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.
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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.
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