Point-In-Time
Accumulation Addresses
GET https://api.glassnode.com/v1/metrics/addresses/accumulation_count_pit
The number of unique accumulation addresses. Accumulation addresses are defined as addresses that have at least 2 incoming non-dust transfers and have never spent funds. Exchange addresses and addresses receiving from coinbase transactions (miner addresses) are discarded. To account for lost coins, addresses that were last active more than 7 years ago are omitted as well.
This is the Point-in-Time (PiT) variant of Accumulation Addresses. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Accumulation Balance
GET https://api.glassnode.com/v1/metrics/addresses/accumulation_balance_pit
The total amount of funds held in accumulation addresses. Accumulation addresses are defined as addresses that have at least 2 incoming non-dust transfers and have never spent funds. Exchange addresses and addresses receiving from coinbase transactions (miner addresses) are discarded. To account for lost coins, addresses that were last active more than 7 years ago are omitted as well.
This is the Point-in-Time (PiT) variant of Accumulation Balance. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
c | string | currency: NATIVE, USD |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Accumulation Trend Score
GET https://api.glassnode.com/v1/metrics/indicators/accumulation_trend_score_pit
The Accumulation Trend Score is an indicator that reflects the relative size of entities that are actively accumulating coins on-chain in terms of their BTC holdings. The scale of the Accumulation Trend Score represents both the size of the entities balance (their participation score), and the amount of new coins they have acquired/sold over the last month (their balance change score). An Accumulation Trend Score of closer to 1 indicates that on aggregate, larger entities (or a big part of the network) are accumulating, and a value closer to 0 indicates they are distributing or not accumulating. This provides insight into the balance size of market participants, and their accumulation behavior over the last month. For more information see the metric description in Glassnode Academy.
This is the Point-in-Time (PiT) variant of Accumulation Trend Score. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Active Entities
GET https://api.glassnode.com/v1/metrics/entities/active_count_pit
The number of unique entities that were active either as a sender or receiver. Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Active Entities. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Asia Year-over-Year Supply Change
GET https://api.glassnode.com/v1/metrics/supply/apac_1y_supply_change_pit
This metric aims at giving an estimate for the year-over-year change in the share of the Bitcoin supply to be held/traded in Asia.
Geolocation of Bitcoin supply is performed probabilistically at the entity level. The timestamps of all transactions created by an entity are correlated with the working hours of different geographical regions to determine the probabilities for each entity being located in the US, Europe, or Asia. Working hours are defined as:
US: 8am to 8pm Eastern Time (13:00-01:00 UTC)
EU: 8am to 8pm Central European Time (07:00-19:00 UTC)
Asia: 8am to 8pm China Standard Time (00:00-12:00 UTC)
An entity's balance will only contribute to the supply in the respective region if the location can be determined with a high certainty. Supply held on exchanges wallets are excluded.
This is the Point-in-Time (PiT) variant of Asia Year-over-Year Supply Change. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Bridges Deposits By Chain
GET https://api.glassnode.com/v1/metrics/bridges/deposits_by_chain_pit
This metric measures the USD value which is deposited into bridge smart contracts on Ethereum, and is therefore flowing out of the Ethereum blockchain, and into target blockchains. Deposit Volume is computed daily by multiplying the number of tokens deposited into bridges by the latest daily price of each token.
Bridges are protocols that enable digital assets to be transferred from one blockchain to another. When an asset is transferred out of Ethereum, it gets deposited and locked into a bridge smart contract. When the asset is transferred back to Ethereum, it is withdrawn and released from the smart contract.
This metric only includes bridge contracts on the Ethereum side. The bridges included in this metric cover bridge deposits into both L1 and L2 blockchains, providing information on the value transferred to both L1 competitors, and L2 scaling solutions. Each bridge included in this metric represents a single blockchain, except the ones labeled as multichain. That label is used to represent bridges that allow transferring assets across multiple different chains.
This is the Point-in-Time (PiT) variant of Bridges Deposits By Chain. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: ETH |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Bridges Net Flow By Chain
GET https://api.glassnode.com/v1/metrics/bridges/net_volume_by_chain_pit
This metric shows the net USD value flowing into, or out of Ethereum bridge smart contracts, calculated as bridge deposits minus bridge withdrawals. It can also be considered to represent the net USD value flowing in, or out of the Ethereum blockchain via bridges. A positive value means that there is more value being deposited into bridges, which translates into a net value outflow from Ethereum. On the other hand, a negative value means that there is more USD value being withdrawn from bridges, which translates into more USD value flowing back into Ethereum.
Bridges are protocols that enable digital assets to be transferred from one blockchain to another. When an asset is transferred out of Ethereum, it gets deposited and locked into a bridge smart contract. When the asset is transferred back to Ethereum, it is withdrawn and released from the smart contract.
