scholarly journals A multi-criteria decision-making approach to performance evaluation of mutual funds: A case study in Serbia

2018 ◽  
Vol 28 (3) ◽  
pp. 385-414 ◽  
Author(s):  
Milena Jaksic ◽  
Predrag Mimovic ◽  
Miljan Lekovic
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Mutual Funds ◽  
Complex Problem ◽  
Multi Criteria Decision Making ◽  
Absolute Efficiency ◽  
Portfolio Managers ◽  
The Republic ◽  
Traditional Approaches

In this paper we evaluate the performance of nine mutual funds in the Republic of Serbia in the period 2011-2013 by integrating traditional approaches for measuring absolute efficiency and the selected multi-criteria decision-making methods for measuring relative efficiency. The aim of our research is to test selection abilities of Serbian portfolio managers. Performance evaluation of mutual funds, being by its nature a complex problem of multi-criteria decision-making, must be solved by the methods that have, at least, the same level of complexity. Research results indicate that mutual funds have inferior performance, which on the other hand, confirms that the national portfolio managers lack selection abilities.

Robust Benchmarking of Indian Mutual Funds-A Partial Frontier Approach

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Ram Pratap Sinha
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Mutual Funds ◽  
Mutual Fund ◽  
Multi Criteria Decision Making ◽  
Risk Framework ◽  
Programming Techniques ◽  
Risk Free Rate ◽  
Risk Ratios ◽  
Free Rate

Performance analysis of mutual funds is usually made on the basis of return-risk framework. Traditionally, excess return (over risk-free rate) to risk ratios were used for the purpose mutual fund evaluation. Subsequently, the application of non-parametric mathematical programming techniques in the context of performance evaluation facilitated multi-criteria decision making. However,the estimates of performance on the basis of conventional programming techniques like DEA and FDH are affected by the presence of outliers in the sample observations. The present, accordingly uses more robust benchmarking techniques for evaluating the performance od sectoral mutual fund schemes based on observations for the second half of 2010. The USP of the present study is that it uses two partial frontier techniques (Order-m and Order- a) which are less susceptible to the problem of extreme data.

Multi-Criteria Decision Making for Vulnerability Mapping of Flood Hazard: A Case Study of Pune City

2019 ◽  
Vol 2 (1) ◽  
pp. 41-52
Author(s):  
Nitin Mundhe
Keyword(s):  
Decision Making ◽  
Flood Hazard ◽  
Geographical Information ◽  
Multi Criteria Decision Making ◽  
Flood Hazards ◽  
Very High Frequency ◽  
Flood Vulnerability ◽  
Natural Risk ◽  
The Town

Floods are natural risk with a very high frequency, which causes to environmental, social, economic and human losses. The floods in the town happen mainly due to human made activities about the blockage of natural drainage, haphazard construction of roads, building, and high rainfall intensity. Detailed maps showing flood vulnerability areas are helpful in management of flood hazards. Therefore, present research focused on identifying flood vulnerability zones in the Pune City using multi-criteria decision-making approach in Geographical Information System (GIS) and inputs from remotely sensed imageries. Other input data considered for preparing base maps are census details, City maps, and fieldworks. The Pune City classified in to four flood vulnerability classes essential for flood risk management. About 5 per cent area shows high vulnerability for floods in localities namely Wakdewadi, some part of the Shivajinagar, Sangamwadi, Aundh, and Baner with high risk.

scholarly journals Coupling Fuzzy Multi-Criteria Decision-Making and Clustering Algorithm for MSW Landfill Site Selection (Case Study: Lanzhou, China)

2021 ◽  
Vol 10 (6) ◽  
pp. 403
Author(s):  
Jiamin Liu ◽  
Yueshi Li ◽  
Bin Xiao ◽  
Jizong Jiao
Keyword(s):  
Decision Making ◽  
Clustering Algorithm ◽  
Fuzzy Membership Function ◽  
Multi Criteria Decision Making ◽  
Landfill Site Selection ◽  
Spatial Distribution Characteristics ◽  
Criteria Weights ◽  
Spatial Decision Making ◽  
Complex Decision

The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods.

Multi-criteria decision-making algorithm based on aggregation operators under the complex interval-valued q-rung orthopair uncertain linguistic information

2021 ◽  
pp. 1-30
Author(s):  
Harish Garg ◽  
Zeeshan Ali ◽  
Zaoli Yang ◽  
Tahir Mahmood ◽  
Sultan Aljahdali
Keyword(s):  
Decision Making ◽  
Brain Tumors ◽  
Score Function ◽  
Aggregation Operators ◽  
Multi Criteria Decision Making ◽  
Linguistic Features ◽  
Interval Numbers ◽  
Fundamental Properties ◽  
Interval Valued

The paper aims to present a concept of a Complex interval-valued q-rung orthopair uncertain linguistic set (CIVQROULS) and investigated their properties. In the presented set, the membership grades are considered in terms of the interval numbers under the complex domain while the linguistic features are added to address the uncertainties in the data. To further discuss more, we have presented the operation laws and score function for CIVQROULS. In addition to them, we present some averaging and geometric operators to aggregate the different pairs of the CIVQROULS. Some fundamental properties of the proposed operators are stated. Afterward, an algorithm for solving the decision-making problems is addressed based on the proposed operator using the CIVQROULS features. The applicability of the algorithm is demonstrated through a case study related to brain tumors and their effectiveness is compared with the existing studies.

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