URPD_NonLog_N_LTH
Tech spec
| Field | Value |
|---|---|
| API name (slug) | urpd_nonlog_lth_n |
| Group | utxo distributions |
| Unit / Valuetype | count / other |
| Shape | binned |
| Resolutions | h1, h4, h8, h12, d1 |
| Endpoints | /v2/utxo_distributions |
| Tier | 2 |
| Last updated | 2025-08-19 19:05 UTC |
| Docs | Open in Swagger |
Brief Description: UTXO Realized Price Distribution (Cost Basis) of investors in linear scale buckets based on BTC.
The URPD_NonLog_N_LTH belongs to a family of on-chain metrics that delineates the distribution of Unspent Transaction Outputs (UTXOs) based on the realized price at the time of their creation. These metrics collectively offer a snapshot of distribution at a specific instance, encapsulated under the term URPD. URPD is short for UTXO Realized Price Distribution.
The URPD family also encompasses these cohorts:
- _lth: restricted to the Long Term Hodler cohort (aged 155+ days).
- _sth: _lth: restricted to the Long Term Hodler cohort (aged less than 155 days)
Metric variants
The buckets are broken down into these metrics
- _N: The count of UTXOs.
- _realized_value: The (cost-basis) value in USD
- _supply_btc: The value (supply) in BTC.
Interpretation Deciphering the URPD_NonLog_N_LTH metrics can offer valuable insights into market sentiment. For example, a dense concentration of UTXOs at specific price levels may indicate robust buying or selling activity at these points, potentially signifying support or resistance levels. Additionally, these metrics can reveal the average cost basis of investors, offering predictions about potential selling pressure as market prices near these levels, due either to investors reaching a break-even point or realizing profits.
Advanced Explanation Broadly, the realized price can be perceived as the cost-price of a UTXO, albeit this is not an absolute interpretation. Technically, the realized price is the spot price at the moment the UTXO was last moved on-chain, which may not coincide with economically significant events such as purchases or sales.
A log-scale chart's price range buckets expand proportionally with the price. This allows for a more nuanced analysis of price distributions at lower levels and a wider perspective at higher levels. The utility of this scaling lies in its representation of percentage changes in price, a metric often more pertinent to traders and investors than absolute price changes. Consequently, log-scale are generally preferred over non-log.