The Confrontation of Two Clustering Methods in Portfolio Management: Ward’s Method Versus DCA Method

DOI10.1007/978-3-319-06569-4_6zbMath1325.91050OpenAlexW196300481MaRDI QIDQ3192958

Nadège Peltre, Hoai An Le Thi, Pascal Damel, Nguyen Trong Phuc

Publication date: 14 October 2015

Published in: Advanced Computational Methods for Knowledge Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-06569-4_6

zbMATH Keywords

DCAportfolio managementclustering methodsWard's method

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonconvex programming, global optimization (90C26) Portfolio theory (91G10)

Related Items (1)

Integrating cluster analysis with MCDM methods for the evaluation of local agricultural production

Uses Software

• SAS

Cites Work

• Unnamed Item
• Convex analysis approach to d. c. programming: Theory, algorithms and applications
• The DC (Difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems
• A new efficient algorithm based on DC programming and DCA for clustering
• DC Programming and DCA for General DC Programs
• Finding Groups in Data
• A D.C. Optimization Algorithm for Solving the Trust-Region Subproblem

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