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In this paper, we use Bayesian nonparametric learning to estimate the skill of actively managed mutual funds and also to estimate the population distribution of skill. A nonparametric hierarchical prior, where the hyperprior distribution is unknown and modeled with a Dirichlet Process prior, is used to model the skill parameter, with its posterior predictive distribution being an estimate of the population distribution. Our nonparametric approach is equivalent to an infinitely ordered mixture of normals where we resolve the uncertainty in the number of mixture components by learning how to partition the funds into groups according to the average ability and the variability in the skill of a group. By resolving the mixture’s uncertainty, our nonparametric prior avoids having to sequentially estimate and test an array of pre-specified, finite ordered, mixture priors. Applying our Bayesian nonparametric learning approach to a panel of actively managed, domestic equity funds, we find the population distribution of skill to be fat-tailed, skewed towards higher levels of performance, with two distinct modes – a primary mode where the average ability covers the average fees charged by funds, and a secondary mode at a performance level where a fund loses money for its investors.

We study how mutual fund managers gain an edge in selecting stocks in an era of globalization. We use textual analysis to construct a measure that captures a mutual fund's offshore exposure concentration through holding US multinational firms. We find that funds with a higher offshore concentration index (OCI) perform significantly better, with the difference in four-factor alpha between the top and bottom deciles amounting to 2.95% per annum. Fund managers’ overweighting of firms with operations in certain countries can be partly attributed to their foreign ethnicity. High OCI fund managers have an information advantage regarding firms’ fundamentals, such as earnings.

The dissertation presents three empirical studies in the field of asset management. The first essay investigates whether within-firm connections alter manager career concerns and if investment distinctiveness, employee risk-taking and fund performance are affected. I measure connectedness using a dataset of within-firm networks based on 13,357 mutual fund managers across 26 years. Well-connected managers within the fund family face lower performance-turnover and -promotion sensitivities. The advantageous treatment enjoyed by better-connected managers in these career altering decisions is associated with lower risk-taking and lower investment distinctiveness of the funds they manage. Funds of better-connected managers deviate less from their peers in systematic factor and sector exposures and exhibit lower risk-adjusted performance. Mutual fund investors are unaware of this phenomenon, illustrated by the lack of a flow differential. The second essay uses proprietary data on self-reported employee reviews from Glassdoor.com to study the relationship between employee satisfaction and mutual fund performance and size. Using the staggered adoption of Anti-SLAPP (Strategic Lawsuits Against Public Participation) laws in the U.S. and variation from mergers between asset management companies to tackle endogeneity issues, we find that employee satisfaction is positively linked to fund performance and size but that only performance-critical employees' satisfaction matters. A one-point increase on the 5-point scale of employee satisfaction leads to a 36bps (36bps) higher annual 3-factor (4-factor) abnormal performance. Furthermore, a one-point increase of employee satisfaction is associated with a 0.2% larger mutual fund size. Finally, while there is a positive effect of employee satisfaction on risk-taking, we cannot establish a causal relationship. The third essay investigates why fund families continue to outsource the portfolio management of their funds to unaffiliated investment advisors despite the well-documented underperformance of outsourced funds. Our empirical analysis shows that investment expertise, or the lack of it, drives the decision to enter an outsourcing relationship and impacts the way fee revenues are shared. Furthermore, market thickness, defined as the number of subadvisors the fund family could contract with, also impacts the fund family's decision to outsource and its relative bargaining power in the resulting relationship. We link the impact of market thickness on the relative power of both parties in the outsourcing relationship to the threat of dismissal of the subadvisor and show that outsourced funds operating in thick markets perform better. Finally, once we account for the initial decision to outsource a mutual fund, we find that outsourced funds do not underperform and are not smaller than in-house managed funds. The fund family lacking the relevant in-house expertise could not have achieved a better performance than the subadvisor and the subadvisor, because of its lack of distribution capabilities, could not have gathered more assets.

Purpose: The main purpose of this study is to analyse the performance of mutual funds using Risk- Return Relationship Models. Theoretical framework: One of India's most important financial intermediaries, mutual funds can provide a wide range of financial services to small and large investors. They are also involved in the country's transformation, and their market participation has become more important. Evaluating a mutual fund's performance concerns investors, researchers, and fund managers. It should be conducted in a way that helps investors make informed decisions and maximize returns. A regular evaluation of a fund's performance is also essential for investors. Design/methodology/approach: The performance of 12 growth-oriented mutual funds has been evaluated using three Risk Adjusted performance measures, namely the Treynor index, Sharpe index, and Jensen measure. Treynor Index, developed by Treynor and Mazuy (1966), defined the measure as the ratio of returns to systematic Risk (Beta). The higher the ratio better the performance. Sharpe Index, developed by Sharpe (1964) defined as the ratio of returns to the variability of returns. Jensen's measure (Jensen 1968) regresses excess fund return with the excess market return. Monthly data was used during the period from Jan 2015 to Dec 2019. Further monthly returns of 12 diversified Equity mutual funds were compared with the returns of the B.S.E.( Bombay Stock Exchange) national index during the same period. Findings: It is identified from the results that the mutual funds have not performed better than their benchmark indicators except the ICICI Multi-asset fund and HDFC mid-cap opportunity fund in terms of a non-risk adjusted measure of the average returns as well as in terms of Risk-adjusted performance measures. Research, Practical & Social implications: Fund houses, Fund managers, researchers, and mutual fund investors can benefit more from a strong risk management foundation. It can help them make informed decisions and maximize their returns. Originality/value: This study differs from past studies because it examined the risk-adjusted performance of a few mutual funds, which ultimately may use by investors and policymakers to enhance the returns in these funds.

