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Artificial Intelligence in Financial Markets

Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics

  • Christian L. Dunis
  • Peter W. Middleton
  • Andreas Karathanasopolous
  • Konstantinos Theofilatos

Table of contents

  1. Front Matter
    Pages i-xv
  2. Introduction to Artificial Intelligence

    1. Front Matter
      Pages 1-1
    2. Swapnaja Gadre-Patwardhan, Vivek V. Katdare, Manish R. Joshi
      Pages 3-44
  3. Financial Forecasting and Trading

    1. Front Matter
      Pages 45-45
    2. Peter W. Middleton, Konstantinos Theofilatos, Andreas Karathanasopoulos
      Pages 47-67
    3. Christian L. Dunis, Peter W. Middleton, Konstantinos Theofilatos, Andreas Karathanasopoulos
      Pages 69-106
    4. Andreas Karathanasopoulos, Peter W. Middleton, Konstantinos Theofilatos, Efstratios Georgopoulos
      Pages 107-121
  4. Economics

    1. Front Matter
      Pages 123-123
    2. Bodislav Dumitru-Alexandru
      Pages 125-158
  5. Credit Risk and Analysis

    1. Front Matter
      Pages 159-159
    2. Paulius Danenas, Gintautas Garsva
      Pages 179-210
    3. Tika Arundina, Mira Kartiwi, Mohd. Azmi Omar
      Pages 211-241
  6. Portfolio Management, Analysis and Optimisation

  7. Back Matter
    Pages 337-344

About this book

Introduction

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. 

Keywords

computational mathematics technology trading forecasting modelling neural networking investment behavioral economics portfolio management quantitative modeling

Editors and affiliations

  • Christian L. Dunis
    • 1
  • Peter W. Middleton
    • 2
  • Andreas Karathanasopolous
    • 3
  • Konstantinos Theofilatos
    • 4
  1. 1.ACANTO HoldingHannoverGermany
  2. 2.University of LiverpoolLiverpoolUnited Kingdom
  3. 3.American University of Beirut (AUB)BeirutLebanon
  4. 4.University of PatrasPatrasGreece

Bibliographic information

  • DOI https://doi.org/10.1057/978-1-137-48880-0
  • Copyright Information The Editor(s) (if applicable) and The Author(s) 2016
  • Publisher Name Palgrave Macmillan, London
  • eBook Packages Economics and Finance
  • Print ISBN 978-1-137-48879-4
  • Online ISBN 978-1-137-48880-0
  • Buy this book on publisher's site