows relate to performance and market timing ability. Based on daily return data and several four-factor models, only about 7.5% of these funds have statistically significant risk-adjusted abnormal returns and even fewer demonstrate market timing ability. After controlling for fund size, management fees, average amount, and volatility of fund flows, older funds show higher Sharpe ratios. Our evidence also reveals the volatility of fund flows has an inverted-U shape relationship with fund performance.
The Indian mutual fund industry has witnessed substantial growth, especially following the 2017 "Mutual Funds Sahi Hai" campaign by the Association of Mutual Funds in India (AMFI). Investors often rely on past Net Asset Value (NAV), fund categories, prominent fund managers, and rankings to make investment decisions. However, rankings alone may not rigorously determine a fund’s future performance. This study explores the correlation between mutual fund rankings and their actual performance, emphasizing macro and micro forecasting techniques employed by fund managers. The research utilizes the Treynor-Mazuy (1966) and Henriksson-Merton (1981) models to evaluate market timing and stock selection abilities of Indian mutual fund managers. Additionally, tracking error and the information ratio are analyzed to assess fund performance consistency. Findings indicate that while mutual funds in India consistently generate excess returns relative to benchmarks, fund managers exhibit weak market timing abilities but strong stock selection skills. Moreover, CMFR rankings do not necessarily correlate with higher returns, as funds with lower rankings often outperform those ranked higher. This study highlights the need for a multi-metric evaluation approach for investment decisions, incorporating models like Treynor-Mazuy and Henriksson-Merton. It underscores that mutual fund rankings alone are not sufficient indicators of superior performance and that investors should consider additional performance metrics to make informed investment choices.
Since the COVID-19 outbreak, asset management companies (AMCs) have taken the lead in increasing wealth through mutual funds. There are two types of mutual funds: open-ended and closed-ended. With 43 AMCs operating in India and an average asset under management (AUM) of ₹27.12 trillion as of July 31, 2020, equity funds are riskier. According to research, small and midcap funds have more risk and higher returns than large-cap funds, which have lower risk and lower returns. For regular investments in mutual funds, especially midcap funds, Systematic Investment Plans (SIPs) have gained popularity. Based on their assets under management (AUM) and monthly SIP inflows from 2020–21 to 2024–25, the top ten midcap funds were examined in this study. The purpose of this study is to show how the performance of the midcap funds and volatility associated with the funds. This study also analyses the volatility of the midcap funds by using Sharpe index, Treynor index, and Jensen's Alpha index. The result shows that few of the midcap funds are more volatile than the other funds but higher volatility generates higher returns for the investors over this last four years.
We demonstrate that a broad set of asset pricing factors/anomalies are significantly exposed to “noise trader risk,” and the noise trader risk is priced in factor premia. We first confirm that mutual funds’ flow-induced trading of factors are uninformed, as they generate a large price impact on factor returns, followed by a complete reversal. We then show that asset pricing factors are subject to flow-driven noise trader risk in that expected variation (covariation) of flow-induced noise trading strongly forecasts variance (covariance) of factor returns. Importantly, factor premia are higher when flow-driven noise trader risk is expected to be more salient.
This paper was accepted by Kay Giesecke, finance.
Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01827 .
Leveraging the systematic variations in investor clientele within a day, we validate an adapted version of the Hong and Stein (1999) model that addresses the consequences of slow information diffusion in China. The model predicts that overnight returns, rather than total returns, strongly forecast future returns, as informed overnight clientele underreact to value-relevant signals. Empirically, we establish a consistent overnight trend phenomenon: Firms with a strong overnight trend reliably outperform those with a weak overnight trend in the subsequent month. The phenomenon is more pronounced among stocks with higher levels of information asymmetry, valuation uncertainty, and relative mispricing. Furthermore, the overnight trend predicts positively firm fundamentals in the cross section.
Artykuł koncentruje się na dokonaniu wstępnej oceny efektów gospodarowania funduszy inwestycyjnych działających w Polsce w latach 2000–2015. Wykorzystując dużą próbę badawczą, składającą się z 221 krajowych funduszy, dokonano analizy wyników osiąganych w trzech segmentach: akcji, mieszanych oraz obligacji. Przy użyciu zarówno tradycyjnych miar wyników, jak i popularnych miar ryzyka możliwe było ustalenie, czy polskie fundusze posiadają zdolność osiągania ponadprzeciętnych rezultatów. W wyniku przeprowadzonej analizy zaobserwowano, że fundusze uzyskiwały generalnie gorsze średnie stopy zwrotu niż wzorzec odniesienia. Jednak ostatecznie rezultaty w większości przypadków nie były statystycznie istotne. Zwiększenie poziomu ryzyka funduszy odpowiada- ło zwiększeniu zaangażowania inwestycji w papiery właścicielskie.