This metric only includes bridge contracts on the Ethereum side. The bridges included in this metric cover bridge deposits into both L1 and L2 blockchains, providing information on the value transferred to both L1 competitors, and L2 scaling solutions. Each bridge included in this metric represents a single blockchain, except the ones labeled as multichain. That label is used to represent bridges that allow transferring assets across multiple different chains.
This is the Point-in-Time (PiT) variant of Bridges Net Flow By Chain. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: ETH |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Bridges Transactions (Absolute)
GET https://api.glassnode.com/v1/metrics/transactions/transfers_count_bridges_pit
The number of transactions (transaction count) in the Ethereum network by contracts that allow transfer of tokens between different blockchains.
This is the Point-in-Time (PiT) variant of Bridges Transactions (Absolute). PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: ETH |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Bridges Transactions (Relative)
GET https://api.glassnode.com/v1/metrics/transactions/transfers_count_bridges_relative_pit
The relative amount (share) of transactions in the Ethereum network by contracts that allow transfer of tokens between different blockchains.
This is the Point-in-Time (PiT) variant of Bridges Transactions (Relative). PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: ETH |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Bridges TVL
GET https://api.glassnode.com/v1/metrics/bridges/total_value_locked_by_chain_pit
The Total Value Locked (TVL) in bridges measures the total USD value that is locked within the Ethereum side of bridge smart contracts. Locked tokens are not available on the Ethereum chain, but are available on the target blockchains. An increasing TVL means that value is flowing out of Ethereum and into other target blockchains, whilst a decreasing TVL means the value is flowing back into Ethereum. Bridge TVL is computed daily, by multiplying the number of tokens locked within the bridge smart contracts, by the latest daily price for each token.
Bridges are protocols that enable digital assets to be transferred from one blockchain to another. When an asset is transferred out of Ethereum, it gets deposited and locked into a bridge smart contract. When the asset is transferred back to Ethereum, it is withdrawn and released from the smart contract.
This metric only includes bridge contracts on the Ethereum side. The bridges included in this metric cover bridge deposits into both L1 and L2 blockchains, providing information on the value transferred to both L1 competitors, and L2 scaling solutions. Each bridge included in this metric represents a single blockchain, except the ones labeled as multichain. That label is used to represent bridges that allow transferring assets across multiple different chains.
This is the Point-in-Time (PiT) variant of Bridges TVL. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: ETH |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Bridges TVL Relative
GET https://api.glassnode.com/v1/metrics/bridges/total_value_locked_by_chain_relative_pit
This metric presents the Relative Total Value Locked (TVL dominance) of each target blockchain bridge compared to the total TVL across all bridges. A rising relative TVL indicates that the target blockchain is growing in USD denominated TVL dominance compared to the others (and vice versa). Bridge TVL is computed daily, by multiplying the number of tokens locked within the bridge smart contract, by the latest daily price of each token. Relative TVL is then computed by dividing the TVL of each bridge by the total TVL across all bridges.
Bridges are protocols that enable digital assets to be transferred from one blockchain to another. When an asset is transferred out of Ethereum, it gets deposited and locked into a bridge smart contract. When the asset is transferred back to Ethereum, it is withdrawn and released from the smart contract.
This metric only includes bridge contracts on the Ethereum side. The bridges included in this metric cover bridge deposits into both L1 and L2 blockchains, providing information on the value transferred to both L1 competitors, and L2 scaling solutions. Each bridge included in this metric represents a single blockchain, except the ones labeled as multichain. That label is used to represent bridges that allow transferring assets across multiple different chains.
This is the Point-in-Time (PiT) variant of Bridges TVL Relative. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: ETH |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Bridges Withdrawals By Chain
GET https://api.glassnode.com/v1/metrics/bridges/withdrawals_by_chain_pit
This metric measures the USD value which is withdrawn from bridge smart contracts on Ethereum, and is therefore flowing into the Ethereum blockchain, and out of target blockchains. Withdrawal Volume is computed daily by multiplying the number of tokens withdrawn from bridges by the latest daily price of each token.
Bridges are protocols that enable digital assets to be transferred from one blockchain to another. When an asset is transferred out of Ethereum, it gets deposited and locked into a bridge smart contract. When the asset is transferred back to Ethereum, it is withdrawn and released from the smart contract.
This metric only includes bridge contracts on the Ethereum side. The bridges included in this metric cover bridge deposits into both L1 and L2 blockchains, providing information on the value transferred to both L1 competitors, and L2 scaling solutions. Each bridge included in this metric represents a single blockchain, except the ones labeled as multichain. That label is used to represent bridges that allow transferring assets across multiple different chains.
