Computational intelligence in economics and finance
Author(s)
Bibliographic Information
Computational intelligence in economics and finance
Springer, c2007
- v. 2
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
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.
by "Nielsen BookData"
