Financial decision aid using multiple criteria : recent models and applications /
This volume highlights recent applications of multiple-criteria decision-making (MCDM) models in the field of finance. Covering a wide range of MCDM approaches, including multiobjective optimization, goal programming, value-based models, outranking techniques, and fuzzy models, it provides researche...
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Group Author: | ; ; |
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Published: |
Springer,
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Publisher Address: | Cham, Switzerland : |
Publication Dates: | [2018] |
Literature type: | Book |
Language: | English |
Series: |
Multiple criteria decision making,
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Subjects: | |
Summary: |
This volume highlights recent applications of multiple-criteria decision-making (MCDM) models in the field of finance. Covering a wide range of MCDM approaches, including multiobjective optimization, goal programming, value-based models, outranking techniques, and fuzzy models, it provides researchers and practitioners with a set of MCDM methodologies and empirical results in areas such as portfolio management, investment appraisal, banking, and corporate finance, among others. The book addresses issues related to problem structuring and modeling, solution techniques, comparative analyses, as well as combinations of MCDM models with other analytical methodologies. |
Carrier Form: | xii, 241 pages : illustrations, forms ; 24 cm. |
Bibliography: | Includes bibliographical references. |
ISBN: |
9783319688756 (hardback) : 3319688758 (hardback) |
Index Number: | HG4011 |
CLC: | F830.59 |
Call Number: | F830.59/F491-5 |
Contents: | Intro; Preface; Acknowledgments; Contents; Multiattribute Assessment of the Financial Performance of Non-life Insurance Companies: Empirical Evidence from Europe; 1 Introduction; 2 Data; 3 Methodology; 3.1 Benefit-of-the-Doubt Approach; 3.2 Metafrontier Analysis; 3.3 Robust Estimation; 4 Results; 4.1 Performance Estimation; 4.2 Explanatory Econometric Analysis; 5 Conclusions and Future Perspectives; References; A DSS for Designing an MCDA Study with Application in Performance Evaluation of Forecasting Models; 1 Introduction; 2 MCDA: A Methodological Framework. |