Purpose: The present study aims to determine the factors influencing investment intention and actual investment behaviour in mutual funds. The study uses financial knowledge and risk tolerance as moderators and past behavioral bias as a mediator. Theoretical framework: The Theory of Planned Behaviour (TPB) appears to have become a very useful model for predicting various investing behaviours. Therefore, the present utilises the TPB model to analyse mutual fund investment behaviour. Design/methodology/approach: The convenience sampling method was used to collect respondents from a population of 582 retail investors through questionnaire survey This research used partial least squares structural equation modelling (PLS-SEM) as the main method of data analysis using SmartPLS 4. Findings: Attitude, financial knowledge, and risk tolerance emerged as the most important determinants of mutual fund investment intention. This highlights the significance of creating favorable conditions in terms of accessibility, which may encourage and ease the decision of investors to purchase mutual funds. Research, Practical & Social implications: Marketers can explain how their mutual fund offerings would help both the market and investors. Marketers should prioritize proper communication about the benefits of mutual funds to investors, as communication is regarded as a critical tool for the success of mutual fund products. Originality/value: To understand individual investors' intentions to engage in mutual funds, the impact of attitude, subjective norms, and perceived behavioural control on investor intentions and, actual investment behaviour were hypothesised and analysed, financial knowledge and risk tolerance functioning as moderators. Additionally, past behavioural bias is a mediator.

Investment funds that claim to focus on socially responsible stocks have proliferated in recent times. In this paper, we verify whether ESG mutual funds actually invest in firms that have stakeholder-friendly track records. Using a comprehensive sample of self-labelled ESG mutual funds (as identified by Morningstar) in the United States from 2010 to 2018, we find that these funds hold portfolio firms with worse track records for compliance with labor and environmental laws, relative to portfolio firms held by non-ESG funds managed by the same financial institutions in the same years. Relative to other funds offered by the same asset managers in the same years, ESG funds hold stocks that are more likely to voluntarily disclose carbon emissions performance but also stocks with higher carbon emissions per unit of revenue. Despite these findings, ESG funds hold portfolio firms with higher average ESG scores. We show that ESG scores are correlated with the quantity of voluntary ESG-related disclosures but not with firms’ compliance records or actual levels of carbon emissions. Finally, ESG funds appear to underperform financially relative to other funds within the same asset manager and year, and to charge higher fees. Our findings suggest that socially responsible funds do not appear to follow through on proclamations of concerns for stakeholders.

In this paper, we investigate the impact of ownership structure on corporate advertising expenditures. Using mutual fund mergers as an exogenous shock to ownership structure, we find that competing firms owned by the same institutional blockholders experience a significant reduction in advertising expenditure. The reduction in advertising expenditure is more likely to occur in the presence of higher coordination benefits or lower coordination costs. Specifically, this effect is more pronounced for firms in more competitive industries, in higher advertising-intensity industries, with greater common ownership, with more concentrated institutional ownership, and with headquarters located in the same state. Overall, our empirical evidence indicates that ownership by common institutional investors significantly affects corporate advertising strategy. This paper was accepted by Matthew Shum, marketing.

Shari’ah mutual funds has its own charm than other types of mutual funds. Shari’ah mutual funds is not limited only to Muslims as the general public, who are already seeing the benefits of investment that is based on the choice of sector and company specific criteria more promising and minimize risk. Islamic mutual funds are able to contribute the confidence of investors amounted to 3.31% in 2011, 4.31% in 2012 and 3.79% in 2013. So the value of the confidence of investors on mutual fund products sharia to 2013 is still around 3-4% . As for growth on Islamic mutual funds into one of the capital market products showed an increase in value in 2012 amounted to 3.79% later in the year 2013 to 4.32%. Investment portfolio management works based framework (framework) for investment management which covers the planning, implementation, evaluation, and adjustment. In mutual funds, investment managers responsible for investment activities, which includes the analysis and selection of investment types, and perform the necessary actions for the benefit of investors. Form of mutual fund performance measurement Shari’ah assessed net asset value (NAV) of the sub weekly. Showed a good performance rekasadana Shari’ah when in a period of return obtained is more positive. Keywords ; Reksadana Syari’ah, Manajemen Portofolio, Nilai Aktiva Bersih (NAB)

Foreign investors’ information disadvantage is often viewed as a key impediment to their investment. This study questions whether foreign investors’ home media mitigates this information barrier by investigating the relation between U.S. mutual fund ownership and U.S. media coverage of local stocks in their host countries. Using a large sample of 38 host countries, we document a positive association between U.S. mutual fund ownership in a local stock and the coverage of U.S. major news providers on that stock. We find that home media-covered stocks incur lower information acquisition costs and gain greater investor awareness from U.S. investors. The home media effect is most salient in host countries with low quality information environments, supporting a novel home media effect that foreign investors tend to rely on their home market media coverage as an information source. The home media effect helps explain the prominent international finance anomaly regarding the dependence of firm returns on home and foreign market factors.

