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The purpose of this study is to evaluate the performance of mutual funds during the COVID-19 pandemic with environmental, social and governance (ESG) criteria. The main research question is whether mutual fund performance differs with respect to the level of the mutual fund’s ESG score.

The data set contains global fund data, and mutual fund performance is analyzed using two types of data envelopment analysis (DEA) models: the DEA portfolio index (DPEI) and the range direction measure (RDM) DEA. Propensity score matching and logistic regression are also applied.

The results reveal that: nonequity mutual funds present significantly higher performance compared to the performance of equity mutual funds; mutual funds with high ESG scores are associated with significantly higher performance compared to those with low to medium ESG scores; funds with high ESG scores experience higher performance irrespective of their type; and efficiency scores derived from the RDM DEA are significantly higher than those derived from the DPEI model.

Investors, fund managers and market participants can benefit from the findings of this study and improve their investment decision-making process, including more sustainable funds in their portfolios. Regulators and policymakers should further promote or even require the inclusion of more sustainable investments in the financial products offered by institutional investors. The main limitation of the study is related to data availability regarding the ESG score of mutual funds.

To the best of the authors’ knowledge, this is the first study that provides robust evidence in support of a positive association between ESG scores and mutual fund performance during the pandemic-induced crisis applying a DEA methodology.

Outlines previous research on measuring the performance of investment funds, suggesting that data envelopment analysis (DEA) techniques can overcome some of the problems of the capital asset pricing model and give pointers for improvement. Uses DEA to assess the relative performance of 257 Australian mutual funds 1995‐1999 and logistic regression to investigate the characteristics which affect it. Describes the methodology and presents the results, which suggest that scale efficiency is the main source of overall technical efficiency and that both are higher for risk‐averse funds with high positive net asset flows. Explains the ASSIRT rating system for managed funds and finds the ratings strongly associated with DEA relative efficiency scores. Believes the findings are useful to analysts, investors and managers.

The purpose of this paper is to estimate the performance of 188 mutual funds relative to the risk/return frontier accounting for the transaction costs of producing a portfolio of investments.

The directional output distance function is used to estimate mutual fund performance. The method allows the data to define a frontier of return and risk accounting for the transaction costs associated with securities management and production of risky returns. Proxies for the transaction costs of producing a portfolio of securities include the turnover ratio, load, expense ratio, and net asset value. The estimates of mutual fund performance are bootstrapped to account for the unknown data generating process. By comparing each mutual fund’s performance relative to the capital market line the authors determine how the fund should adjust their portfolio in regard to risk and return in order to maximize the inefficiency adjusted Sharpe ratio.

The bootstrapped estimates indicate that the average mutual fund could simultaneously expand return and contract risk by 3.2 percent if it were to operate on the efficient frontier. After projecting each mutual fund’s return and risk to the efficient frontier the authors find that a majority of the mutual funds should reduce risk to be consistent with the capital market line.

Many researchers have used data envelopment analysis to estimate a piecewise linear frontier of risk and return to measure mutual fund performance. To the authors’ knowledge the research is the first to use a twice-differentiable quadratic directional distance function to measure the managerial performance and risk/return tradeoff of mutual funds.

The main purpose of this study is to use the Sharpe Ratio to test the efficient market hypothesis for different market capitalization and investment styles of mutual funds. The results of the study for the entire period of 1994‐2007 as well as the two subperiods (1994‐1999 and 2000‐2007) indicate that small cap funds have provided the highest risk‐adjusted return for the entire period whereas growth funds have exhibited lower returns. The findings, therefore, suggest that the mutual funds market is not always efficient, which makes it possible for an investor or a mutual fund manager to earn excess return on a risk‐adjusted basis.

The purpose of this paper is to investigate the impact of investor confidence on mutual fund performance in two relatively vulnerable but leading emerging markets, India and Pakistan.

