Computational Intelligence in Economics and Finance: Volume II, 2. sējumsPaul P. Wang, Tzu-Wen Kuo Springer Science & Business Media, 2007. gada 11. jūl. - 228 lappuses 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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1.–5. rezultāts no 40.
... efficiency. Investigating the validity of the efficient market hypothesis is a major concerned the finance research community continuously investigates. The editors selection of papers to include in this volume also successfully managed ...
... Efficiency of Index Fund Selections Over the Fund's Future Period Yukiko Orito, Manabu Takeda, Kiyoaki Iimura, Genji Yamazaki ............. 157 Failure of Genetic-Programming Induced Trading Strategies: Distinguishing between Efficient ...
... Efficient Markets Hypothesis A large part of this volume can be read as a continuous effort to question and to challenge the efficient markets hypothesis or the random walk hypothesis. Are stock prices predictable? Are trading ...
... efficient markets hypothesis is nonlinearity. In fact, one fundamental question regarding the efficient markets hypothesis is whether financial time series are linear or nonlinear. Nonlinearity motivates the use of CI tools in many ...
... efficiency, competitiveness or survivability of firms, or more generally, to answer what makes some firms thrive and others decline. Using observations of firms, economic theory provides different approaches to the answer. Some are more ...
Saturs
1 | |
An Overview of Insurance Uses of Fuzzy Logic | 24 |
ArnoldF Shapiro 25 | 63 |
Estimating Female Labor Force Participation through Statistical | 93 |
An Application of Kohonens SOFM to the Management | 106 |
Trading Strategies Based on Kmeans Clustering and Regression Models | 123 |
Application of an Instance Based Learning Algorithm for Predicting | 144 |
Nonlinear GoalDirected CPPI Strategy | 183 |
A LogicalHeuristic Approach | 209 |
Index | 224 |
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Computational Intelligence in Economics and Finance: Volume II Paul P. Wang,Tzu-Wen Kuo Priekšskatījums nav pieejams - 2010 |
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Business Applications and Computational Intelligence Kevin E. Voges,Nigel Pope Priekšskatījums nav pieejams - 2006 |