Discover how AI technologies are transforming quantitative trading. From mastering QuantConnect's powerful algorithmic trading platform to utilizing PredictNow's advanced predictive analytics and employing adaptive investment strategies, this book equips you with the tools and knowledge to thrive in modern financial markets.
Explore fundamental concepts such as supervised and unsupervised learning, as well as advanced techniques like deep learning, neural networks, and recurrent neural networks. Learn how these methodologies can be applied to financial data to identify patterns, trends, and anomalies, empowering you to make more informed, data-driven trading decisions.
Foundations of Capital Markets
Foundations of Quantitative Trading
Defining AI Problems
Dataset Preparation
Model Choice,Training, and Application
Applied Machine Learning
Better Hedging with Reinforcement Learning
AI for Risk Management and Optimization
Application of LLMs and Generative AI in Trading
Examine strategies like mean reversion, momentum trading, and statistical arbitrage, and understand how machine learning techniques are used to implement these approaches. Through detailed analysis of successful examples, you’ll gain a deeper understanding of the strengths, limitations, and potential risks of AI-driven trading strategies. Learn how metrics like the Sharpe Ratio, Sortino Ratio, and CAGR are used to evaluate risk-adjusted returns and overall performance.
Learn how to clean, transform, and prepare financial data for machine learning algorithms through techniques like feature engineering. Discover how to create actionable features using technical indicators, fundamental analysis, and sentiment analysis, and explore signal detection methods that help identify high-probability trading opportunities. Mastering these techniques will allow you to turn raw data into actionable insights for better trading decisions.
Gain insight into QuantConnect, a comprehensive scalable cloud-based platform designed for quantitative backtesting, optimization, live trading, and user collaboration. Learn how to use its features to automate trading strategies, optimize workflows, and refine your approach. With the right platform in place, you can focus on generating alpha while effectively, managing risk and maximizing trading performance.
Founder and Chief Executive Officer of QuantConnect
Founder and Chief Executive Officer of RocketEdge.com
Founder and Chief Scientific Officer of Predictnow.ai
Chief Executive Officer of Adaptive Investment Solutions
Senior Product Manager at AWS AI
PETTER N. KOLM
Professor, Courant Institute of Mathematical Sciences, New York University; Awarded “Quant of the Year” 2021.
A must-have for algorithmic traders and students, this book emphasizes designing trading strategies with QuantConnect. Featuring Python examples and advanced AI/ML models, it offers a clear and accessible presentation ideal for anyone in quantitative finance.
CHRIS BARTLETT
CEO, Algoseek
This comprehensive guide masterfully bridges the gap between AI technology and practical trading applications, offering finance professionals valuable insights for developing robust, data-driven trading strategies.
MICHAEL ROBBINS
Author of "Quantitative Asset Management".
This concise guide provides a gentle introduction with hands-on examples and expert insights into dissecting and evaluating trades from seasoned traders. The code will make otherwise complex or confusing examples clear. It is an excellent springboard for developing your own strategies.
DIMITRI BIANCO
Head of Quant Risk and Research.
The book ties both theory and industry together while providing code, output, and a platform to implement AI models in a trading environment. Cookbook style makes it a great book for those new to machine learning and AI in quantitative finance.
JACQUES JOUBERT
Quant Researcher and Developer, Co-Founder and CEO of Hudson and Thames Quantitative Research
This is the book I wish I had when starting out, it would have saved me years! It offers rare insights and practical tutorials, allowing the next generation of quants to stand on the shoulders of giants.
RAJNEESH SINGH
Director, Amazon SageMaker
As a novice trader myself, I have been looking for ways to apply AI in real world trading scenarios. This book does an excellent job in explaining trading concepts and mapping these to AI concepts to build trading strategies. A must read if you want to use AI for building wealth.
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