000752149 000__ 05648cam\a2200529Ii\4500 000752149 001__ 752149 000752149 005__ 20230306141358.0 000752149 006__ m\\\\\o\\d\\\\\\\\ 000752149 007__ cr\cn\nnnunnun 000752149 008__ 151016s2016\\\\sz\\\\\\o\\\\\000\0\eng\d 000752149 019__ $$a925499539$$a931591972$$a932333125 000752149 020__ $$a9783319214405$$q(electronic book) 000752149 020__ $$a3319214403$$q(electronic book) 000752149 020__ $$z9783319214399 000752149 020__ $$z331921439X 000752149 0247_ $$a10.1007/978-3-319-21440-5$$2doi 000752149 035__ $$aSP(OCoLC)ocn925332953 000752149 035__ $$aSP(OCoLC)925332953$$z(OCoLC)925499539$$z(OCoLC)931591972$$z(OCoLC)932333125 000752149 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dIDEBK$$dYDXCP$$dOCLCF$$dEBLCP$$dAZU$$dCOO$$dDEBSZ$$dGW5XE 000752149 049__ $$aISEA 000752149 050_4 $$aQ342 000752149 08204 $$a006.3$$223 000752149 1001_ $$aResta, Marina,$$eauthor. 000752149 24510 $$aComputational intelligence paradigms in economic and financial decision making$$h[electronic resource] /$$cMarina Resta. 000752149 264_1 $$aCham :$$bSpringer,$$c2016. 000752149 300__ $$a1 online resource. 000752149 336__ $$atext$$btxt$$2rdacontent 000752149 337__ $$acomputer$$bc$$2rdamedia 000752149 338__ $$aonline resource$$bcr$$2rdacarrier 000752149 4901_ $$aIntelligent systems reference library ;$$v99 000752149 5050_ $$aPreface; Contents; List of Figures; List of Tables; Part I Theoretical Framework ; 1 Yet Another Introduction to Self-Organizing Maps; 1.1 Background; 1.2 The Basic Algorithm; 1.3 Stopping Criteria and Convergence Measures; 1.4 Output Visualization; 1.5 SOM Variants; 1.5.1 SOM Batch; 1.5.2 Topological Structures in SOMs; 1.5.3 Neural Gas and Growing Neural Gas; 1.5.4 Topology Representing Networks; 1.5.5 Self-Organizing Surface; 1.5.6 Evolving Self-Organizing Map; 1.5.7 Growing Hierarchical SOM; 1.6 Putting SOM at Work; 2 Networks Analysis and Beyond; 2.1 Introduction; 2.2 Classical Networks 000752149 5058_ $$a2.3 Lattice Network2.4 Scale-Free Networks; 2.4.1 Degree Distribution; 2.4.2 Power-Law Distribution in Real-World Networks; 2.4.3 Barabasi -- Albert Model; 2.5 The Configuration Model; 2.6 Small-World Networks; 2.7 Measuring the Robustness of Networks; 2.7.1 Average Shortest Path Length; 2.7.2 Clustering Coefficients; 2.7.3 Hierarchical Modularity; 2.7.4 Assortativity; 2.7.5 Degree Correlation; 2.8 Centrality Measures; 3 Elastic Maps; 3.1 Introduction; 3.2 A Formal Description; 3.3 How Elastic Maps Work; 3.4 Available Algorithm Implementations; Part II Applications 000752149 5058_ $$a4 SOM Variants for the Simulation of Market Price Modeling4.1 Introduction; 4.2 Voronoi Maps; 4.3 An Application to Financial Markets: Main Settings; 4.4 Experimental Results; 4.5 Conclusions and Outlooks for Future Works; 5 Elastic Maps to Define the Risk Profile of Financial Investments; 5.1 Introduction; 5.1.1 Strategic Asset Allocation; 5.1.2 Tactical Asset Allocation; 5.1.3 Stock Picking; 5.2 Portfolio Selection Within the Markowitz Framework; 5.3 Case Study: The General Framework; 5.4 Stocks Picking with Elastic Maps; 5.4.1 Maps Visualization 000752149 5058_ $$a5.4.2 Building Securities Portfolios with Elastic Maps5.5 Selection with Fundamental Analysis; 5.5.1 Data and Preprocessing; 5.5.2 The Formation of the Portfolio; 5.6 Comparison Between the Methods; 5.7 Conclusion; 6 Hubs and Communities of Financial Assets with Enhanced Self-Organizing Maps; 6.1 Introduction; 6.2 Value at Risk: An Introductory Guide; 6.3 Algorithmic Settings; 6.3.1 Self-Organizing Maps; 6.3.2 The VaRSOM; 6.4 Discussion Case; 6.5 Conclusion; 7 Financial Landscapes of Health Care Providers; 7.1 Introduction 000752149 5058_ $$a7.2 The Financial Statements of Public Italian Healthcare Providers: ƒ7.3 The Methodology: Motivation and Description; 7.3.1 The Minimum Spanning Tree Filtering Procedure; 7.3.2 The Planar Maximally Filtered Graph; 7.3.3 The Directed Bubble Hierarchical Tree; 7.4 Results Discussion; 7.4.1 Retrieving Information from Networks; 7.4.2 Cluster Analysis for the MST Network; 7.4.3 Cluster Analysis for the PMFG Network; 7.4.4 Cluster Analysis for the DBHT Network; 7.5 Conclusion; 8 Using SOM for Mortality Projection; 8.1 Background; 8.2 Mortality Trends and Related Issues; 8.2.1 Actuarial Notations 000752149 5058_ $$a8.2.2 The Lee -- Carter Model 000752149 506__ $$aAccess limited to authorized users. 000752149 520__ $$aThe book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process. In the first part the textbook presents a comprehensive and self-contained introduction to the field of self-organizing maps, elastic maps and social network analysis tools and provides necessary background material on the topic, including a discussion of more recent developments in the field. In the second part the focus is on practical applications, with particular attention paid to budgeting problems, market simulations, and decision-making processes, and on how such problems can be effectively managed by developing proper methods to automatically detect certain patterns. The book offers a valuable resource for both students and practitioners with an introductory-level college math background. 000752149 588__ $$aOnline resource; title from PDF title page (viewed October 22, 2015) 000752149 650_0 $$aComputational intelligence. 000752149 650_0 $$aFinance$$xDecision making. 000752149 77608 $$iPrint version:$$z331921439X$$z9783319214399$$w(OCoLC)911210566 000752149 830_0 $$aIntelligent systems reference library ;$$v99. 000752149 852__ $$bebk 000752149 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-21440-5$$zOnline Access$$91397441.1 000752149 909CO $$ooai:library.usi.edu:752149$$pGLOBAL_SET 000752149 980__ $$aEBOOK 000752149 980__ $$aBIB 000752149 982__ $$aEbook 000752149 983__ $$aOnline 000752149 994__ $$a92$$bISE