Financial markets demand speed, intelligence, and scalability. Cloud-Native Quant Trading equips you with the knowledge and tools to harness the full power of modern cloud infrastructure for AI-driven trading. Designed for quant professionals, data scientists, and algorithmic traders, this book shows you how to design, deploy, and optimize trading systems that scale effortlessly across AWS, GCP, and Azure.

Inside, you’ll explore:

Cloud-native architectures tailored for high-frequency and low-latency trading.
Real-time data pipelines for market data ingestion, feature engineering, and execution.
AI model integration with LSTMs, Transformers, and reinforcement learning agents.
Scalable infrastructure strategies using Kubernetes, serverless computing, and distributed storage.
Cross-cloud deployment for risk management, redundancy, and global reach.
Security and compliance frameworks essential for institutional-grade trading systems.

From setting up elastic environments to building robust AI pipelines, this book bridges the gap between quantitative finance and cutting-edge cloud engineering. By the end, you’ll have a practical blueprint for trading systems that are not only intelligent, but built to thrive in the fast-changing, globalized market landscape.

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