A pooled ordinary least squared (OLS) model is used to look at two alternative measures of investor confidence and test for the relationship between investor confidence and mutual fund returns. To check the robustness of the findings, the authors also implement two-stage least squares and generalized method of moments techniques to control for unobserved heterogeneity, simultaneity and dynamic endogeneity problems in the regressors.

The paper finds that the returns of mutual funds are positively associated with investor confidence and an interaction effect exists between investor confidence and persistence in performance. The paper also confirms that returns from mutual funds are associated with different fund characteristics such as fund size, turnover, expense, liquidity, performance persistence and the fund’s age. These findings remain robust to alternative model specifications and measures of investor confidence.

While the previous literature mainly focuses on mutual fund characteristics and the macroeconomic determinants of mutual fund returns, this paper demonstrates that investor confidence plays an important role in determining mutual fund performance. The authors attribute this finding to two relatively unique features of the emerging markets in the study. A lack of awareness of mutual funds as being a low-cost investment vehicle and the interplay of cultural and behavioral changes have prevented investor’s savings from being channeled into investment products, away from gold or property.

The purpose of this paper is to measure efficiency of superannuation funds using data envelopment analysis (DEA), using data related to financial performance of superannuation funds. The sample comprises 183 superannuation funds covering approximately 79 per cent of the 231 largest Australian Prudential Regulation Authority (APRA)-regulated funds in 2012. The research covers a period of seven years from 2005 to 2012. The results indicate that most Australian superannuation funds are inefficient relative to the benchmark efficiency frontier based on efficient funds. The findings emphasise the importance of improving the efficiency of Australian superannuation funds by reducing overall fund expenses to narrow the gap in performance between efficient and inefficient funds.

This study aims to contribute to policy, theory and practice in several dimensions. Member protection and the efficiency of the superannuation system are topical issues (Donald, 2009). Despite its importance from a regulatory point of view, efficiency has only been discussed in relation to operational issues such as managing agency relationships, fees and charges, investment return or economies of scale. The relative efficiency of the Australian superannuation system from an economic productivity perspective has rarely been examined, except for a study by Njie (2006), where the Malmquist productivity DEA technique was used to measure the efficiency of Australia’s retirement income system.

Most inefficient funds had very low efficiency scores and were fell into the lower quintiles such as Quintiles 4 (scored 0.200-0.399) and 5 (scored 0.001-0.199). Consequently, input reduction targets were significantly higher for these two quintiles. Similarly, input reduction targets were high under the period DEA estimates. In order to be comparatively efficient, Quintile 4 funds were required to reduce total expenses by 75 per cent (−0.754) and volatility of return by 80 per cent (−0.801). Similarly, Quintile 5 funds needed to reduce total expenses by, on average, 83 per cent (−0.824) and volatility of return by 89 per cent (−0.894).

As in other empirical research, this study also depended heavily on the data collected from the secondary sources such as APRA database and other financial reports. The issues of measurement errors in data sources such as APRA database are well documented (see, e.g. Cummins, 2012). This issue needs the attention of future research on the efficiency of superannuation funds.

The findings on individual year DEA estimates indicate that most funds were inefficient due to high expenses. Therefore, mandatory disclosure of fees and charges in a comparable manner may be necessary to justify fee payments and to address transparency and accountability issues, which are critical issues identified by the Cooper Review and the academic literature (Australian Government, 2014; Cooper et al., 2010; Gallery and Gallery, 2006).

The issue of Australian superannuation funds concentrating the majority of fund assets in highly volatile investment vehicles such as the share markets has been in the spotlight in the aftermath of the global financial crisis. There have been proposals to better diversify superannuation assets in other asset classes (Cooper et al., 2010).

This study contributes to the current literature on superannuation funds by investigating efficiency. As efficiency studies using DEA have not been conducted on the Australian superannuation industry, this study also contributes to the academic literature on DEA and its extensive applications to various economic sectors. Efficiency scores using DEA, ranking, trends and shifts in the efficiency frontiers could be obtained for Australian superannuation funds on an on-going or annual basis.

