Unlike equities, where insider transactions are largely hidden until quarterly filings, every Bitcoin and Ethereum transaction is permanently visible on a public ledger. On-chain analysis mines that data for signals about supply, holder behavior, and conviction that price charts alone can't reveal.
Exchange Netflows
When large amounts of BTC flow onto exchanges, it often signals intent to sell (or to post collateral for leveraged trading). Sustained outflows to private wallets suggest accumulation and reduced near-term sell pressure, since coins moved to cold storage are typically held with a longer time horizon.
MVRV: Spotting Cycle Extremes
MVRV = Market Cap / Realized CapRealized cap values each coin at the price it last moved on-chain, effectively an aggregate cost basis for the entire network. An MVRV ratio above roughly 3.5 has historically coincided with market cycle tops (aggregate holders sitting on large unrealized profits, raising sell incentive), while readings below 1 have marked capitulation-driven cycle bottoms (holders underwater on average).
SOPR: Profit-Taking in Real Time
SOPR compares the price a coin sold at on-chain to the price it was acquired at. A SOPR reading above 1 means coins are moving at a profit on average; below 1 means at a loss. In healthy bull trends, SOPR tends to hold above 1 and bounce off it on dips — a break below 1 during an uptrend has often flagged a short-term local top.
| Metric | What it captures |
|---|---|
| Exchange netflow | Near-term selling/buying pressure |
| MVRV | Cycle-level over/undervaluation |
| SOPR | Real-time realized profit/loss behavior |
| Active addresses | Network usage and organic demand trend |
Exchange labeling is imperfect (some wallets are mislabeled or unlabeled), and on-chain metrics tend to lag or lead price by days to weeks, not minutes. Use them to frame the macro backdrop, not to time individual entries.
Where to Find This Data
Platforms like Glassnode, CryptoQuant, and Nansen aggregate and visualize on-chain metrics without requiring you to run a node or parse raw transaction data yourself, making this analysis accessible even without a technical background.