Artificial Intelligence in Financial Markets: Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics 1st Edition Christian 1137488808 9781137488800

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Product details:

• ISBN 10: 1137488808
• ISBN 13: 9781137488800
• Author: Christian L. Dunis

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.

Table of contents:

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

2. Financial Forecasting and Trading

2. Trading the FTSE100 Index: ‘Adaptive’ Modelling and Optimization 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

3. Economics

5. Business Intelligence for Decision Making in Economics

4. Credit Risk and Analysis

6. An Automated Literature Analysis on Data Mining Applications to Credit Risk Assessment

7. Intelligent Credit Risk Decision Support: Architecture and Implementations

8. Artificial Intelligence for Islamic Sukuk Rating Predictions

5. Portfolio Management, Analysis and Optimisation

9. Portfolio Selection as a Multi-period Choice Problem Under Uncertainty: An Interaction-Based Approach

10. Handling Model Risk in Portfolio Selection Using Multi-Objective Genetic Algorithm

11. Linear Regression Versus Fuzzy Linear Regression: Does it Make a Difference in the Evaluation of the Performance of Mut

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