This study examines fund manager skill using a sample of Real Estate Investment Trust Unit Investment Trusts (REIT UITs). It also investigates how REIT UIT performance compares to investing in REIT mutual funds. Are REIT UIT fund managers able to select REITs that deliver superior performance? Using a hand-collected sample of REIT UITs from May 2009 to July 2015, this study finds that REIT UITs do not deliver statistically significant positive alpha. This result is consistent with the Comer and Rodriguez (2015) finding for a sample of diversified UITs, but counter to the Cici et al. (2011) finding of positive alpha for REIT mutual fund managers. This is the first paper to investigate fund manager stock selection skill in REIT UITs.

Continuous-time regime-switching models are a very popular class of models for financial applications. In this work the so-called signal-to-noise matrix is introduced for hidden Markov models where the switching is driven by an unobservable Markov chain. Its relations to filtering, i.e. state estimation of the chain given the available observations, and portfolio optimization are investigated. A convergence result for the filter is derived: The filter converges to its invariant distribution if the eigenvalues of the signal-to-noise matrix converge to zero. This matrix is then also used to prove a mutual fund representation for regime-switching models and a corresponding market reduction which is consistent with filtering and portfolio optimization. Two canonical cases for the reduction are analyzed in more detail, the first based on the market regimes and the second depending on the eigenvalues. These considerations are presented both for observable and unobservable Markov chains. The results are illustrated by numerical simulations.

We identify fixed-income mutual funds as an important contributor to the unusually high selling pressure in liquid asset markets during the COVID-19 crisis. We show that mutual funds experienced pronounced investor outflows amplified by their liquidity transformation. In meeting redemptions, funds followed a pecking order by first selling their liquid assets, including Treasuries and high-quality corporate bonds, which generated the most concentrated selling pressure in these markets. Overall, the estimated price impact of mutual funds was sizable at a third of the increase in Treasury yields and a quarter of the increase in corporate bond yields during the COVID-19 crisis.

We study whether the stability of mutual funds and the propensity of a run among investors depend on the ownership structure. Flows of funds run by banks or by firms that belong to the same financial group as a bank are less volatile and less sensitive to bad past performance. This enables bank-affiliated funds to better weather distress and to hold lower precautionary cash buffers in comparison with their unaffiliated peers. Banks provide liquidity support to distressed affiliated funds increasing their stakes in funds that are experiencing large outflows. We find that liquidity support and other benefits of bank affiliation are stronger if the parent bank is more liquid and better capitalised. Analyzing the aftermath of two exogenous shocks to financial markets -- the Brexit referendum and political uncertainty in Italy -- we show that distress in the banking system spills over to the mutual fund sector via ownership links.

This paper studies the relationship between mutual fund management's direct experience with air pollution and the fund's engagements with portfolio companies on environmental issues. We find that higher air pollution in a mutual fund's headquarter county increases the propensity of the fund to vote in support of shareholders' environmental proposals and to liquidate its holdings of portfolio firms with lower environmental ratings. We also find that greater air pollution exposure of a mutual fund predicts better environmental performance at its portfolio companies. To establish causality, we use elevated air pollution produced by large wildfires in a mutual fund's headquarter county as an instrument and identify similar effects on the outcome variables. These results suggest that a mutual fund's direct exposure to pollution can inform its environmental engagements at its portfolio companies.

Using daily mutual fund returns to estimate market timing, some econometric issues, including heteroscedasticity, correlated errors, and heavy tails, make the traditional least squares estimate in ...

We study the extent of cross-asset learning in financial markets by examining the spillover effects around mutual fund fire sales, which lead to a well-documented impact-reversal pattern in returns. We find that the returns of fire sale stocks spill over onto the stock returns of economic peers with a magnitude of around one-third of the original effect. These spillovers extend to liquidity and are not explained by common funding shocks or the hedging activity of liquidity providers. We conclude that they represent information spillovers due to learning from prices, thus identifying cross-asset learning as an important driver for the commonality in returns and liquidity. (JEL G11, G12, G14, G23) Received July 1, 2021; editorial decision August 30, 2021. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We examine the effect of investment restrictions on mutual fund performance. Utilizing a unique panel of mutual fund contract changes, we explore several ways these changes affect a fund, including: performance, funding risk, and managerial contracting. We find that the general shift towards fewer restrictions over the period 1996–2011 has provided little benefit to mutual funds. Specifically, neither performance nor flow increased and we observe no changes in risk on average. We do find, however, an increased likelihood of management turnover when restrictions are removed. We conclude that contract restrictions do not explain the general underperformance of mutual funds, and that these investment restrictions are not binding.

We use an instrumental variables (IV) approach to examine the effects of dynamic endogeneity when estimating the relationship between mutual fund flows and performance. Unlike the one-stage estimation approach commonly used in prior research, the IV approach allows us to address reverse causality between flow and performance. Through rigorous exclusion tests, we conclude that fund media coverage, risk ranking, and management structure win in a horse race as exogenous instruments for fund flow, while the fund turnover ratio and institutional share perform best as instruments for fund performance. We then demonstrate that endogeneity bias leads to inaccurate inferences in one-stage estimates, as evidenced by the reversals of the signs of flow and performance coefficient estimates when we switch to the IV approach. We find that careful attention to model specification allows us to resolve several widespread inconsistencies in the literature that were likely driven by model misspecification.