Mutual funds represent one of the fastest growing type of financial intermediary in the American economy. The question remains as to why mutual funds and in particular actively managed mutual funds have grown so fast, when their performance on average has been inferior to that of index funds. One possible explanation of why investors buy actively managed open end funds lies in the fact that they are bought and sold at net asset value, and thus management ability may not be priced. If management ability exists and it is not included in the price of open end funds, then performance should be predictable. If performance is predictable and at least some investors are aware of this, then cash flows into and out of funds should be predictable by the very same metrics that predict performance. Finally, if predictors exist and at least some investors act on these predictors in investing in mutual funds, the return on new cash flows should be better than the average return for all investors in these funds. This article presents empirical evidence on all of these issues and shows that investors in actively managed mutual funds may have been more rational than we have assumed.
We analyze the performance of asset allocation funds using a best-fit multifactor model that includes both stock and bond market factors. Utilizing large samples of allocation funds from both the US and the UK, we find that, on average, asset allocation funds do not outperform their benchmarks, and there is little or weak evidence of performance persistence when examining both decile portfolios and small-size portfolios. However, asset allocation funds still demonstrate superior abilities. At the individual fund level, some funds exhibit significant positive alphas, stock market timing, and bond market timing in both the US and UK markets. Furthermore, we find that US allocation funds with low past maximum drawdowns (MDDs) outperform those with high past MDDs during periods of high stock market returns and high stock market volatility. In contrast, UK allocation funds with low past MDDs outperform those with high MDDs when bond market returns are high.
Purpose
The main objective of the paper is to find evidence of abnormal returns and performance persistence of actively managed equity funds in the Indian context on an annual basis during the post-subprime crisis period between 2009 and 10 and 2019 and 2020.
Design/methodology/approach
The study is exploratory and empirical, used daily net asset value (NAV) of 180 equity funds for 10 years and applied the risk-adjusted, Jensen's (1968) single-factor, Fama and French's (1993) three-factor model and Carhart's (1997) four-factor model to evaluate the performance. The performance persistence has been tested using cross-section regression (Bollen and Busse, 2005), the non-parametric contingency approach, along with the robustness measure, i.e. Malkiel's (1995) Z -score, Brown and Goetzmann's (1995) cross-product ratio (CPR) and Kahn and Rudd's (1995) χ ² value.
Findings
The results show that the Indian equity funds are unable to generate abnormal returns, and the size, value and momentum strategies applied by the fund managers in generating abnormal returns do not work effectively. However, funds provide strong evidence of significant performance persistence on an annual basis in the short-term, mid-term and long-term periods. Both parametric as well as non-parametric tests provide identical evidence of persistence, and the performance persistence is independent of the choice of models, as all the models (i.e. two, three or four-factor models) provide significant evidence of persistence.
Research limitations/implications
Though the study is comprehensive and covered a longer period, there is a scope for future research by examining the influence of fund characteristics, fund rating and macroeconomic factors on performance and persistence. It can be extended over to a longer period covering the post-COVID-19 period, a larger sample size and a comparative study of Indian and foreign mutual funds (MFs).
Practical implications
The outcomes of this research paper can help wealth-maximizing investors in the identification of persistent equity funds and can apply the previous period’s performance information as a useful investment strategy to generate higher returns in the future. We believe that these outcomes will have significant ramifications for all MF stakeholders and policymakers, especially for the Indian industry in ensuring and establishing the credibility of MF managers, in providing better returns as well as to make MF investment more attractive to Indian retail investors.
Originality/value
Despite the exponential growth in the Indian MF industry, limited evidence is available on performance and persistence covering a large sample size during the post-sub-prime crisis period using different return models and parametric and non-parametric approaches. The study is based on the daily data set of a larger sample size representing all the Asset Management Company (AMC) and the longer period following the post-subprime crises, which affected capital flows significantly. Moreover, the application of all the measures enables us to understand performance persistence in a larger context.
Assuming that the return characteristics of funds are known, i.e. for the time being putting aside the problem of estimation error, what is the best way to rank funds? The main alternative criteria are reviewed. We argue that the Sharpe ratio provides the ranking that is most closely aligned with investors’ preferences.
