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On-Chain Analytics and Quantitative DeFi
Modeling AMM Dynamics, Impermanent Loss, and MEV with Python
English
90 b
New
Up to 30 days for returns
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Reactive Publishing
A practical technical guide to quantitative analysis of decentralized finance using on-chain data.
This book explores core concepts in on-chain analytics and quantitative DeFi, with a focus on Automated Market Makers (AMMs), impermanent loss, and Miner Extractable Value (MEV).
Through clear explanations and hands-on Python examples, you will learn how to:
- Model AMM dynamics and liquidity provision mechanics
- Analyze and manage impermanent loss
- Understand and quantify MEV opportunities on blockchain networks
- Work with blockchain event data using Python and Web3 libraries
Designed for developers, quantitative analysts, and DeFi researchers with intermediate Python knowledge, this book bridges blockchain fundamentals with practical data analysis techniques. All code examples are focused on transparent, reproducible methods using publicly available on-chain data.
Note: This is a technical reference, not financial advice. Trading and investing in cryptocurrency involves substantial risk.
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