The topic about institutional investor being a monitoring role has been widely discussed but different results exist in previous empirical studies. Along with their progressively development, institutional investors are now playing more important role in Chinese capital market. Using samples from Chinese capital market, this paper collects fraud data and data of mutual funds’ ownership in listed firms between 2008 and 2015 to examine the monitoring function of institutional investors against accounting fraud. To go deep into the monitoring incentives of investors that fall into different categories, mutual funds are further classified as heterogeneous groups according to their investment strategy and investment durations. The monitoring role of mutual funds in different groups and their influence as the disincentive to accounting fraud of listed firms are investigated in the paper. Mutual fund ownership is found to be able to curb the incidence of accounting fraud. Active mutual funds are able to conduct more effective monitoring when compared with passive mutual funds. It is also reported that short-term mutual funds are more significant than long-term mutual funds in monitoring. Policy makers may need to normalize institutional investments by quantified indicators or in other reasonable ways. Key words: Accounting fraud, institutional investors, investment duration, monitoring role.

We develop a flexible and bias-adjusted approach to jointly examine skill, scalability, and value added across individual funds. We find that skill and scalability (i) vary substantially across funds, and (ii) are strongly related as great investment ideas are difficult to scale up. The combination of skill and scalability produces a value added that (i) is positive for the majority of funds, and (ii) approaches its optimal level after an adjustment period possibly due to investors' learning. These results are consistent with theoretical models in which funds are skilled and able to extract economic rents from capital markets.

Using information on mutual fund trades executed from 1998 to 2017 by 31,513 individual investor clients of a major Portuguese financial institution, we study the relationship between the disposition effect, financial literacy and trading experience. We find that mutual fund investors exhibit strong disposition effect. The tendency to hold losers is partially offset with literacy: not only holding a university degree reduces the propensity to hold on to loser funds but also higher financial knowledge and stronger math skills reduce the disposition effect. Literacy also plays a role in shaping the way experience affects this bias. Evidence of the disposition effect persists after accounting for redemption fees, bad emotions, irrational beliefs, market sentiment and the existence of someone to blame.

This study aims to determine whether conventional money market mutual funds perform better than sharia money market mutual funds or vice versa during the COVID-19 pandemic in Indonesia. This research method is descriptive with a quantitative comparison approach. This study employed secondary data obtained from IDX, Indonesian Bank, and Pasar Dana website. The research employed the money market mutual funds data, Net Asset Value, BI 7 Days Repo rate during year 2020. Sharpe ratio utilized in this research to determine the money market mutual funds performance. Then, the result compared by using Independent sample T-test on SPSS. The result uncovers that in general the performance of conventional money market mutual funds performance superior the sharia money market mutual funds performance during covid-19 in Indonesia. However, both mutual funds average Sharpe ratio show the negative number during 2020. Moreover, there are no significant difference between conventional and sharia money market mutual funds returns during the period 2020. The high different return on the maximum return due to some conventional mutual fund perform exceptional during 2020.

Purpose Mutual fund investors assess a fund manager’s skills when allocating their capital. To identify the rationale behind retail investors’ decisions, this study aims to examine the relation between mutual fund flows and abnormal returns (alpha), as well as the various risk factors in the Japanese mutual fund market, which has distinctive characteristics regarding investors and distributors. Design/methodology/approach Six standard asset pricing models are used to investigate how investors assess mutual fund managers’ skills: the market-adjusted return, the capital asset pricing model and the Fama–French three-factor model and its augmented versions. Findings Contrary to the literature, this study finds that investors in Japan mainly rely on alpha to assess mutual funds. In particular, investors respond to alpha for fund inflows and their evaluations depend on the market environment and their mutual fund search costs. Originality/value This study measures the response of investors to the skills of mutual fund managers in the Japanese market – especially for funds purchased through bank-related distributors that have aimed to capture inexperienced retail investors since deregulation in the 1990s – and reveals their high response to alpha.

This paper investigates the implications of investor learning for the sensitivity of mutual fund flows to past performance. We illustrate theoretically that when some sophisticated investors learn from past fund performance to form their posterior expectations of managerial ability, the flow-performance sensitivity should be weaker for funds with more volatile past performance and longer track records. Moreover, the dampening effects of performance volatility and fund age on the flow-performance sensitivity should be stronger for funds attracting more sophisticated investors. We provide supporting evidence for this investor learning hypothesis using mutual fund flows and compare the relative level of sophistication among investors in load versus no-load funds, institutional versus retails funds, and star versus non-star funds.

One of the major trends in the mutual fund industry is the rising importance of passive investing. One of the responses of the investment community to this challenge has been the creation of enhanced return index funds. In this paper, we examine the performance of enhanced index funds and find that they outperform index funds when we analyze both pre-expense performance (management ability) and post-expense performance (investor returns). However, when we use any of several criteria that have been proposed for picking the best fund from among those following some index, index funds outperform enhanced index funds.

The purpose of this research is to identify the factors that support mutual funds investment decisions through overconfidence, risk perception, loss aversion, availability, and herding variables on the investment decisions of the residents of Batam City. Data were collected through questionnaires and processed using multiple linear regression. The results of testing and processing research data show that overconfidence, loss aversion, and herding significantly positively affect investment decisions, while risk perception and availability do not affect investment decisions.

