In this paper, we apply a nonlinear methodology (Self-Organizing Maps and k-means algorithm) to classify mutual funds. This methodology allows us to identify which mutual funds did not follow the investment objectives established from its official category. We also propose an alternative classification, which has a lower rate of misclassified mutual fund. It achieves better performances in term...

H alf of all of U.S. households own shares in one or more mutual funds, either directly or through personal or employer-sponsored retirement accounts. The growth in mutual fund investment has been dramatic. At the end of World War II, there were 73 mutual funds registered with the Securities and Exchange Commission holding $1.2 billion in assets (Investment Company Institute, 2003). By the end ...

T his study is the second in a two-part analysis of the mutual fund industry. The first part (Fortune 1997, referred to here as " Part I ") examined the basic structure of the industry and discussed the historical relationship between mutual fund flows and returns on both short-term and long-term financial instruments. That study ended with a discussion of the role that momentum investing by mu...

We document a curious feature of the German mutual fund industry. Unlike U.S. mutual funds, funds domiciled in Germany do not necessarily compute their net asset values (NAV) as of market close. Using a sample of German equity funds, we infer each fund’s NAV closing time from the best-fit market model using both maximum likelihood and Bayesian estimation. The results of both approaches coincide...

This paper examines the interaction of idiosyncratic risk, liquidity and return across time in determining fund performance, as well as across investment style portfolios of European mutual funds. This study utilizes a unique data set including returns for equity mutual funds registered in six European countries. Overall, using monthly data, we find that both liquidity and idiosyncratic risk ar...

This paper proposes two quadratic-constrained DEA models for evaluation of mutual funds performance, from a perspective of evaluation based on endogenous benchmarks. In comparison to previous studies, this paper decomposes two vital factors for mutual funds performance, i.e. risk and return, in order to define mutual funds’ endogenous benchmarks and give insights and suggestions for managements...

Mutual funds are usually classified based on their stated objectives. If the stated objectives are not the actual objectives the funds pursue, conclusions drawn by investors and researchers based on the stated objectives will be misleading. This study classifies funds based on their attributes (characteristics, investment style, and risk/return measures). We find that the stated objectives of m...

Mutual fund investors are concerned with the selection of the best fund in terms of performance among the set of alternative funds. This paper proposes an innovative mutual funds performance evaluation measure in the context of multicriteria decision making. We implement a multicriteria methodology using stochastic multicriteria acceptability analysis, on Greek domestic equity funds for the per...

Mutual fund sectors are one of the fastest growing sectors in Indian economy that have potential for sustained future growth. Mutual funds make saving and investing simple and affordable. Anybody with an investible surplus of as little as a few hundred rupees can invest in mutual funds. The Indian Mutual Fund industry has already opened up many exciting investment opportunities to Indian invest...