2016
DOI: 10.1016/j.omega.2015.07.007
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Modeling leakage in two-stage DEA models: An application to US mutual fund families

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Cited by 33 publications
(18 citation statements)
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“…The overall efficiency of a mutual fund can be conceptualized into two components: decision quality efficiency and capital magnet efficiency. The two‐stage concept presented in Figure comports with the literature (e.g., Galagedera et al, ; Premachandra et al, ), with a particular focus on window time effects in this study. The first stage discusses decision quality efficiency, particularly (a) a fund manager's ability to select shares for either short‐term or long‐term investments via buying and selling turnover ratios, which represent the number of transactions, and (b) how decisions are made to determine whether a fund can obtain excess returns from expenses, namely, management fees ratio and transaction costs ratio.…”
Section: Methodsmentioning
confidence: 77%
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“…The overall efficiency of a mutual fund can be conceptualized into two components: decision quality efficiency and capital magnet efficiency. The two‐stage concept presented in Figure comports with the literature (e.g., Galagedera et al, ; Premachandra et al, ), with a particular focus on window time effects in this study. The first stage discusses decision quality efficiency, particularly (a) a fund manager's ability to select shares for either short‐term or long‐term investments via buying and selling turnover ratios, which represent the number of transactions, and (b) how decisions are made to determine whether a fund can obtain excess returns from expenses, namely, management fees ratio and transaction costs ratio.…”
Section: Methodsmentioning
confidence: 77%
“…Similarly, Galagedera et al () inserted a new dimension to the two‐stage model of Premachandra et al () by adding total cash flow to investors as the output of the first‐stage efficiency, thereby increasing the model's discriminatory power. They showed that small fund families tend to perform better than their bigger counterparts.…”
Section: Mutual Fund Performance Evaluationmentioning
confidence: 99%
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“…While radial models assume that input reductions and output expansions change proportionally (Seiford & Zhu, 1999;Lewis & Sexton, 2004;Castelli, Pesenti, & Ukovich, 2010;Yang & Liu, 2012;Kao, Wu, & Huang, 2017;Marchetti & Wanke, 2017), non-radial models are a more flexible evaluation tool that can compute input contractions and output improvements individually (Yu & Lin, 2008;Barros, Managi, & Matousek, 2012;Xu & Cui, 2017). Furthermore, given that slacks have been recognized as important factors in explaining inefficient behavior (Mahlberg & Sahoo, 2011), a network slacks-based measure (NSBM) model proposed by Tone and Tsutsui (2009) has been widely used for performance evaluation in various industries (Avkiran, 2009;Yu, 2010;Galagedera, Watson, Premachandra, & Chen, 2016;Zha, Liang, Wu, & Bian, 2016;Xu & Cui, 2017).…”
Section: Introductionmentioning
confidence: 99%
“…Based on the production technology and following Galagedera et al (2016) we can calculate an approximation of the input distance function as the reciprocal of the Farrell technical efficiency(Färe et al, 1992b). It must be noted that our proposed distance function and the distance function ofGalagedera et al (2016) are approximations of the input distance function proposed byFäre et al (1992b). InGalagedera et al (2016) model (B.2), the component (1 − 0 ) 0 at the third constraint does not allow for proportional reductions of all intermediate variables.…”
mentioning
confidence: 98%