Management companies assign some portfolio managers to run funds within a single investment objective (i.e., specialists), and others to run funds across several investment objectives (i.e., generalists). Our results show that funds achieve higher performance when they appoint superior pickers as specialists and market timers as generalists. We argue that these decisions are the result of a better match of manager mandates with the way information is collected and processed in each investment strategy. Overall our results are consistent with decision-making in fund families that add value to their investors by aiming to optimally assign or reassign portfolio managers.

This paper analyzes Chinese mutual fund managers’ ability to time aggregate market confidence in China’s securities market. To measure aggregate market confidence in the Chinese market, we construct a Composite Investor Confidence Index (CICI) based on investor confidence surveys from institutional and individual investors. The study finds that managers successfully shift their fund exposure relative to shifts in the aggregate confidence level in the market. Additional analysis shows that top confidence timers outperform bottom confidence timers by more than 4% per year. The study also finds that mutual funds possessing confidence timing ability tend to be younger funds that are larger in size and have higher expense ratios. Our findings remain robust after controlling for market, liquidity and volatility timing, as well as confidence reaction.

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.

Identifying similar mutual funds among a given universe of funds has many applications, including competitor analysis, marketing and sales, tax loss harvesting, and so on. For a contemporary analyst, the most popular approach to finding similar funds is to look up a categorization system such as Morningstar categorization. Morningstar categorization has been heavily investigated by academic researchers from various angles, including using unsupervised clustering techniques in which clusters were found to be inconsistent with categorization. Recently, however, categorization has been studied using supervised classification techniques, with the categories being the target labels. Categorization was indeed learnable with very high accuracy using a purely data-driven approach, causing a paradox: Clustering was inconsistent with respect to categorization, whereas supervised classification was able to reproduce (near) complete categorization. Here, the authors resolve this apparent paradox by pointing out incorrect uses and interpretations of machine learning techniques in the previous academic literature. The authors demonstrate that by using an appropriate list of variables and metrics to identify the optimal number of clusters and preprocessing the data using distance metric learning, one can indeed reproduce the Morningstar categorization using a data-driven approach. The present work puts an end to the debate on this issue and establishes that the Morningstar categorization is indeed intrinsically rigorous, consistent, rule-based, and reproducible using data-driven approaches, if machine learning techniques are correctly implemented. Key Findings ▪ Academic literature has time and again questioned the consistency and robustness of mutual fund’s categorization systems, such as Morningstar categorization, by contrasting them with unsupervised clustering of funds. ▪ Here, the authors settle the debate in favor of Morningstar categorization by pointing out the use of incorrect lists of variables and interpretation of machine learning algorithms in the previous literature, while emphasizing that the main missing piece from the machine learning side in previous research was the appropriate distance metric. ▪ The authors employ a machine learning technique called distance metric learning and reproduce the Morningstar categorization completely using a data-driven approach.

A Mutual Fund is a professionally-managed form of collective investments that pools money from many investors and invests it in stocks, bonds, short-term money market instruments, and/or other securities. Mutual Fund is a trust that pools the savings of a number of investors who share a common financial goal. This pool of money is invested in accordance with a stated objective. The joint ownership of the fund is thus “Mutual”, i.e. the fund belongs to all investors. The money thus collected is then invested in capital market instruments such as shares, debentures and other securities. The income earned through these investments and the capital appreciations realized are shared by its unit holders in proportion the number of units owned by them. Thus a Mutual Fund is the most suitable investment for the common man as it offers an opportunity to invest in a diversified, professionally managed basket of securities at a relatively low cost.

This paper aims to empirically compare the performance of the smooth transition exponential smoothing (STES) method against the well-known generalized autoregressive conditional heteroskedasticity (GARCH) model in one-step-ahead volatility forecasting. While the GARCH model captured most of the stylized facts of the financial time series, threats of outliers in the leptokurtic distributed series remain unresolved. The study compared volatility forecasting performance of a total of 22 models and methods comprising STES, GARCH, and some ad-hoc forecasting. The daily returns of seven mutual fund indices (derived from 57 individual equity mutual funds) under two different economic conditions (sub-periods) were applied across all competing models. Findings revealed that the STES method with error and absolute error as transition variables emerged as the best post-sample volatility forecasting model in both sub-periods with and without financial crisis impact, as verified by model confidence set (MCS) procedure. The implications based on the results are: (1) both the sign and size of yesterday’s news shock have an impact on today’s volatility; (2) the STES method is resilient to outliers, and hence superior to GARCH and other volatility forecasting approaches examined. This study contributes an empirical approach in forecasting the risk of mutual funds investment for investors and fund managers, as well as extending the scope of volatility forecasting literature into the less explored mutual funds.

