793 research outputs found

    Data Envelopment Analysis Models of Investment Funds

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    Evaluating Greek equity funds using data envelopment analysis

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    This study assesses the relative performance of Greek equity funds employing a non-parametric method, specifically Data Envelopment Analysis (DEA). Using an original sample of cost and operational attributes we explore the e€ect of each variable on funds' operational efficiency for an oligopolistic and bank-dominated fund industry. Our results have significant implications for the investors' fund selection process since we are able to identify potential sources of inefficiencies for the funds. The most striking result is that the percentage of assets under management affects performance negatively, a conclusion which may be related to the structure of the domestic stock market. Furthermore, we provide evidence against the notion of funds' mean-variance efficiency

    New Evidence On Hedge Fund Performance Measures

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    Hedge funds are still relatively unfamiliar to most investors despite the intense popularity they have enjoyed in recent years. Measuring the performance of these financial instruments using traditional methods is, however, problematic, since their returns do not follow a normal distribution. In this study, we consider rankings obtained with the Stochastic Dominance (SD) method and compare them with ranks produced using Sharpe Ratios, Modified Sharpe Ratios, and Data Envelopment Analysis. We also explore the advantages highlighted by the literature of the Data Envelopment Analysis (DEA) method in relation to traditional measures like Sharpe ratio and Modified Sharpe ratio. Our results show that classic performance measures are better correlated with SD than DEA results

    Data envelopment analysis models of investment funds

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    This paper develops theory missing in the sizable literature that uses data envelopment analysis to construct return-risk ratios for investment funds. It explores the production possibility set of the investment funds to identify an appropriate form of returns to scale. It discusses what risk and return measures can justifiably be combined and how to deal with negative risks, and identifies suitable sets of measures. It identifies the problems of failing to deal with diversification and develops an iterative approximation procedure to deal with it. It identifies relationships between diversification, coherent measures of risk and stochastic dominance. It shows how the iterative procedure makes a practical difference using monthly returns of 30 hedge funds over the same time period. It discusses possible shortcomings of the procedure and offers directions for future research. © 2011 Elsevier B.V. All rights reserved

    Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds

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    Development and application of the data envelopment analysis (DEA) method, have been the subject of numerous reviews. In this paper, we consider the papers that apply DEA methods specifically to financial services, or which use financial services data to experiment with a newly introduced DEA model. We examine 620 papers published in journals indexed in the Web of Science database, from 1985 to April 2016. We analyse the sample applying citations network analysis. This paper investigates the DEA method and its applications in financial services. We analyse the diffusion of DEA in three sub-samples: (1) banking groups, (2) money market funds, and (3) insurance groups by identifying the main paths, that is, the main flows of the ideas underlying each area of research. This allows us to highlight the main approaches, models and efficiency types used in each research areas. No unique methodological preference emerges within these areas. Innovations in the DEA methodologies (network models, slacks based models, directional distance models and Nash bargaining game) clearly dominate recent research. For each subsample, we describe the geographical distribution of these studies, and provide some basic statistics related to the most active journals and scholars

    On the Use of Data Envelopment Analysis in Hedge Fund Performance Appraisal

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    This paper aims to show that Data Envelopment Analysis (DEA) is an efficient tool to assist investors in multiple criteria decision-making tasks like assessing hedge fund performance. DEA has the merit of offering investors the possibility to consider simultaneously multiple evaluation criteria with direct control over the priority level paid to each criterion. By addressing main methodological issues regarding the use of DEA in evaluating hedge fund performance, this paper attempts to provide investors sufficient guidelines for tailoring their own performance measure which reflect successfully their own preferences. Although these guidelines are formulated in the hedge fund context, they can also be applied to other kinds of investment funds.hedge fund, mutual fund, alternative investment, data envelopment analysis, performancemeasures, Sharpe ratio

    On the informativeness of persistence for evaluating mutual fund performance using partial frontiers

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    The last few years have witnessed a rapid evolution in the literature evaluating mutual fund performance using frontier techniques. The instruments applied, mostly DEA (Data Envelopment Analysis) and, to a lesser extent, FDH (Free Disposal Hull), are able to encompass several dimensions of performance, but they also have some disadvantages that might be preventing a wider acceptance. The recently developed order-m and order-α partial frontiers overcome some of the disadvantages (they are robust with respect to extreme values and noise, and do not suffer from the well-known curse of dimensionality) while keeping the main virtues of DEA and FDH (they are fully nonparametric). In this article we apply not only the non-convex counterpart of DEA (FDH) but also order-m and order-α partial frontiers to a sample of US mutual funds. The results obtained for both order-m and order-α are useful, since a full ranking of the mutual funds' performance can be obtained. We merge these methods with the literature on mutual fund performance persistence. By combining the two literatures we derive an algorithm which establishes how the choice of m and α parameters intrinsic to order-m and order-α (respectively) relate to the existence of performance persistence and the contrarian effect

