Mutual fund performance: The decision quality and capital magnet efficiencies

Hsieh, Hong-Po; Tebourbi, Imen; Lu, Wen‐Min; Liu, Nai‐Yu

doi:10.1002/mde.3143

Cited by 6 publications

(4 citation statements)

References 63 publications

(78 reference statements)

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“…In contrast to the single DEA black box model, a two-stage DEA model identifies sub-processes and aims at measuring their efficiency (Kao 2014). In this strand lie the studies of Premachandra et al (2012), Galagedera et al (2016, 2018), Sánchez-González et al (2017, Galagedera (2018), and Hsieh et al (2020. Premachandra et al (2012) first introduced a series two-stage modeling for mutual fund performance evaluation considering operational and portfolio process.…”

Section: Survey Of Dea-based Mutual Fund Performance Evaluationmentioning

confidence: 99%

“…Galagedera (2019) modeled social responsibility in mutual fund performance appraisal by means of a two-stage DEA using non-discretionary first stage output. In a recent study, Hsieh et al (2020) employed a window two-stage DEA approach to assess the performance of mutual funds registered in Taiwan.…”

Section: Survey Of Dea-based Mutual Fund Performance Evaluationmentioning

confidence: 99%

“…These works employ single stage DEA that does not reflect the internal structure of funds. Exceptions are the research by Premachandra et al (2012) and the studies followed by Galagedera et al (2016, 2018), Sánchez-González et al (2017, Galagedera (2018), and Hsieh et al (2020.…”

Section: Introductionmentioning

confidence: 99%

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Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach

Tsolas

2020

JRFM

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This paper documents a new series two-stage data envelopment analysis (DEA) modeling framework for mutual fund performance evaluation in terms of operational and portfolio management efficiency that is implemented to a sample of precious metal mutual funds (PMMFs). In the first and second stage, one-input/one-output and multi-input/one-output settings are used, respectively. In the light of the results, the funds assessed are inefficient in both operational and portfolio management process and in particular, they seem to be more inefficiently operated. The operational management efficiency is correlated with portfolio management efficiency and, therefore, sample funds should give more emphasis on their operational policies to ensure their success in the industry. The research framework may not only benefit PMMFs, but also funds of other classes to quantify their performance and improve their competitive advantages.

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Section: Survey Of Dea-based Mutual Fund Performance Evaluationmentioning

confidence: 99%

Section: Survey Of Dea-based Mutual Fund Performance Evaluationmentioning

confidence: 99%

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Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach

Tsolas

2020

JRFM

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“…A number of works that followed Premachandra et al (2012) lie in this research strand. Recent contributions to this type of DEA modeling on fund performance evaluation are the works by Galagedera (2018Galagedera ( , 2019, Hsieh et al (2020), andTsolas (2020).…”

Section: Literature Reviewmentioning

confidence: 99%

The Determinants of the Performance of Precious Metal Mutual Funds

Tsolas

2020

JRFM

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The aim of this paper is to assess the efficiency of a set of 62 precious metal mutual funds (PMMFs) and to explain performance differences between funds using weighted additive data envelopment analysis (DEA) and Tobit regression, respectively. The contribution of this paper is twofold: to provide for the first-time metrics of the relative performance of PMMFs using a particular weighted additive model, namely the range-adjusted measure (RAM), and to explain the performance of the funds by the use of a Tobit model. Results do not suggest positive linkages between RAM-based and standard fund performance metrics (Sharpe ratio and Jensen’s alpha). Moreover, for the sample inefficient funds the mean–variance performance hypothesis does not hold. In addition, fund performance based on RAM can be explained by the persistence of the fund and the beta coefficient.

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A novel robust network data envelopment analysis approach for performance assessment of mutual funds under uncertainty

et al. 2022

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Mutual fund (MF) is one of the applicable and popular tools in investment market. The aim of this paper is to propose an approach for performance evaluation of mutual fund by considering internal structure and financial data uncertainty. To reach this goal, the robust network data envelopment analysis (RNDEA) is presented for extended two-stage structure. In the RNDEA method, leader–follower (non-cooperative game) and robust optimization approaches are applied in order to modeling network data envelopment analysis (NDEA) and dealing with uncertainty, respectively. The proposed RNDEA approach is implemented for performance assessment of 15 mutual funds. Illustrative results show that presented method is applicable and effective for performance evaluation and ranking of MFs in the presence of uncertain data. Also, the results reveal that the discriminatory power of robust NDEA approach is more than the discriminatory power of deterministic NDEA models.

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Mutual fund performance: The decision quality and capital magnet efficiencies

Cited by 6 publications

References 63 publications

Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach

Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach

The Determinants of the Performance of Precious Metal Mutual Funds

A novel robust network data envelopment analysis approach for performance assessment of mutual funds under uncertainty

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