Mutual fund investors, both individuals and corporations, are really hiring an administrator to handle their life savings or their excess liquidity. Consequently, they should strive to pick a good fund manager. Unfortunately, most individual investors devote more time to the decision-making process for the purchase of certain consumption goods (tv sets, stereos, cars, bicycles, laptops) than to the selection of mutual funds. Investors should take the time and the effort to do the required research and select performing funds with consistent above-average returns in their own class.

Investing in stock markets through mutual funds has some important advantages for investors. Mutual fund investment facilitates investors achieving higher diversification than they can achieve on their own. Also, mutual funds allow savers to invest in businesses and industries that are outside their area of expertise by hiring qualified and specialized fund managers. In addition, many mutual funds have a long track record, and they are relatively easy to compare.

When selecting a mutual fund for investment, investors and financial advisors face a difficult decision. Investors must handle a wide range of both quantitative and qualitative fund data (such as risk, past financial performance, investment style, fund manager skill, fund manager rating, fund manager tenure, or expense ratios) and then decide which relevant variables they should be focusing on. Therefore, many investors and advisors may find it quite challenging monitoring a large number of variables and deciding the leverage of each variable in their final investment decision.

Investors choosing managed mutual funds expect active managers to have a persisting edge and obtain better results than when a passive management strategy is pursued. Index funds and managed funds differ in their investment approach and fee structure. Index funds replicate a specific stock market index by investing in a set of securities that mirror the index’s composition. Alternatively, managed funds have investment managers who actively select and manage the securities for the fund’s portfolio. Active fund management often leads to higher management fees and higher trading costs than index funds.

The mutual fund manager plays a crucial role in making investment decisions, constructing the fund’s portfolio, and managing its assets. An active fund manager is responsible for making investment decisions, including selecting securities, asset allocation, and timing of buys and sells.

The manager’s ability to identify attractive investment opportunities and manage risk can influence the fund’s performance. A manager’s skill in selecting individual securities within the fund can significantly impact returns. Their research and analysis capabilities are essential in identifying investments that have the potential to outperform the market.

Matallín-Sáez et al. ^[2] conducted a study analyzing the connection between active management and the results achieved in American equity mutual funds. They found a U-shaped relationship, indicating that both the best and worst performing funds had active management. Active management involves selecting different strategies or investment bets that can lead to either a positive or negative abnormal performance; however, it also comes with higher expenses. Only a few active managers have the ability to add excess returns to a portfolio above their funds’ benchmarks on a regular basis. According to ^[2], significant evidence of managed fund performance is only found for the top decile performing funds.

Livingston et al. ^[3] discovered a significant level of active management intensifies the performance extremes. Mutual funds with elevated expense ratios and turnover rates displayed increased volatility and lower average performance. This suggests that mutual funds with more active management, higher expenses, and higher turnover ratios carry greater risk.

Tosun et al. ^[4] found that fund managers have an asymmetric ability when buying and selling stocks. In addition, they revealed that fund managers with superior selling ability are significantly better at buying stocks and, as a result, earn significantly higher aggregate returns. However, fund managers who buy stocks successfully do not necessarily have parallel selling skills, leading to lower returns overall. They conclude that selling skill is the key determinant of overall mutual fund timing performance.

The examination of the link between manager characteristics and managerial competence, as measured by Carhart’s four-factor model Alpha, reveals a positive correlation between accumulated experience and managerial skill ^[5]. To elaborate, managers with longer tenures tend to have more experience, and all else being equal, older managers often achieve superior performance.

When it comes to the readability of investment fund reports and its impact on investor decisions, Losada ^[6] conducted research on how the information provided in prospectuses and quarterly reports influences investors’ decisions to buy or sell funds. The results suggested that the comprehensibility of the investment policy texts has no impact on investors’ choices regarding subscriptions and redemptions.

Regarding the fund selection process by financial advisors, a study by Jones et al. ^[7] identified several fund characteristics that financial advisors consider when recommending mutual funds. The findings indicate that financial advisors give preference to unbiased information sources like extensive data repositories and impartial rankings as opposed to relying on fund promotion and widely circulated press releases. Effective financial advisors place higher significance on a fund’s performance compared to other funds with similar characteristics, including style, risk, and the tenure of the fund manager. They also consider sales loads and fees to a lesser extent.

According to Agarwal et al. ^[8], funds can add value through the advantages of asymmetric information and the skills of the fund manager, resulting in positive returns. This implies that fund managers who possess unique information or expertise can generate favorable investment outcomes.

Daniel et al. ^[9] demonstrated that mutual funds exhibit some level of selectivity ability. This suggests that fund managers have the potential to identify and invest in securities that outperform the market or other comparable investments.

