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Computational Intelligence Techniques for Trading and Investment

By: (Edited by) Andreas Karathanasopoulos , (Edited by) Christian Dunis , (Edited by) Georgios Sermpinis , (Edited by) Konstantinos Theofilatos , (Edited by) Spiros Likothanassis

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Ksh 7,350.00

Format: Hardback or Cased Book

ISBN-10: 0415636809

ISBN-13: 9780415636803

Series: Routledge Advances in Experimental and Computable Economics

Publisher: Taylor & Francis Ltd

Imprint: Routledge

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Mar 6th, 2014

Print length: 218 Pages

Weight: 498 grams

Dimensions (height x width x thickness): 23.90 x 15.60 x 2.00 cms

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  • Description

  • Reviews

Computational intelligence, a sub-branch of artificial intelligence, is a field which draws on the natural world and adaptive mechanisms in order to study behaviour in changing complex environments. This book provides an interdisciplinary view of current technological advances and challenges concerning the application of computational intelligence techniques to financial time-series forecasting, trading and investment.

Computational intelligence, a sub-branch of artificial intelligence, is a field which draws on the natural world and adaptive mechanisms in order to study behaviour in changing complex environments. This book provides an interdisciplinary view of current technological advances and challenges concerning the application of computational intelligence techniques to financial time-series forecasting, trading and investment.

The book is divided into five parts. The first part introduces the most important computational intelligence and financial trading concepts, while also presenting the most important methodologies from these different domains. The second part is devoted to the application of traditional computational intelligence techniques to the fields of financial forecasting and trading, and the third part explores the applications of artificial neural networks in these domains. The fourth part delves into novel evolutionary-based hybrid methodologies for trading and portfolio management, while the fifth part presents the applications of advanced computational intelligence modelling techniques in financial forecasting and trading.

This volume will be useful for graduate and postgraduate students of finance, computational finance, financial engineering and computer science. Practitioners, traders and financial analysts will also benefit from this book.


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