Visual Explorations in Finance (häftad)
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Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
258
Utgivningsdatum
2010-10-21
Upplaga
Softcover reprint of the original 1st ed. 1998
Förlag
Springer London Ltd
Medarbetare
Kohonen, Teuvo (ed.), Deboeck, Guido (ed.)
Illustrationer
13 Illustrations, color; 122 Illustrations, black and white; XLV, 258 p. 135 illus., 13 illus. in co
Dimensioner
229 x 155 x 18 mm
Vikt
418 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9781849969994

Visual Explorations in Finance

with Self-Organizing Maps

av Guido Deboeck, Teuvo Kohonen
Häftad,  Engelska, 2010-10-21
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Self-organizing maps (SOM) have proven to be of significant economic value in the areas of finance, economic and marketing applications. As a result, this area is rapidly becoming a non-academic technology. This book looks at near state-of-the-art SOM applications in the above areas, and is a multi-authored volume, edited by Guido Deboeck, a leading exponent in the use of computational methods in financial and economic forecasting, and by the originator of SOM, Teuvo Kohonen. The book contains chapters on applications of unsupervised neural networks using Kohonen's self-organizing map approach.
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Innehållsförteckning

1: Applications.- 1 Let Financial Data Speak for Themselves.- 2 Projection of Long-term Interest Rates with Maps.- 3 Picking Mutual Funds with Self-Organizing Maps.- 4 Maps for Analyzing Failures of Small and Medium-sized Enterprises.- 5 Self-Organizing Atlas of Russian Banks.- 6 Investment Maps of Emerging Markets.- 7 A Hybrid Neural Network System for Trading Financial Markets.- 8 Real Estate Investment Appraisal of Land Properties using SOM.- 9 Real Estate Investment Appraisal of Buildings using SOM.- 10 Differential Patterns in Consumer Purchase Preferences using Self-Organizing Maps: A Case Study of China.- 2: Methodology, Tools and Techniques.- 11 The SOM Methodology.- 12 Self-Organizing Maps of Large Document Collections.- 13 Software Tools for Self-Organizing Maps.- 14 Tips for Processing and Color-coding of Self-Organizing Maps.- 15 Best Practices in Data Mining using Self-Organizing Maps.- Notes.- Author Index.

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