AI for Portfolio Optimization: Engineering Intelligent Investment Strategies: Machine Learning Models for Asset Allocation, Risk Parity, and Dynamic Rebalancing
Reactive Publishing In a financial landscape defined by volatility and complexity, traditional investing methods are no longer enough. AI for Portfolio Optimization delivers a cutting-edge guide to engineering intelligent investment strategies using artificial intelligence. James Preston, a leader in the application of machine learning to financial markets, presents a modern, practical framework for constructing robust portfolios in the age of automation.
This book explores how AI models can enhance asset allocation, risk management, rebalancing, and scenario analysis. Readers will learn how to implement data-driven portfolio strategies using Python, integrate real-time financial data, and apply advanced techniques like reinforcement learning, ensemble methods, and genetic algorithms to optimize for return and resilience.
Whether you're a quantitative analyst, portfolio manager, fintech innovator, or serious investor, this guide equips you with the tools and mindset needed to thrive in the next era of intelligent capital allocation.