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Computational Intelligence in Economics and Finance

Overview of attention for book
Cover of 'Computational Intelligence in Economics and Finance'

Table of Contents

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    Book Overview
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    Chapter 1 Computational Intelligence in Economics and Finance: Shifting the Research Frontier
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    Chapter 2 An Overview of Insurance Uses of Fuzzy Logic
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    Chapter 3 Forecasting Agricultural Commodity Prices using Hybrid Neural Networks
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    Chapter 4 Nonlinear Principal Component Analysis for Withdrawal from the Employment Time Guarantee Fund
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    Chapter 5 Estimating Female Labor Force Participation through Statistical and Machine Learning Methods: A Comparison
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    Chapter 6 An Application of Kohonen’s SOFM to the Management of Benchmarking Policies
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    Chapter 7 Trading Strategies Based on K-means Clustering and Regression Models
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    Chapter 8 Comparison of Instance-Based Techniques for Learning to Predict Changes in Stock Prices
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    Chapter 9 Application of an Instance Based Learning Algorithm for Predicting the Stock Market Index
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    Chapter 10 Evaluating the Efficiency of Index Fund Selections Over the Fund’s Future Period
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    Chapter 11 Failure of Genetic-Programming Induced Trading Strategies: Distinguishing between Efficient Markets and Inefficient Algorithms
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    Chapter 12 Nonlinear Goal-Directed CPPI Strategy
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    Chapter 13 Hybrid-Agent Organization Modeling: A Logical-Heuristic Approach
Attention for Chapter 10: Evaluating the Efficiency of Index Fund Selections Over the Fund’s Future Period
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Citations

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Chapter title
Evaluating the Efficiency of Index Fund Selections Over the Fund’s Future Period
Chapter number 10
Book title
Computational Intelligence in Economics and Finance
Published by
Springer, Berlin, Heidelberg, January 2007
DOI 10.1007/978-3-540-72821-4_10
Book ISBNs
978-3-54-072820-7, 978-3-54-072821-4
Authors

Yukiko Orito, Manabu Takeda, Kiyoaki Iimura, Genji Yamazaki, Orito, Yukiko, Takeda, Manabu, Iimura, Kiyoaki, Yamazaki, Genji

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 100%
Readers by discipline Count As %
Economics, Econometrics and Finance 1 100%

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