Beginner's Track, Prediction Markets
summary
Covers how binary yes/no shares always sum to $1, contrasts order book vs AMM liquidity and shows a live Scaffold-ETH demo deploying a market with 100 yes and 100 no tokens, a 0.01 ETH payout per winning token and 10 tokens locked as starting liquidity. Explains oracle options (Chainlink, optimistic staking) and revenue via trading fees, cites a real-world $3.3 billion betting figure for Trump vs Harris, and explores AI agents funding many micro-markets to solve niche information gaps.
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chapters (15)
- 0:00Introduction to Prediction Markets & Real-World Use Cases
- 0:43How Binary Markets Work: Yes/No Shares & $1 Rule
- 2:22Key Components: Tokens (ERC20/1155) & Trading Mechanisms
- 4:20Order Books vs. AMMs for Prediction Market Liquidity
- 5:41Oracle Challenges: Bringing Real-World Data On-Chain
- 7:37Scaffold-ETH Demo: Setting Up a Prediction Market
- 9:44Roles: Users, Liquidity Providers & Oracles
- 10:53Liquidity Pools: Minting Tokens & Starting Probabilities
- 13:16Dynamic Probability Adjustments & Locked Tokens
- 15:28Monetization Models: Fees, Incentives & Revenue Pools
- 17:23Live Trading Demo: Buying/Selling Shares
- 19:18Reporting Outcomes & Resolving Markets
- 21:22Advanced Concepts: Conditional Tokens & Multi-Outcome Markets
- 22:29AI Agents & the Future of Decentralized Forecasting
- 25:11Q&A: Legal Considerations & Stock Market Integration
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