On-chain research and tokenomics
Not investment advice.
On-chain analysis (trading & research)
Uses public ledger data (balances, transfers, contract events, timestamps) alongside technical and fundamental lenses.
Building blocks: Holdings; transactions (audit trail via tx hashes; can monitor in near real time).
| Lens | Notes |
|---|---|
| Top holders / concentration | Float risk; often aggregated to entities when labeled |
| Exchange flows | Heuristic only—inflows/outflows need context (stablecoins, market-making, era) |
| ETF / treasury | Flows where addresses or filings are public |
| Whales | Large relative size; following whales is risky |
| Multichain | L2s, bridges—partial views mislead |
Macro-style metrics (examples): active addresses, tx count/volume, TVL, unique holders—definitions vary by indexer.
Visualization helps for complex paths; tables alone miss structure.
Tokenomics (educational)
Tokenomics = issuance, distribution, utility, and incentives.
Supply: Circulating vs total vs max (if any). Float = unlocked vs locked—watch vesting calendars (not deterministic for price).
Distribution: Mining/staking rewards; public sales; airdrops; team/investor locks; DAO/treasury.
Utility: Fees; access; staking; LSTs; restaking (protocol-specific); governance.
Demand levers (examples): incentives, burns, buyback-and-burn, liquidity mining, buybacks—verify in docs and contracts.
Governance: Token voting exists on a spectrum; not always fully decentralized.
Caveats
Labels and clusters can be wrong; correlation ≠ causation; past patterns ≠ future prices.