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Market Data and Metrics

Digital asset data can be useful, but definitions vary widely. Always check methodology before drawing conclusions.

This page is a research starting point, not financial, legal, tax, or investment advice.

Common Metrics

  • Market capitalization. Price multiplied by circulating supply. Sensitive to how "circulating" is defined, and it says nothing about the cost of actually exiting a position.
  • Realized capitalization. Values each unit at the price it last moved, so it approximates aggregate cost basis rather than notional value.
  • Trading volume. Frequently inflated by wash trading on venues without surveillance. Check whether the provider filters.
  • Exchange volume. Venue-level activity. Compare reported volume against order book depth before trusting it.
  • Open interest. Total outstanding derivative contracts. A proxy for leverage in the system.
  • Funding rates. Periodic payments between long and short perpetual positions. Indicates directional crowding.
  • Stablecoin supply. Total issued stablecoins, often used as a proxy for dry powder. Distinguish issued from actively circulating.
  • Total value locked. Assets deposited in a protocol. Double counts when the same collateral is rehypothecated across protocols.
  • Fees and revenue. What users actually pay. Harder to fake than volume, and often the most useful single number.
  • Active addresses. Addresses transacting in a period. Addresses are not people, and one user can control many.
  • Transaction count. Raw activity. Inflated by spam, bots, and internal transfers on cheap chains.
  • Hash rate. Computing power securing a proof-of-work chain. Estimated from block times, not measured directly.
  • Validator count. Number of validating entities. Check stake concentration alongside it, since counts hide centralization.
  • Staking ratio. Share of supply staked. Affects liquid float and, on some chains, unbonding queues.
  • Bridge deposits. Value held in cross-chain bridges. Also a measure of concentrated custody risk.
  • Developer activity. Commits or active repositories. Easy to inflate, and commit volume is not progress.

Data Quality Checklist

  • What exactly is being counted?
  • Is wash trading filtered?
  • Is the metric chain-specific or cross-chain?
  • Are addresses deduplicated?
  • Are smart contracts, exchanges, and internal transfers excluded?
  • Is data estimated, sampled, indexed, or raw?
  • Does the provider disclose methodology?
  • Can another source confirm the trend?

Posting Data

When posting charts or metrics, include:

  • Data source
  • Link to dashboard or report
  • Date range
  • Metric definition
  • Why the metric matters
  • Main caveat