PurposeMutual funds are the second most preferred investment option in India and have garnered considerable research interest. The focus of Indian studies thus far has been restricted to the bottom-up approach of investing which rewards a fund manager for picking winner stocks and generates superior returns. While changing portfolio allocation as per varying macro-trends has been instrumental in generating superior returns, it has not been given the desired attention. This study addresses this important research gap.Design/methodology/approachThe authors analyze the industry selection ability of the fund manager on a robust sample by decomposing alpha into alpha due to industry selection and alpha attributable to stock selection. Alpha estimates are computed on a robust sample of 34 open-ended Indian equity mutual funds for a 10-year duration 2011–2020 using three base models of asset pricing – single-factor, four-factor and five-factor alpha under panel data methodology.FindingsThe study leads us to four major findings. One, industry selection explains more than two-fifth of the alpha both in cross-section and time series of returns; two, industry selection exhibits persistence for more than four quarters across asset pricing model; third, younger funds have level playing when alpha from picking right industries is concerned; four, broad industry allocation continues to explain superior returns as sector allocation undergoes consolidation during ongoing COVID-19 pandemic and funds increase exposure to defensive stocks, consistent with folio allocations as per macroeconomic conditions.Research limitations/implicationsThe authors find strong evidence of persistence in the case of alpha attributable to the industry selection component, and the findings are consistent with the persistence results reported in the empirical literature. While some funds excel in stock-picking skills and others excel in picking the right industries, both skills together make for winner funds that attract larger investor flows as investors chase superior performance. The authors also find no evidence of diseconomies of scale in the case of industry allocation alpha generated by the fund managers.Practical implicationsThe results suggest a fresh approach for investors while making mutual fund investment decisions; the investors can achieve superior returns by assessing industry selection skills as it tends to provide a more holistic picture concerning a perennial question – why some funds outperform and continue to contribute to investor's wealth?Social implicationsMutual funds have become a favored investment option for Indian investors more so as a disciplined investment option owing to dismal financial literacy rates. The study throws light on a relatively unaddressed dimension of choosing winner funds. The significance of right sector allocation assumed even more significance with the onset of the pandemic which lends further credence to the findings of the study.Originality/valueResearch has been conducted on secondary data extracted from a well-cited database for Indian mutual funds. Empirical analysis and conclusion drawn are based on authentic statistical analysis and adds to the existing literature.

PurposeThe purpose of this paper is to explore how heuristics are formed and whether herding and prospect theory act as antecedents to heuristics. The relationship is explored specifically for millennials.Design/methodology/approachThe proposed relationship is explored specifically for millennials. Herding and prospect theory are modelled as antecedents to heuristics. The study uses survey data from 923 millennials from India to test the model for two financial products: equity and mutual funds. Regression analysis is used to evaluate the model.FindingsFindings support the role of herding and prospect theory as antecedents to heuristics of millennials although to varying degrees for equity and mutual fund investments. The impact of herding on heuristics is likely to be smaller for equity investments as compared to mutual fund investments.Research limitations/implicationsThe findings provide insights into how heuristics are formed for millennials. The findings add to literature by beginning a new line of inquiry on how heuristics are formed. Since the model is tested on a single generation, future research can test the model on other generations. In addition, future research can also add more antecedents to our proposed model.Practical implicationsFindings from this study can provide financial planners and marketers with an understanding of how heuristics are formed for millennials. Financial planners can use these insights while providing financial advice to this generation and marketers can use them to create more relevant outreach.Social implicationsFinancial investments are an important conduit for financial security. By understanding the cognitive processes that influence financial investment decision-making, it is possible for educators to create content appropriately and for financial planners to advise clients accordingly to enable optimal financial decisions that will be wealth-creating.Originality/valueExisting literature primarily treats heuristics, herding and prospect theory as being independent of each other. The authors take a novel approach to model the antecedents to heuristics to be herding and prospect theory. The model is tested on millennials for two financial products: equity and mutual funds.

The purpose of this paper is to examine the widely believed beating capacity of actively managed funds during the market downturn. This popular hypothesis has been tested with the performance of Indian Equity Mutual Funds during the pandemic period. The conditional alphas are estimated using lagged instrumental variables with the fixed effect/LSDV estimator and the sys-GMM estimator in contrast to the OLS estimation from a sample of 1271 schemes for 5 months from 1st March 2020 to 31st July 2020. The study’s findings indicate that the actively managed Indian mutual fund co-moves with the market and does not possess the ability to beat the market. The major implication comes from the application of fixed effect and GMM estimators for the performance evaluation of Indian Mutual Funds’ during the crisis period, and it serves the investors in deciding the profitable investment opportunities., Highlights The paper examined the ability of actively managed funds to beat the market downturnThe study applied Sys-GMM and LSDV/fixed effect models for estimating the performance alphaThe actively managed Indian mutual funds do not possess the ability to outperform the market

We find evidence for the beta anomaly in mutual fund performance. This anomaly is not accounted for in the standard four-factor framework, nor by the addition of a betting-against-beta factor to the benchmark model. We identify the active component of alpha (active alpha) not attributable to the passive effects related to beta. Active alpha is persistent and associated with superior portfolio performance. We find that, although many investors use standard alpha to allocate capital, a subset of sophisticated investors allocate their money based on active alpha. Our procedure is useful across the commonly used benchmark models for measuring performance and can be extended to accommodate other potential factor beta anomalies. This paper was accepted by Karl Diether, finance. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.4639 .

Indonesian people's interest in stocks and mutual funds is still low compared to other investment instruments. This study aims to evaluate the performance of mutual funds in Indonesia before and during the COVID-19 pandemic. Markov chain is used to assess the performance of each type of mutual fund because of its accuracy and suitability for data showing volatility. The results showed that all types of mutual funds experienced an increase with a probability of more than 50% in the long term. Money market mutual funds, both Islamic and conventional, have the highest probability of increasing by more than 90%. The first passage time can indicate how much price volatility is, wherein in this study, stock mutual funds and sharia stock mutual funds have high volatility. Before conducting further technical analysis, the Markov chain can be used to choose the type of mutual fund that is anticipated to increase.

