Learning Prediction Markets

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42 chapters ~60 hours total 316 pages

1

Frontmatter

6 chapters

• Learning Prediction Markets -- Complete Outline
• Learning Prediction Markets
• Preface
• How to Use This Book
• Prerequisites
• Acknowledgments

2

Part I: Foundations

7 chapters

• Part I: Foundations
• Chapter 1 — What Are Prediction Markets?
• Chapter 2: A Brief History of Prediction Markets
• Chapter 3: Probability Fundamentals
• Chapter 4: Contracts, Payoffs, and Market Mechanics
• Chapter 5: The Modern Platform Landscape
• Chapter 6: Setting Up Your Python Toolkit

3

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 chapters

• Part VI: Blockchain & Decentralized Markets
• Chapter 34: Blockchain Fundamentals for Prediction Markets
• Chapter 35: Smart Contract Market Mechanisms
• Chapter 36: DeFi Integration and Liquidity Mining
• Chapter 37: Oracles, Resolution, and the Decentralization Trilemma

8

Part VII: Regulation, Ethics, and the Future

6 chapters

• Part VII: Regulation, Ethics & the Future
• Chapter 38: The Regulatory Landscape
• Chapter 39: Ethics of Prediction Markets
• Chapter 40: Real-World Applications
• Chapter 41: The Frontier — Research Directions
• Chapter 42: Capstone — Building a Complete Trading System

9

Appendices

8 chapters

• Appendix A: Mathematical Foundations
• Appendix B: Statistical Tables
• Appendix C: Python Reference / API Reference
• Appendix D: Data Sources
• Appendix E: Glossary
• Appendix F: Notation Guide
• Appendix G: Answers to Selected Exercises
• Appendix H: Bibliography

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