Purpose
In the present study, we investigate whether enhanced momentum strategies outperform price momentum strategies and if they show greater resilience and stability under adverse market conditions. We also examine if such strategies are explained by prominent asset pricing models or are a result of behavioral mispricing.
Design/methodology/approach
Data consist of the equity shares of all companies listed on National Stock Exchange over the study period. To check the efficacy of enhanced momentum over price momentum, six momentum strategies have been designed and their raw as well as risk-adjusted returns using multi-factor models have been observed. Behavioral mispricing has been examined by constructing an investor attention index. Finally, few robustness tests have been performed to confirm the results.
Findings
We find that an enhanced momentum strategy which combines relative and absolute strength momentum outperforms conventional price momentum strategy in India. We also demonstrate that rational pricing models are not able to explain momentum profits for any of the strategies. Finally, we observe that investor overreaction is the possible explanation of momentum profits in India. Thus, our results confirm the role of behavioral mispricing in explaining momentum returns.
Originality/value
Our research is the first major attempt to study enhanced momentum strategies in the Indian context. We experiment with several new enhanced momentum strategies which have not been explored in prior literature. The findings have strong implications for global portfolio managers who wish to design profitable trading strategies.
Investors nowadays have a vast array of investment opportunities due to the highly competitive market landscape. Amid the volatile financial environment, mutual funds stand out as a professionally managed, safe, and less risky investment option, making them an attractive and widely chosen investment globally. However, in India, mutual funds are relatively new, with limited research and awareness among investors. Mutual funds enable investors to pool their resources to purchase a diverse portfolio of securities. The success of mutual funds depends significantly on the expertise of fund managers and the vigilance of investors. Effective fund managers must analyse investor behavior and understand their needs and expectations to enhance performance and meet investor demands. Hence, it is crucial to identify mutual fund investors' needs, their scheme preferences, and performance evaluations in the current scenario.
The present research seeks to explore the relationship between demographic factors and the investment awareness levels of retail investors. It also aims to study the various factors influencing retail investors' behavior towards mutual funds. This study is based on primary data collected from 385 respondents through a structured questionnaire. Exploratory Factor Analysis was employed to identify the factors influencing retail investors' behavior regarding mutual fund investments. The findings indicate that gender significantly impacts investment patterns, with women generally showing higher awareness than transgender individuals, followed by men, about various investment instruments and tools. Additionally, demographic factors like age and education level significantly increase investors' awareness of investment options. Factors such as transparency, company reputation, and risk management strategy also shape investor perceptions.
This study is highly valuable for Asset Management Companies (AMCs), brokers, distributors, and potential investors, as well as for academic purposes. It offers essential insights for mutual fund organizations, helping them understand investor perceptions more deeply. Moreover, the research identifies seven key factors influencing retail investors' investment behavior in mutual funds.
Keywords: Investment, Investment Behavior, Mutual Funds, Behavioral Finance
We argue that institutional brokerage networks facilitate liquidity provision and mitigate the price impact of large non-information-motivated trades. Using commissions, we map trading networks of mutual funds (institutions) and their brokers. Central funds (institutions) tend to outperform their peripheral counterparts in terms of return gap (execution shortfall). This outperformance is more pronounced when funds experience large outflows and for large trades in less liquid stocks. Central brokers can deliver superior trade execution compared to peripheral brokers, but mainly for central institutions. We use the collapse of Lehman Brothers as a quasi-natural experiment to establish the likely causality of our findings. (JEL G14, G23, G24)
Examining risk‐adjusted returns for executed trades over horizons of up to 1 year, we document strong evidence of short‐term trading skill using daily mutual fund transactions from Finland. We find that trading performance is highly persistent up to the 1 month horizon, with an annualized Carhart abnormal return of 5.03% observed for both buys and sells. Moreover, the returns observed for the first week account for almost 36% of a fund's 1 year trade return, underscoring the significance of short‐term trading in mutual funds. For the best‐performing funds, this short‐term performance also translates into sustained long‐term outperformance. Investigating possible sources, we find that liquidity provision, rather than price pressure, is a significant contributor. In addition, short‐term trading performance is significantly positively related to trade size, fund size, and expenses, depending on whether buys or sells are considered.
The present study analysis the association between composition of fund portfolio and fund returns. Fund portfolio is a collection of financial investments and fund return is a return offered by the investment. The study aims to understand the composition of selected mutual fund portfolios and return of selected mutual fund portfolios.