    Resampling DEA estimates of investment fund performance

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    Data envelopment analysis (DEA) is attractive for comparing investment funds because it handles different characteristics of fund distribution and gives a way to rank funds. There is substantial literature applying DEA to funds, based on the time series of funds' returns. This article looks at the issue of uncertainty in the resulting DEA efficiency estimates, investigating consistency and bias. It uses the bootstrap to develop stochastic DEA models for funds, derive confidence intervals and develop techniques to compare and rank funds and represent the ranking. It investigates how to deal with autocorrelation in the time series and considers models that deal with correlation in the funds' returns. © 2012 Elsevier B.V. All rights reserved

    On the informativeness of persistence for mutual funds' performance evaluation using partial frontiers

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    The last few years have witnessed a rapid evolution in the literature evaluating mutual fund performance using frontier techniques. The instruments applied, mostly DEA (Data Envelopment Analysis) and, to a lesser extent, FDH (Free Disposal Hull), are able to encompass several dimensions of performance, but they also have some disadvantages that might be preventing a wider acceptance. The recently developed order-m and order-a partial frontiers overcome some of the disadvantages (they are robust with respect to extreme values and noise, and do not suffer from the well-known curse of dimensionality) while keeping the main virtues of DEA and FDH (they are fully-nonparametric). In this article we apply not only the non-convex counterpart of DEA, namely, FDH but also order-m and order-a partial frontiers to a sample of Spanish mutual funds. The results obtained for both order-m and order-a are useful, since a full ranking of mutual funds’ performance is obtained. We combine these methods with the literature on mutual fund performance persistence. By combining the two literatures we derive an algorithm for guiding the choice of m and a parameters intrinsic to order-m and order-a (respectively) based on mutual fund performance persistence. Los Ășltimos años han sido testigos de una rĂĄpida evoluciĂłn de la literatura que evalĂșa el rendimiento de fondos de inversiĂłn utilizando la metodologĂ­a del enfoque frontera. Los instrumentos aplicados, principalmente DEA (Data Envelopment Analysis) y, en menor medida, FDH (Free Disposable Hull), son capaces de abarcar varios aspectos del rendimiento, pero tambiĂ©n poseen algunas desventajas que podrĂ­an impedir una mayor aceptaciĂłn. El recientemente desarrollado enfoque de las fronteras parciales de orden-m y de orden-alfa supera algunos de los inconvenientes (estos procedimientos son robustos con respecto a los valores extremos y perturbaciones aleatorias o ruido, y no sufren la conocida “maldiciĂłn de la dimensionalidad” o curse of dimensionality), manteniendo las principales virtudes de DEA y FDH (ambas tĂ©cnicas son absolutamente no paramĂ©tricas). En este artĂ­culo se aplica no sĂłlo la versiĂłn no convexa de DEA, es decir, FDH, sino tambiĂ©n para fronteras de orden-m y de orden-alfa cuya utilidad es notable, ya que se obtiene una clasificaciĂłn completa del rendimiento de los fondos de inversiĂłn. En este trabajo se combinan estos mĂ©todos con la literatura existente relativa a la persistencia en el rendimiento de los fondos de inversiĂłn. Mediante la combinaciĂłn de ambas literaturas deducimos un algoritmo capaz de guiar (o que sirva de referencia) en la elecciĂłn de los parĂĄmetros intrĂ­nsecos m y alfa correspondientes a orden-m y a orden-alfa (respectivamente) en base a la persistencia en el rendimiento de los fondos de inversiĂłn.eficiencia, fondos de inversiĂłn, enfoque de fronteras parciales, persistencia. efficiency, mutual funds, partial frontiers, persistence.

    DEA investment strategy in the Brazilian stock market

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    This paper presents a multi-period investment strategy using Data Envelopment Analysis (DEA) in the Brazilian stock market. Results show that the returns based on the DEA strategy were superior to the returns of a Brazilian stock index in most of the 22 quarters analyzed, presenting a significant Jensen's alpha.
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