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Kategorie szczegółowe BISAC

Computational Intelligence in Economics and Finance: Volume II

ISBN-13: 9783642091933 / Angielski / Miękka / 2010 / 228 str.

Paul P. Wang; Tzu-Wen Kuo; Shu-Heng Chen
Computational Intelligence in Economics and Finance: Volume II Wang, Paul P. 9783642091933 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Computational Intelligence in Economics and Finance: Volume II

ISBN-13: 9783642091933 / Angielski / Miękka / 2010 / 228 str.

Paul P. Wang; Tzu-Wen Kuo; Shu-Heng Chen
cena 403,47 zł
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Readers will find, in this highly relevant and groundbreaking book, research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results.

Kategorie:
Informatyka, Bazy danych
Kategorie BISAC:
Computers > Artificial Intelligence - General
Business & Economics > Finance - General
Computers > Mathematical & Statistical Software
Wydawca:
Springer
Język:
Angielski
ISBN-13:
9783642091933
Rok wydania:
2010
Ilość stron:
228
Waga:
0.39 kg
Wymiary:
23.5 x 15.5
Oprawa:
Miękka
Wolumenów:
01

Computational Intelligence in Economics and Finance: Shifting the Research Frontier.- An Overview of Insurance Uses of Fuzzy Logic.- Forecasting Agricultural Commodity Prices using Hybrid Neural Networks.- Nonlinear Principal Component Analysis for Withdrawal from the Employment Time Guarantee Fund.- Estimating Female Labor Force Participation through Statistical and Machine Learning Methods: A Comparison.- An Application of Kohonen’s SOFM to the Management of Benchmarking Policies.- Trading Strategies Based on K-means Clustering and Regression Models.- Comparison of Instance-Based Techniques for Learning to Predict Changes in Stock Prices.- Application of an Instance Based Learning Algorithm for Predicting the Stock Market Index.- Evaluating the Efficiency of Index Fund Selections Over the Fund’s Future Period.- Failure of Genetic-Programming Induced Trading Strategies: Distinguishing between Efficient Markets and Inefficient Algorithms.- Nonlinear Goal-Directed CPPI Strategy.- Hybrid-Agent Organization Modeling: A Logical-Heuristic Approach.

Prof. Dr Shu-Heng Chen is a professor in the Department of Economics of the National Chengchi University. He serves as the Director of the AI-ECON Research Center, National Chengchi University. Dr. Chen holds a M.A. degree in mathematics and a Ph. D. in Economics from the University of California at Los Angeles. He has more than 150 publications in international journals, edited volumes and conference proceedings.

Prof. Dr. Paul P. Wang, has published extensively in the fields of mathematical systems modeling, fuzzy logic, pattern recognition,intelligent ystems,managements of economical systems, and the computational biology and bioinformatics. He has been a co-founder of several corporations including Intelligent Machines Inc. He has served as an EiC of the Information Sciences Journal for two decades and he is the managing editor of the New Mathematics & Natural Computing at present. In addition,he is the founder of JCIS, Inc. and Society for Mathematics of Uncertainty in 2006.

Prof. Dr. Tzu-Wen Kuo is an assistant professor in Department of Finance and Banking of Aletheia University in Taiwan. She is also a fellow of AI-ECON research center. Her research interest is Genetic Programming in Economics and Finance.

Computational intelligence (CI), as an alternative to statistical and econometric approaches, has been applied to a wide range of economics and finance problems in recent years, for example to price forecasting and market efficiency.

This book contains research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results.

Chen, Wang, and Kuo have grouped the 12 contributions following their introductory chapter into applications of fuzzy logic, neural networks (including self-organizing maps and support vector machines), and evolutionary computation. All chapters were selected either by invitation or based on a careful selection and extension of best papers from the International Workshop on Computational Intelligence in Economics and Finance in 2005. Overall, the book offers researchers an excellent overview of current advances and applications of computational intelligence techniques to economics and finance problems.

Wang, Paul P. Colleen A. Morris, M.D. is a professor and chief o... więcej >


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