Overview
- Fahed Mostafa
Department of Computer Science and Computer Engineering, La Trobe University, Bundoora, Australia
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- Tharam Dillon
Department of Computer Science and Computer Engineering, La Trobe University, Bundoora, Australia
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- Elizabeth Chang
School of Business, University of New South Wales, Canberra, ACT, Australia
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- Presents an in-depth analysis of neural-network research in financial time series
- Addresses various issues concerning neural network modeling in market risk
- Explains and demonstrates how neural networks can overcome shortcomings in statistical time series modeling
- Includes supplementary material:sn.pub/extras
Part of the book series:Studies in Computational Intelligence (SCI, volume 697)
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Table of contents (9 chapters)
Front Matter
Pages i-xBack Matter
Pages 159-171
Reviews
Authors and Affiliations
Department of Computer Science and Computer Engineering, La Trobe University, Bundoora, Australia
Fahed Mostafa, Tharam Dillon
School of Business, University of New South Wales, Canberra, ACT, Australia
Elizabeth Chang
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Bibliographic Information
Book Title:Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk
Authors:Fahed Mostafa, Tharam Dillon, Elizabeth Chang
Series Title:Studies in Computational Intelligence
DOI:https://doi.org/10.1007/978-3-319-51668-4
Publisher:Springer Cham
eBook Packages:Engineering,Engineering (R0)
Copyright Information:Springer International Publishing AG 2017
Hardcover ISBN:978-3-319-51666-0Published: 10 March 2017
Softcover ISBN:978-3-319-84713-9Published: 04 May 2018
eBook ISBN:978-3-319-51668-4Published: 28 February 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number:1
Number of Pages:X, 171
Number of Illustrations:23 b/w illustrations
Topics:Computational Intelligence,Artificial Intelligence,Macroeconomics/Monetary Economics//Financial Economics,Operations Research/Decision Theory