Exchange-traded funds are built on a market structure that connects fund shares, underlying baskets, authorized participants, liquidity providers, and intraday pricing relationships. ETF Arbitrage with Python provides a practical technical guide to understanding how these relationships work and how they can be modeled with Python.

This book explains the core mechanics behind ETF creation and redemption, basket pricing, market making, liquidity behavior, and arbitrage relationships. Rather than focusing on trading claims or simplified profit formulas, it approaches ETF arbitrage as a market-structure problem involving data, pricing logic, execution constraints, and portfolio relationships.

Readers will learn how to examine ETF premiums and discounts, compare fund prices against underlying basket values, model liquidity conditions, and build Python workflows for research, analysis, and simulation. The book is designed for quantitative finance readers, analysts, developers, traders, and students who want a clearer technical understanding of ETF pricing systems.

Inside, the book covers:

Creation-redemption mechanics and ETF primary-market structure
Authorized participants and liquidity provider workflows
Basket pricing and net asset value relationships
Premium and discount analysis
ETF liquidity modeling and spread behavior
Market making concepts for ETF products
Python-based research workflows for ETF data
Hedging logic across ETF shares and underlying baskets
Practical modeling examples for pricing and arbitrage analysis

ETF Arbitrage with Python is a structured guide for readers who want to understand how ETF arbitrage works beneath the surface and how Python can be used to study ETF market behavior with greater precision.