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From the brand
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Make AI work for you.
From ChatGPT to agentic AI, quantum computing to prompt engineering, large language models, the ethics of AI, and beyond, Wiley has the guides you need to join the AI revolution and make artificial intelligence work for you.
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AI & Finance
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AI & Finance
From the Publisher
Modern, Hands-on Approach to AI in Trading
"Hands-On AI Trading with Python, QuantConnect, and AWS" is a practical guide that bridges the gap between AI theory and real-world trading applications. Focusing on intuition and hands-on experience, the book uses QuantConnect's cloud-based platform to streamline AI strategy development by avoiding technical complexities like data management or infrastructure setup. It covers a wide range of techniques, including machine learning, deep learning, and reinforcement learning, applied to practical trading scenarios. Printed in full color, it enhances understanding with detailed charts and code snippets, making advanced concepts accessible to both beginners and professionals in quantitative finance.
A Comprehensive Suite of Examples
Our book features over 20 complete AI trading algorithms, addressing key techniques like trend detection, regime classification, and reinforcement learning for optimal hedging. Examples progress from basic concepts to advanced applications using Python with TensorFlow, PyTorch, and scikit-learn, all on the QuantConnect platform for backtesting and live trading.
Technologies covered include Machine Learning (Random Forests, SVMs, Gaussian Processes), Deep Learning (CNNs, RNNs, Transformers), Reinforcement Learning, Natural Language Processing, Time Series Analysis, and Clustering.
Examples include: ML Trend Scanning with MLFinlab, Factor Preprocessing Techniques for Regime Detection, Reversion vs. Trending: Strategy Selection by Classification, Alpha by Hidden Markov Models, FX SVM Wavelet Forecasting, and more. Each includes detailed explanations, code, and discussions on practical considerations, equipping readers to master AI in quantitative finance.
Practically Introduces Quantitative Concepts
Our book goes beyond coding exercises, integrating key concepts like risk management, portfolio optimization, and corporate actions directly into AI trading strategies. We explore techniques like Corrective AI and Conditional Parameter Optimization to dynamically adapt strategies to volatile markets and demonstrate how AI can predict and capitalize on events like mergers and dividends. Emphasizing transaction costs, slippage, and real-world frictions, we ensure readers are equipped to transition seamlessly from backtesting to live trading with adaptive, robust systems.
Rich Additional Content and Community
To enhance the value of our book, we provide extensive resources, including a GitHub repository with all code examples, actively maintained for compatibility with QuantConnect and Python libraries. Readers can engage with a vibrant community through forums, webinars, and social media, fostering collaboration and continuous learning. Additional online resources, such as extended datasets, articles, and video tutorials, dive into advanced topics and emerging AI trading trends. Our close ties with QuantConnect ensure readers have access to the platform’s latest features, creating a comprehensive learning experience that blends cutting-edge techniques, practical finance concepts, and a supportive ecosystem.
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