This study examines whether mandatory increase in reporting frequency exacerbates agency problems. Utilizing the setting of the 2004 SEC mandate on increased reporting frequency of mutual fund holdings, we show that increased reporting frequency elevates window dressing (buying winners or selling losers shortly before the end of the reporting period). This effect is driven by low‐skill fund managers’ incentives to generate mixed signals. Funds managed by low‐skill managers experience lower returns, more outflows, and a higher collapse rate when their window dressing is elevated after the 2004 rule change. These results suggest that, although higher reporting frequency on agents’ actions can exacerbate signal manipulations, the related manipulation costs improve sorting among agents in the longer term.
This paper is aimed to evaluate the performance of all listed mutual funds in Dhaka Stock Exchange, decompose the performance to dive deeper into the sources of this evaluated performance, and examine the fund managers timing talent, using time-series weekly data on both market price and market NAV per share from January 2016 to December 2021. Form the performance evaluation analysis, Treynor, Sharpe and M2 measures revealed significantly different results under price and NAV bases, indicating that mutual funds’ price doesn’t reflect the funds’ fundamental and that funds are not well diversified which is confirmed later by the very low R2 values; Statistically insignificant alpha (Jensen and Hwang & Satchell) values indicate the lack of managerial expertise of fund managers which is again validated by the informational ratio based ranking differentials. Moreover, performance decomposition demonstrates that all the funds generated return by taking risk and creating imperfectly diversified portfolio in both price-NAV basis, but only a few funds produced return for managers’ excellent stock-picking skills in only price basis. Furthermore, Treynor & Mazuy and Henriksson & Merton (H-M) models show that not a single fund manager displays any significant timing talent in both models and in both price-NAV basis. These findings lead to the conclusion that the mutual fund sector of DSE is lagging far behind. Lack of educated investors, expert managers, disclosures, integrity, and timely policies are considered the main reason for this sluggish growth of mutual fund sector.
The COVID-19 was an unexpected health crisis that propagated into several countries as a result of globalization, where it was quickly transmitted to the stock markets by decreasing value, and the same thing was observed since the 2007–2008 subprime crisis. These crises are without doubt part of the undesirable effects of the stock markets since they negatively impact their behaviour, although the developed markets are less affected than emerging markets by the effects of crises reflecting on their growth, and in our case study (COVID19) health crise. It’s in this context that during this period several indices that attempt to replicate the performance of a market move downwards as well as upwards, hence the need to understand this behaviour in particular during this period. As traditional indices, ethical indices appeared in the 1980s and developed until the 1990s, where they are defined as a subset of their traditional benchmarks after going through a filtering process and constitute a separate investment area offering investors investment opportunities in line with their personal convictions and strategic orientations; These indices have been the subject of a few studies on their behaviour in the period of crisis, particularly in a developed country context. This article, therefore proposes to analyse the behaviour of ethical indices both socially responsible and Islamic in times of health crisis (COVID19) in a context of emerging countries from two different regions, Africa and Asia by reviewing their context, via their filtering criteria and an in-depth graphical analysis. Our results show that there is a highl correlation between these indices and the absence of a difference in performance in times of crisis.
IPO underpricing refers to the phenomenon of excess returns at the beginning of an IPO. This paper selects 505 companies listed on the STAR Market from 2019 to 2022 as samples, and examines the impact of technological innovation on IPO underpricing from the perspectives of R&D investment and R&D output. The results show that R&D investment, which is characterized by information asymmetry, leads to uncertainty in the market's valuation of companies, which will intensify IPO underpricing, but the signal effect of patents will significantly reduce the degree of IPO underpricing. The study suggests that companies should pay more attention to patent applications while increasing R&D investment, and focus on converting the results of R&D investment into patents in order to obtain more commercial value.
Accésit Premio Estudios Financieros 2000 El objetivo del presente trabajo es analizar la dimensión del efecto de la sincronización pasiva en la gestión de carteras. Este efecto se produce cuando una cartera no gestionada activamente presenta inestabilidad en el nivel de riesgo sistemático. En contraposición a ésta, la sincronización activa o market-timing implica una gestión activa de la cartera y, por lo tanto, cambios en el nivel de riesgo sistemático al objeto de anticipar adecuadamente los movimientos del mercado. En el trabajo se propone un modelo de beta dinámica que recoge el efecto de la sincronización pasiva atribuible a la evolución acumulada de las ponderaciones de los activos que forman la cartera. Los resultados muestran la importancia de este efecto en la aplicación de las medidas de performance y sincronización activa, que evalúan los resultados de carteras institucionalmente gestionadas como es el caso de los fondos de inversión.
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