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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 uncertainty as to whether investments in riskier and less efficient markets allow managers to ‘beat the market’ remains a question to which answers are required. Accordingly, the purpose of this chapter is to offer new insights on portfolios of the US, European and Emerging Market (‘EM’) domiciled equity mutual funds whose objectives are the investment in emerging economies, and specifically analyses two main issues: alpha generation and the influence of the funds’ characteristics on their risk-adjusted performance.

The dataset is made up a survivorship-bias controlled sample of 137 equity funds over the period January 2004 to December 2014, which are then grouped into equally weighted portfolios according to the scheme’s origin. The Jensen’s (1968) Single-Factor model along with the Fama and French’s (1993) and Carhart’s (1997) multifactor models are employed to authenticate results and answer both research questions.

Research analysis reveals that EM exposed fund managers fail to collectively outperform the market. It thereby offers ground to believe that the emerging world is very close to being efficient, proving that the Efficient Market Hypothesis (‘EMH’) ideal exists in this scenario where market inefficiency might only be a perception of market participants as any apparent opportunity to achieve above-average returns is speedily snapped up by very active managers. Overall these managers take a conservative approach to portfolio construction, whereby they are more unperturbed investing in large cap equity funds so as to lessen somewhat the exposure towards risks associated with liquidity, stability and volatility.

Furthermore, the findings show that large-sized equity portfolios have the lead over the medium and small-sized competitors, whilst the high cost and mature collective investment vehicles enjoy an alpha which although is negative is superior to their peers. The riskiest funds generated the lowest alpha, and thereby produced doubts as to whether investors should accept a higher risk for the hope of earning higher returns, at least when aiming to gain an exposure into the emerging world.

Mutual fund performance is not an innovative topic so to speak. Nonetheless, researchers and academia have centred their efforts on appraising the behaviour of fund managers domiciled primarily in developed and more efficient economics, leaving the emerging region highly uncovered in this respect. This study, therefore aims at crafting meaningful contributions to the literature as well as to the practical perspective.

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 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.