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Artificial Intelligence in Financial Markets

Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics

Palgrave Macmillan

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xv
  2. Introduction to Artificial Intelligence

    1. Front Matter

      Pages 1-1
    2. A Review of Artificially Intelligent Applications in the Financial Domain

      • Swapnaja Gadre-Patwardhan, Vivek V. Katdare, Manish R. Joshi
      Pages 3-44
  3. Financial Forecasting and Trading

    1. Front Matter

      Pages 45-45
    2. Trading the FTSE100 Index: ‘Adaptive’ Modelling and Optimization Techniques

      • Peter W. Middleton, Konstantinos Theofilatos, Andreas Karathanasopoulos
      Pages 47-67
    3. Modelling, Forecasting and Trading the Crack: A Sliding Window Approach to Training Neural Networks

      • Christian L. Dunis, Peter W. Middleton, Konstantinos Theofilatos, Andreas Karathanasopoulos
      Pages 69-106
    4. GEPTrader: A New Standalone Tool for Constructing Trading Strategies with Gene Expression Programming

      • Andreas Karathanasopoulos, Peter W. Middleton, Konstantinos Theofilatos, Efstratios Georgopoulos
      Pages 107-121
  4. Economics

    1. Front Matter

      Pages 123-123
    2. Business Intelligence for Decision Making in Economics

      • Bodislav Dumitru-Alexandru
      Pages 125-158
  5. Credit Risk and Analysis

    1. Front Matter

      Pages 159-159
    2. Intelligent Credit Risk Decision Support: Architecture and Implementations

      • Paulius Danenas, Gintautas Garsva
      Pages 179-210
    3. Artificial Intelligence for Islamic Sukuk Rating Predictions

      • Tika Arundina, Mira Kartiwi, Mohd. Azmi Omar
      Pages 211-241
  6. Portfolio Management, Analysis and Optimisation

    1. Front Matter

      Pages 243-243
    2. Handling Model Risk in Portfolio Selection Using Multi-Objective Genetic Algorithm

      • Prisadarng Skolpadungket, Keshav Dahal, Napat Harnpornchai
      Pages 285-310
  7. Back Matter

    Pages 337-344

About this book

As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making.

This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization.

This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field. 

Editors and Affiliations

  • ACANTO Holding, Hannover, Germany

    Christian L. Dunis

  • University of Liverpool, Liverpool, United Kingdom

    Peter W. Middleton

  • American University of Beirut (AUB), Beirut, Lebanon

    Andreas Karathanasopolous

  • University of Patras, Patras, Greece

    Konstantinos Theofilatos

About the editors

Dr Christian L. Dunis is a Founding Partner of Acanto Research, where he is responsible for global risk and new products. He is also Emeritus Professor of Banking and Finance at Liverpool John Moores University where he directed the Centre for International Banking, Economics and Finance (CIBEF) from February 1999 through to August 2011. Christian holds a MSc and a Superior Studies Diploma in International Economics, and a PhD in Economics from the University of Paris.

Dr Peter W. Middleton completed his PhD at the University of Liverpool. His working experience is in Asset Management and he has published numerous articles on Financial Forecasting of Commodity spreads and Equity time series.

Dr Andreas Karathanasopoulos studied for his MSc and Phd at Liverpool John Moores University under the supervision of Professor Christian Dunis. His working experience is academic having taught at Ulster University, London Metropolitan University and the University of East London. He is currently Associate Professor at the American University of Beirut and has published over 30 articles and one book in the area of artificial intelligence.

Dr Konstantinos Theofilatos completed his MSc and PhD in the University of Patras Greece. His research interests include computational intelligence, financial time series forecasting and trading, bioinformatics, data mining and web technologies. He has published 27 publications in scientific peer reviewed journals and over 30 articles in conference proceedings.

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access