Documentation
Learn how frfn prediction markets work
What is frfn?
frfn is a permissionless prediction market solving liquidity fragmentation and sybil attacks by dynamically concentrating liquidity around uncertain outcomes (40-60% odds) using its pm-AMM, which auto-adjusts exposure as events near resolution. Markets bootstrapped via bonding curves incentivize balanced trading, then graduate to efficient AMMs. An AI agent oracle resolves outcomes, but users can stake collateral to dispute errors—creating a self-improving oracle that delivers trusted real-world data, outperforming platforms reliant on static liquidity models or centralized resolution.
Built for Monad Hackathon, leveraging Monad's high-TPS blockchain.
How It Works
Dynamic Liquidity
frfn's pm-AMM auto-concentrates liquidity around uncertain outcomes, improving capital efficiency and reducing slippage.
Market Lifecycle
Markets start with bonding curves for initial trading.
Dynamic liquidity concentration around uncertain outcomes.
AI oracle resolves outcomes, with user-staked disputes.
Current Implementation
Currently live on Monad Testnet with basic market creation, trading, and manual resolution.
Future Plans
- Black-Scholes model integration (implemented)
- Uniswap v4 hook deployment (awaiting Monad)
- AI oracle for automated resolution
Technical Architecture
Smart contracts for market creation, basic AMM, and USDC trading. Future integration with Uniswap v4 and AI oracle.
Roadmap
- Current: Basic implementation on Monad Testnet
- Phase 1: Black-Scholes integration
- Phase 2: Uniswap v4 hook deployment
- Phase 3: AI oracle integration
- Phase 4: Monad Mainnet launch