In this paper, we examine how mutual fund managers behave to fluctuations in market volatility. We use a sample of daily return from countries around the world to evaluate how manager perform to publicly available information. There is a lack of empirical studies that examine the relation between conditional market returns and conditional volatility on a global scale; we provide evidence across countries to answer this question. Our study provides new evidence about conditional mutual fund performance across countries. We find that during periods of high market volatility mutual funds reduce market exposure across all countries; this implies that systemic risk is particularly sensitive to changes in market volatility around the world.

This article aims to investigate the factors that influence the mutual fund industry’s growth in Pakistan. Financial markets are always exposed to systematic risks which are out of one’s control. Mutual funds being part of this market are dependent on the macroeconomic factors in the country. Pakistan’s financial market is quite volatile thus slightly change in any economic indicator can affect the growth of mutual funds. Globally, Mutual fund industry is expanding day by day and Pakistan is still far behind to meet with other country like USA, UK, and India as it contributes only 1.6% of the GDP in the year 2020. In this article, influence of four independent macroeconomic factors i.e. GDP growth rate, interest rate, inflation rate and exchange rate was analyzed against the dependent value of Asset under Management. Fiscal year data from 2011-2020 was taken from different authentic sources to perform the regression analysis using SPSS tool. Study concluded that GDP growth rate, interest rate and inflation rate have negative impact on the growth of mutual fund industry which means the value of AUM decreases when these factors tend to increase in the economy. Further, exchange rate has positive impact indicating that the value of AUM increases with the increase of this factor in the economy in Pakistan. Keywords: Mutual Funds, Growth, Asset Under Management, Macroeconomic Factors, Regression Analysis, Pakistan.

PurposeWhen a fund manager leaves, the investment strategy of the fund changes or remains the same. The departing fund manager's resignation is either forced or voluntary. The study investigates the relationship between the portfolio manager's transition and the fund's investment strategy and how the change affects the mutual fund returns in the subsequent period.Design/methodology/approachThe authors examine 148 fund manager changes in India between April 2005–March 2018 using three performance measures: abnormal return (fund return minus benchmark return), Jensen's alpha and Carhart four-factor alpha. The analysis includes an event study methodology, followed by a two-step Fama–MacBeth regression approach.FindingsContrary to the previous studies conducted in the developed markets, the authors find that fund performance improves irrespective of whether the fund manager change is forced or voluntary. The outperformance after the fund manager's exit is significant for funds belonging to the larger fund families.Originality/valueIn the context of investment management, the authors provide a conceptual framework to understand the effect of fund manager exit on mutual fund performance. The authors substantiate their arguments with empirical evidence. To the best of the authors' understanding, this is the first research to examine the effect of changing mutual fund managers in an emerging market setting.

Purpose This paper aims to study manipulation and performance persistence in equity mutual funds. To this end, Manipulation-Proof Performance Measure (MPPM) and Doubt Ratio, along with a number of current performance measures are used to evaluate the performance of equity mutual funds in Iran. Design/methodology/approach The authors investigate performance manipulation by 1) comparing the results of the MPPM with the current performance measures, 2) checking the Doubt Ratio to detect suspicious funds. Additionally, the authors investigate performance persistence by forming and evaluating portfolios of the equity mutual funds at several time horizons. Findings The authors conclude that there is no evidence of performance manipulation in the equity mutual funds. Additionally, when comparing the performance of the upper (top) tertile portfolios and the lower tertile portfolios, in all of the studied 1, 3, 6 and 12-month horizons, the authors find performance persistence in the equity mutual funds. Originality/value To the best of the authors’ knowledge, this research is the first study to investigate the performance manipulation in the Iranian equity mutual funds, and also is the first study in Iran that uses the MPPM and the Doubt Ratio in addition to a number of current performance measures to investigate the performance persistence in the equity mutual funds at several time horizons.

This study examines the performance of equity mutual funds using Sharpe, Treynor, Jensen, and M2. The sample used in this study is 57 stock mutual funds in 2015 – 2019 and 29 stock mutual funds in 2010 – 2019. The performance of stock mutual funds will be compared with LQ – 45 and IHSG to find out whether they underperform or outperform on market performance. The results showed that when seen in years 2015 - 2019 with the benchmark LQ - 45, 11 equity funds outperformed by using Sharpe, Treynor, and M2, and 12 mutual funds stocks outperformed by using a Jensen. Using the Composite Index as the benchmark, it is found that four equity funds outperformed by using Sharpe, M2, and 5 equity funds outperformed by using Treynor and Jensen from 57 samples of mutual fund shares. From the performance of the year 2010 - 2019, it is found that the 10 equity funds outperformed by using Sharpe and M2, and 15 equity funds outperformed by using Treynor and Jensen with LQ – 45 as the benchmark. The Composite Index found that 0 of stock mutual funds outperformed by using Sharpe and M2, while 3 mutual funds outperformed using Treynor and 2 mutual funds outperformed using Jensen from 29 stock mutual funds samples.

