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Financial Decision Making Using Computational Intelligence

Language EnglishEnglish
Book Hardback
Book Financial Decision Making Using Computational Intelligence Michael Doumpos
Libristo code: 01427849
Publishers Springer-Verlag New York Inc., July 2012
Financial Decision Making Using Computational Intelligence covers all the recent developments in com... Full description
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102.99
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Financial Decision Making Using Computational Intelligence covers all the recent developments in complex financial decision making through computational intelligence approaches. Computational intelligence has evolved rapidly in recent years and it is now one of the most active fields in operations research and computer science. The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides a wide range of useful techniques, including new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems.§This book presents the recent advances made in financial decision making using computational intelligence, covering both new methodological developments as well as new emerging application areas. This work covers a wide range of topics related to financial decision making, financial modeling, risk management, and financial engineering, including algorithmic trading, financial time-series analysis, asset pricing, portfolio management, auction markets, and insurance services. Practitioners in the financial industry as well as operations researchers, management scientists, and data analysts will find this publication highly useful.

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About the book

Full name Financial Decision Making Using Computational Intelligence
Language English
Binding Book - Hardback
Date of issue 2012
Number of pages 326
EAN 9781461437727
ISBN 1461437725
Libristo code 01427849
Weight 650
Dimensions 167 x 240 x 24
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