The purpose of this paper is to consider compromise solutions of multiple attribute decision-making methods (TOPSIS, VIKOR, and similarity-based approach) in order to evaluate and rank mutual funds and to compare the capabilities of different approaches based on the different traditional indices of mutual funds assessment. In addition, a new algorithm for ranking mutual funds was proposed subsequently.

In this research, three groups of indices including general, risk-modified performance evaluation, and risk-modified performance evaluation indices using semivariance were used in the mutual funds assessment, which led to the comparison between selected mutual funds, using three mentioned methods and three different groups of criteria. The results of this comparison were compiled and synthesized with linear assignment method. At the end, an algorithm for decision making and investing in mutual funds for professional and unprofessional investors was proposed.

Using different methods and different criteria proved that the results of similarity-based approach as a MADM technique have the ability to rank and evaluate mutual funds regardless of the criteria used compared to TOPSIS and VIKOR. Furthermore, the authors propose the algorithm of this research as a new model of mutual funds evaluation which considers a wide range of variables with respect to amateur and professional points of view.

The originality of this paper is threefold: first, different criteria were considered to make the evaluation more comprehensive. Second, four different approaches were used to make the results more authentic. Third, a holistic algorithm with its implication was proposed.

The main goal of this paper is better understand the risk/return trade-off of investing in socially responsible investment funds (SRIF) and green investment funds (GIF).

To achieve our aim a green investment fund portfolio, a socially responsible investment portfolio and a conventional fund (CF) portfolio from the United States of America (USA) were selected to compare the efficiency of these three different portfolios, by using Value-Based Data Envelopment Analysis (DEA) methodology.

The results point out that SRIF and GIF are more efficient than CF. For five years, the CFs have not outperformed the GIF.

The results suggest that there is a growing awareness on the part of investors that sustainable companies are the companies that will allow a better quality of life and a more sustainable environment. It seems that somehow managers and investors are aware that the market will compensate them for thinking about a cleaner and more equitable world.

This paper seeks to evaluate the risk‐adjusted performance of the largest US‐based equity mutual funds using rigorous analysis grounded in modern portfolio theory and present the results in a manner which is comprehensible to a lay investor.

This study evaluates the performance of the 20 largest US‐based mutual funds using risk‐adjusted returns during 1995‐2004. In particular, a relatively new risk‐adjusted performance measure by Modigliani and Modigliani is used to evaluate these equity funds. This study also utilizes a variation of the Sortino Ratio to account for downside risk.

The results show that the funds with the highest returns may lose their attractiveness once the degree of risk had been factored into the analysis. Conversely, some funds may look very attractive once their low risk is factored into their performance.

Future researchers may want to investigate the effects of factors, such as fund manager, compensation, service fees, corporate governance metrics, and overweighting in risky industries on the performance of mutual funds.

The empirical evidence presented in this study can be used as input in decision making by investors who are exploring the possibility of participating in the stock market via large mutual funds, but are not sure of what selection criteria to employ.

The paper is one of the first studies that apply the new M² measure to evaluate the performance of mutual funds. Various other performance metrics are also utilized including the Sharpe, Sortino, Treynor measures and Jensen's α.

The purpose of this paper is to measure the effectiveness of the integration of Europe by benchmarking economic progress made by the participating nations.

Using data envelopment analysis, this paper compares the relative performance of 26 European Union (EU) nations against one another with seven economic variables as the benchmark parameters from 1999 to 2006.

The paper finds that not all the participating nations were equally efficient at the beginning of the economic integration in 1999. Economic integration does help in achieving convergence in economic performance of 26 EU nations, because 18 of the 26 nations were efficient in 2002. However, this paper finds that after 2002, there is a lack of convergence in the performance of 26 EU nations and some nations have performed more efficiently in contrast to other nations.

The paper identifies the member nations that are lagging behind and make recommendations as to how they can improve their performance to bring them at par with other participating nations.