Modern Statistical Arbitrage with Python and Polars: Building Low-Latency Pairs and Cointegration Pipelines

By: James Preston

Reactive Publishing

Quantitative finance is shifting rapidly. Traditional Python tools like Pandas often hit performance bottlenecks when handling the massive, high-frequency datasets required for modern statistical arbitrage. Modern Statistical Arbitrage with Python and Polars provides a practical, code-first guide to building high-performance, real-time trading pipelines using Polars, the ultra-fast DataFrame library built on Rust.

Written for quantitative developers, financial engineers, and algorithmic traders, this book bridges the gap between statistical theory and production-ready execution. You will learn how to leverage Polars' lazy evaluation, parallel execution engine, and memory-efficient architecture to process market tick data, compute rolling statistical indicators, and execute cointegration tests at scale.

What You Will Learn:

High-Performance Data Processing: Harness Polars' lazy frame API and SIMD optimizations to manipulate tick-level price data with minimal memory footprint.

Modern Cointegration Techniques: Implement fast Augmented Dickey-Fuller (ADF) tests, Johansen cointegration procedures, and Kalman filtering for dynamic hedge ratio estimation.

Low-Latency Signal Generation: Build real-time pairs trading strategies, mean-reversion signals, and z-score indicators with zero-copy operations.

Pipeline Optimization: Seamlessly integrate Polars with Python's numerical ecosystem (NumPy, SciPy, and PyArrow) to optimize backtesting and signal execution speed.

Production-Grade Architecture: Design scalable, event-driven pipelines capable of handling live market feeds while minimizing slippage and execution latency.

Whether you are looking to replace legacy Pandas workflows or architect a brand-new quantitative trading infrastructure, this book gives you the tools, mathematics, and Python code required to gain a competitive edge in today's automated markets.

• Format: Paperback
• Language: English
• ISBN: B0HL3S8VQN
• ISBN13: 9798177113982
• Release Date: September 2026
• Publisher: Independently published
• Length: 468 Pages
• Weight: 1.24 lbs.
• Dimensions: 9.0" x 1.1" x 6.0"