This study examines whether the management style of a fund differs depending on the type of fund being managed for tax purposes, given the rules of temporary tax relief for fund investments. The study considers a change in the ratio of tax-favored assets to the net asset value of a tax relief qualified fund around the effective date of tax relief laws in South Korea in 2007 and 2016. A regression model is used to test sample data from domestic and overseas equity funds available in the three months before and after the 2007 and 2016 Restriction of Special Taxation Act came into effect. It was found that the ratio of the value of tax-favored assets to the net asset value in the tax relief qualified fund increased significantly since the enactment of tax relief laws in both 2007 and 2016. These findings suggest that fund managers may try to change the asset allocation in a managed fund to increase the after-tax return of the fund investor, which means that fund managers do take into account the potential tax burden on fund investors and try to minimize it. AcknowledgmentThis work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF- 2019S1A5A8035027).

Despite the growing number of millennials and fintech having been present for some years now in mutual funds in Jakarta, the market share of PT PAM Indonesia has not increased. The number of unhappy customers reflected by the number of inactive customers has been increased to 43% of its total customers. due to the disappointment with the company’s services. This study is investigating the influence of service quality on consumer satisfaction and consumer perceived value as a mediating variable in mutual funds in Jakarta. This study contributes to the customer's perceived value literature by providing evidence in the mutual fund industry. To gather the primary data, in this study using a quantitative approach by sending a questionnaire to 100 millennials customers. SPSS software was used to analyze the satisfaction level in different locations and demographic factors, whilst SmartPLS3 was used to analyze the relationship between variables and to test hypotheses. The result showed that consumer perceived value mediates the relationship between service quality on consumer satisfaction. The findings suggest to retrieve customer satisfaction, the company must improve its service quality to meet consumer perceived value especially for the millennials in the mutual fund industry.

The mutual fund industry in India has registered significant growth since the liberalization of Indian Economy in 1991 and has emerged as a significant financial intermediary.The growing importance of Indian mutual funds may be noted in terms of the increased mobilization of funds and the increasing number of schemes and investors in the industry.The results show that there is a significant association between educational qualification of the investors and the risk tolerance level and occupation of the investors and the risk tolerance level.The results further indicate that there is no significant association between occupation of the investors and the level of knowledge of mutual fund and monthly savings of the investors and the level of knowledge of mutual fund.Therefore, the investors have to consider the prevailing rate of risk free returns and to compare the fund returns with it. Based on this the selection of schemes and the choice of investment avenues can be decided.Due to the fund man timing skill,stock selection ability,imperfect diversification the schemes had suffered with low return. Hence to increase the fund return the concerned fund managers have to improve all these skills.

The coronavirus disease (COVID-19) has adversely impacted the globally interconnected economy and brought the tourism sector to a temporary standstill. As such, this study aimed to investigate the spillover effect of industrial sectors by emphasizing the tourism sector. The study data was gathered from China and The United States (US) between 2019 and 2020 (pandemic period) using the Multivariate Generalised Autoregressive Conditional Heteroscedastic-Dynamic Conditional Correlation (MGARCH-DCC) and Wavelet Coherence Transform (CWT) techniques to analyse the investment holding period. Country-wise, the sectoral return volatility in China was significantly higher than the US counterpart. Additionally, the intra-sector correlation analyses demonstrated that Chinese sectors successfully mitigated the intra-sector correction in the last quarter of 2019. A short-term holding period was also suggested for investors in China while a long-term counterpart was recommended for investors in the US. Regarding the Chinese and US industrial sectors in the first quarter of 2020, it was mutually concluded that both country stocks reflected high volatility. The tourism sector was also negatively affected throughout the pandemic period (between 2019 and 2020). Essentially, this study offered practical contributions to investors, mutual fund holders, and brokers. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

Mutual funds are designed to raise investment funds. The objectives of this study are: to determine the performance of mutual funds on the LQ-45 index is higher than the performance of equity funds in the Indonesian capital market and to measure the level of efficiency in the capital market using CAPM modeling and using Net Active Value (NAV) data per year for the 2015 period. -2019. To determine whether a mutual fund is good or bad, it is not measured by how much the return has been generated or by how big or small the risk of fluctuation is, but this is seen from how much the mutual fund performs with its reference index. If the performance of index mutual funds is better or the performance of stock mutual funds is lower overall, the capital market can be said to be efficient. The results of this study indicate that the performance of the LQ-45 index mutual funds is smaller than the performance of the more superior stock mutual funds above. So it can be concluded that the Indonesian capital market is an inefficient Indonesian capital market.

This paper extends the multiplier dynamic data envelopment analysis (DEA) by using directional distance function (DDF). Based on the duality theory, a multiplier network DDF model is proposed for the dynamic system which consists of a sequence of periods linked by carryovers. The proposed multiplier dynamic model is non-oriented and is able to handle negative data that possibly exist in inputs, carryovers and outputs. The overall efficiency score calculated by the proposed multiplier dynamic model can be decomposed into a weighted average of period efficiency scores. The approach that determines a unique efficiency score for each period is also proposed. To demonstrate the validity and practicality of the proposed dynamic model, we apply it to evaluate the performance of mutual funds in the American market. The empirical results show that the proposed multiplier dynamic model has strong ability to discriminate performance and good practice value for the actual portfolio selection.