1
Frontmatter
6 chapters2
Part I: Foundations
7 chapters3
Part II: Market Microstructure and Pricing
7 chapters- Part II: Market Microstructure & Pricing
- Chapter 7: Order Books and the Limit Order Market
- Chapter 8: Automated Market Makers
- Chapter 9: Scoring Rules and Proper Incentives
- Chapter 10: Bid-Ask Spreads, Transaction Costs, and Fees
- Chapter 11: Information Aggregation Theory
- Chapter 12: Calibration — Measuring Forecast Quality
4
Part III: Trading Strategies and Edge
8 chapters- Part III: Trading Strategies & Edge
- Chapter 13: Finding and Quantifying Your Edge
- Chapter 14: Binary Outcome Trading Strategies
- Chapter 15: Multi-Outcome and Scalar Market Strategies
- Chapter 16: Arbitrage in Prediction Markets
- Chapter 17: Portfolio Construction and Risk Management
- Chapter 18: Behavioral Biases and Market Inefficiencies
- Chapter 19: Live Trading, Execution, and Operational Discipline
5
Part IV: Data Science and Modeling
9 chapters- Part IV: Data Science & Modeling
- Chapter 20: Data Collection and Web Scraping
- Chapter 21: Exploratory Data Analysis of Market Data
- Chapter 22: Statistical Modeling — Regression and Time Series
- Chapter 23: Machine Learning for Probability Estimation
- Chapter 24: NLP and Sentiment Analysis
- Chapter 25: Ensemble Methods and Model Combination
- Chapter 26: Backtesting Prediction Market Strategies
- Chapter 27: Feature Stores, Pipelines, and MLOps
6
Part V: Market Design and Mechanism Engineering
7 chapters- Part V: Market Design & Mechanism Engineering
- Chapter 28: Principles of Prediction Market Design
- Chapter 29: Liquidity Provision and Market Making
- Chapter 30: Combinatorial Prediction Markets
- Chapter 31: Decision Markets and Futarchy
- Chapter 32: Building a Prediction Market Platform from Scratch
- Chapter 33: Scaling, Performance, and Operations
7
Part VI: Blockchain and Decentralized Markets
5 chapters8
Part VII: Regulation, Ethics, and the Future
6 chapters9
Appendices
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