Fund ratings serve as a means of evaluating mutual funds. Chen et al. ^[10] mentions that for ratings to be useful and valid, they should reflect fund performance. Two studies [11,12]^[11][12] have assessed the predictive accuracy of well-established mutual fund evaluation systems in the United States market. Morningstar’s qualitative and quantitative ratings are investment grading tools widely utilized by both investors and managers ^[13]. Morningstar’s ratings provide an additional perspective on evaluating fund performance.

The use of fuzzy-set qualitative comparative analysis (fsQCA) in the study adds to the body of knowledge concerning the elements influencing the performance of mutual funds ^[14]. FsQCA is a comparative approach rooted in set theory for the detection of causal patterns within an empirical dataset, accounting for complex and non-linear relationships. By employing fsQCA, researchers can gain a deeper understanding of the complex causal relationships and factors that influence mutual fund performance, complementing traditional approaches such as regression analysis.

Mutual fund performance evaluation has long been a focal point in finance research. The classic regression approach to fund performance would facilitate the identification of independent factors that lead to performing funds. However, the complexity of factors influencing mutual fund performance requires a methodological approach capable of capturing the intricate inter-relationships. Fuzzy-set qualitative comparative analysis (fsQCA) is a methodology that combines set theory and fuzzy logic techniques to analyze complex causal relationships. Unlike traditional statistical methods, fsQCA can handle limited sample sizes, non-linear associations, and interaction effects. It is particularly suited for investigating mutual fund performance, as it allows for a holistic examination of multiple factors and their combinations.

Graham et al. ^[15] describe an instance of utilizing fuzzy-set qualitative comparative analysis (fsQCA) to outline the circumstances that result in either superior or inferior performance of mutual funds that invest in large-capitalization US equities or large-capitalization Eurozone equities. The findings indicate that, on average, mutual funds need to have favorable Morningstar and analyst ratings to create value based on the Jensen’s Alpha ratio. Similarly, larger funds with superior Morningstar ratings are linked to enhanced Sharpe ratios and improved returns, especially when the fund manager tenure is rather short. Graham et al. ^[16] compares mutual funds in Europe and the United States and examines the factors that contribute to the underperformance or outperformance of mutual funds compared to their peers. Employing fuzzy-set qualitative comparative analysis, they leverage extensive research on fund returns to validate and build upon previous findings. To generate value, it is essential for funds to have positive Morningstar ratings and analyst endorsements. Additionally, funds with minimal management and ongoing fees tend to exhibit favorable Sharpe ratios and higher returns. Similarly, larger funds with strong Morningstar ratings tend to have good Sharpe ratios and returns, particularly when fund managers have relatively brief tenures. In a paper focused on ESG (Environmental, Social, and Governance) rated funds, Welling and Stoklasa ^[17] analyze the possible drivers of high performance of European ESG funds. They examine the commonly presumed connections between a fund’s sustainability and its performance, establishing hypotheses to be explored through the fsQCA approach. The findings suggest that, while displaying strong performance, is not distinctly linked to a high sustainability rating, a high sustainability rating appears to act as a safeguard against poor fund performance. Finally, Kumar et al. ^[18] explores the principal contributors and the knowledge framework in business and management research that utilizes complexity theory and fuzzy-set qualitative comparative analysis. It serves as a valuable reference for obtaining a thorough comprehension of the current status and potential directions for future research in predicting business-related phenomena through the application of complexity theory and fsQCA. Manager skill and fund size relate to fund performance in the following opposite ways: while manager skill is positively associated with high performance, fund size is negatively related to fund performance. Skilled fund managers should be able to take advantage of financial market inefficiencies, and with the appropriate investment strategies, they can outperform their funds’ benchmarks on a regular basis. The lower the market efficiency, the more likely the active manager will achieve a persistent edge over the fund benchmark. Some successful funds grow so large that their size harms performance as managers have more funds available for investment than worthy investment opportunities to match them. Likewise, managing large cash inflows (fund subscriptions) and outflows (fund redemptions) makes a manager’s job more complex, and it may have a bad effect on fund return. Other relevant factors that complete each of the three successful recipes leading to performing funds are sustainability (ESG score), agency rating (MS stars), and the sensitivity of fund performance to changes in benchmark performance (Beta). All three factors are positively related to fund performance, and each of them is forming one separate recipe combined with the following two pervasive factors: manager skill and fund size. With regard to sustainability (ESG score), socially responsible investors can select mutual funds that align with their personal values for sustainability without sacrificing financial performance. Then, concerning the agency rating (MS stars), Morningstar’s rating system seems to have a relevant explanatory capacity for fund performance. Finally, the sensitivity of fund performance to changes in benchmark performance (Beta) shows that high Beta values involve higher volatility because any ups and downs in benchmark performance result in amplified changes in fund performance. All in all, investors and financial advisors can save the time and effort required to monitor a large number of variables. They would just need to focus on five variables and on any of the three successful combinations provided by the fsQCA model, avoiding the loss of focus that results from handling a large number of factors. Special attention should be devoted to the following two prevailing factors: manager skill and fund size.