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Artificial Intelligence in Financial Markets Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics
Title
Artificial Intelligence in Financial Markets [electronic resource] : Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics / edited by Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous, Konstantinos Theofilatos.
ISBN
9781137488800
Publication
London : Palgrave Macmillan UK : Imprint: Palgrave Macmillan, 2016.
Physical Description
XV, 344 p. 49 illus., 17 illus. in color : online resource.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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. .
Variant and related titles
Springer eBooks.
Other formats
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
December 01, 2016
Series
New Developments in Quantitative Trading and Investment
Contents
1. A Review of Applications of Artificial Intelligence in Financial Domain
SECTION I: Financial Forecasting and Trading
2. Trading the FTSE100 Index – ‘Adaptive' Modelling and Optimisation Techniques
3. Modelling, Forecasting and Trading the Crack – A Sliding Window Approach to Training Neural Networks
4. GEPTrader: A new Standalone Tool for Constructing Trading Strategies with Gene Expression Programming
SECTION II: ECONOMICS
5. Business Intelligence for Decision Making in Economics
6. An automated literature analysis on data mining applications to credit risk assessment
SECTION III: CREDIT RISK ANALYSIS
7. Intelligent credit risk decision support: architecture and implementations
8. Artificial Intelligence for Islamic Sukuk Rating Predictions
SECTION IV: PORTFOLIO MANAGEMENT, ANALYSIS AND OPTIMISATION
9. Portfolio selection as a multiperiod choice problem under uncertainty: an interation-based approach
10. Handling model risk in portfolio selection using a Multi-Objective Genetic Algorithm
11. Linear regression versus fuzzy linear regression — does it make a difference in the evaluation of the performance of mutual fund managers?
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