KOL research
@0xChainMind
A wallet-filtering and on-chain copy-trading KOL example. The real lesson is not blind copying, but building a logic for distinguishing which wallets are worth following and which ones should be ignored.
📌 Research value
@0xChainMind turns Polymarket’s on-chain visibility into an actionable wallet-ranking framework: who to follow, who not to follow, and how to compute real post-slippage EV.
Core idea: most users treat Polymarket like a casino, but consistently profitable wallets can still be identified and studied.
🔍 Why copy-trading is possible here
- Orders are matched off-chain but settled on-chain
- Each position belongs to a wallet
- Entry price and transaction history can be reconstructed
Main challenge: not seeing the wallet, but understanding what actually created its profitability.
🐋 Three whale types
1. Directional traders (worth studying)
Lower frequency, larger size, more topic focus, higher chance of genuine informational edge.
2. Market makers (do not copy)
Bi-directional inventory, spread capture, maker rewards—follower economics do not match.
3. High-frequency bots (do not copy)
Ultra-low latency makes delayed replication negative EV almost immediately.
📊 Three wallet metrics
Sharpe = (average return - risk-free rate) / return std
f = (p × b - q) / b
EV_copy = EV - slippage
Any serious copy system must include slippage and execution delay, otherwise many “high EV” wallets are illusions.
✅ Correct approach
- Do not copy leaderboard wallets
- Do not copy high-frequency bots
- Build a basket of 5–10 quality wallets
- Raise conviction only when multiple strong wallets converge