Artificial Intelligence in Financial Markets: Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics
Book Details
- Author: Christian L. Dunis (Editor)
- Categories: Algorithmic Trading, Risk Management, Machine Learning
Quick Summary
This volume explores cutting-edge applications of artificial intelligence and machine learning methods in financial markets, covering risk management, portfolio optimization, and economic forecasting through computational approaches.
Detailed Summary
"Artificial Intelligence in Financial Markets" is an edited volume that examines the application of artificial intelligence techniques to financial market problems. The book covers the intersection of computational intelligence and finance, presenting methods and applications across risk management, portfolio optimization, and economic analysis.
The text addresses various AI methodologies as applied to financial problems, including neural networks for price prediction and pattern recognition, genetic algorithms for trading system optimization, fuzzy logic for handling imprecise financial data, and machine learning techniques for classification and regression tasks in market analysis.
Risk management applications explore how AI methods can improve upon traditional statistical approaches for measuring and managing financial risk, including more accurate estimation of Value at Risk (VaR), stress testing, and credit risk assessment. Portfolio optimization chapters examine how computational intelligence methods can address the limitations of mean-variance optimization, including handling non-normal return distributions, incorporating transaction costs, and managing the curse of dimensionality in large portfolios.
The economics applications cover the use of AI for macroeconomic forecasting, including predicting economic indicators and business cycle turning points, areas where traditional linear models have shown significant limitations.
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