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Artificial Intelligence in Financial Markets

Overview of attention for book
Cover of 'Artificial Intelligence in Financial Markets'

Table of Contents

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    Book Overview
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    Chapter 1 A Review of Artificially Intelligent Applications in the Financial Domain
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    Chapter 2 Trading the FTSE100 Index: ‘Adaptive’ Modelling and Optimization Techniques
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    Chapter 3 Modelling, Forecasting and Trading the Crack: A Sliding Window Approach to Training Neural Networks
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    Chapter 4 GEPTrader: A New Standalone Tool for Constructing Trading Strategies with Gene Expression Programming
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    Chapter 5 Business Intelligence for Decision Making in Economics
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    Chapter 6 An Automated Literature Analysis on Data Mining Applications to Credit Risk Assessment
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    Chapter 7 Intelligent Credit Risk Decision Support: Architecture and Implementations
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    Chapter 8 Artificial Intelligence for Islamic Sukuk Rating Predictions
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    Chapter 9 Portfolio Selection as a Multi-period Choice Problem Under Uncertainty: An Interaction-Based Approach
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    Chapter 10 Handling Model Risk in Portfolio Selection Using Multi-Objective Genetic Algorithm
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    Chapter 11 Linear Regression Versus Fuzzy Linear Regression: Does it Make a Difference in the Evaluation of the Performance of Mutual Fund Managers?
Attention for Chapter 2: Trading the FTSE100 Index: ‘Adaptive’ Modelling and Optimization Techniques
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Citations

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Chapter title
Trading the FTSE100 Index: ‘Adaptive’ Modelling and Optimization Techniques
Chapter number 2
Book title
Artificial Intelligence in Financial Markets
Published by
Palgrave Macmillan, London, January 2016
DOI 10.1057/978-1-137-48880-0_2
Book ISBNs
978-1-137-48879-4, 978-1-137-48880-0
Authors

Peter W. Middleton, Konstantinos Theofilatos, Andreas Karathanasopoulos

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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 %
Researcher 1 100%
Readers by discipline Count As %
Business, Management and Accounting 1 100%

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