This is the Point-in-Time (PiT) variant of Bridges Withdrawals By Chain. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: ETH |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Coinjoin Output Count
GET https://api.glassnode.com/v1/metrics/transactions/transfers_from_coinjoins_count_pit
The total count of indistinguishable outputs in coinjoin transactions. The metric is an aggregate of different coinjoin providers. Note that coinjoin metrics rely on heuristics and statistical information that change over time. Therefore these metrics are mutable – the data is stable, but especially most recent data points are subject to slight fluctuations as time progresses.
This is the Point-in-Time (PiT) variant of Coinjoin Output Count. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Coinjoin Output Volume
GET https://api.glassnode.com/v1/metrics/transactions/transfers_volume_from_coinjoins_sum_pit
The total amount of indistinguishable outputs in coinjoin transactions, i.e. the volume of coins mixed by different coinjoin providers. Note that coinjoin metrics rely on heuristics and statistical information that change over time. Therefore these metrics are mutable – the data is stable, but especially most recent data points are subject to slight fluctuations as time progresses.
This is the Point-in-Time (PiT) variant of Coinjoin Output Volume. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
c | string | currency: USD, NATIVE |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
DeFi Transactions (Absolute)
GET https://api.glassnode.com/v1/metrics/transactions/transfers_count_defi_pit
The number of transactions (transaction count) in the Ethereum network by on-chain financial instruments and protocols implemented as smart contracts, including decentralized exchanges (DEXs).
This is the Point-in-Time (PiT) variant of DeFi Transactions (Absolute). PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: ETH |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
DeFi Transactions (Relative)
GET https://api.glassnode.com/v1/metrics/transactions/transfers_count_defi_relative_pit
The relative amount (share) of transactions in the Ethereum network by on-chain financial instruments and protocols implemented as smart contracts, including decentralized exchanges (DEXs).
This is the Point-in-Time (PiT) variant of DeFi Transactions (Relative). PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: ETH |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Depositing Addresses
GET https://api.glassnode.com/v1/metrics/addresses/sending_to_exchanges_count_pit
The number of unique addresses that appeared as a sender in a transaction sending funds to exchanges.
This is the Point-in-Time (PiT) variant of Depositing Addresses. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol (see list below for more details) |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 10m, 1h, 24h, 1w, 1month |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Supported asset symbols: BTC, ETH, 1INCH, AAVE, ABT, AMP, AMPL, ANT, APE, BADGER, BAL, BAND, BAT, BNT, BOBA, BOND, BORG, BUSD, CAKE, CELR, COMP, CREAM, CRO, CRV, CVC, CVP, CVX, CVXCRV, DAI, DDX, DENT, DHT, DODO, DPI, DRGN, ELF, ENG, ENJ, ETHDYDX, EURS, FET, FLX, FRAX, FTM, FTT, FUN, FXS, GNO, GUSD, HEGIC, HOT, HT, HUSD, IMX, INDEX, KCS, LAMB, LBA, LDO, LEO, LINK, LOOM, LRC, MANA, MATIC, MCB, METIS, MIR, MKR, MLN, MTA, MTL, NDX, NEXO, NFTX, NMR, Nsure, OCEAN, OKB, OMG, PAY, PERP, PICKLE, PNK, PNT, POLY, POWR, PPT, PYUSD, QASH, QKC, QNT, RAI, RDN, REN, REP, rETH, RLC, ROOK, RPL, RSR, SAND, SFRXETH, SHIB, SNT, SNX, SSV, STAKE, stETH, STORJ, sUSD, SUSHI, TEL, TUSD, UBT, UMA, UNI, USDC, USDD, USDK, USDP, USDT, UTK, VERI, WBTC, WETH, wNXM, YAM, YFI, ZRX
Entities Net Growth
GET https://api.glassnode.com/v1/metrics/entities/net_growth_count_pit
The net growth of unique entities in the network. This metric is defined as the difference between new entities and "disappearing" entities (entities with a zero balance that had a non–zero balance at the previous timestamp). Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
The computation of this metric requires statistical information from several days, and is therefore only available with a lag of one week.
This is the Point-in-Time (PiT) variant of Entities Net Growth. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entities Supply Distribution
GET https://api.glassnode.com/v1/metrics/entities/supply_distribution_relative_pit
Relative distribution of the circulating supply held by entities with specific balance bands.
This is the Point-in-Time (PiT) variant of Entities Supply Distribution. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity- and Supply-Adjusted CYD
GET https://api.glassnode.com/v1/metrics/indicators/cyd_account_based_supply_adjusted_pit
Coin Years Destroyed (CYD) is defined as the 365 day rolling sum of Coin Days Destroyed (CDD), and shows the amount of coin days that have been destroyed over the past year. It is indicative of long-term holder behaviour. This version is entity-adjusted, meaning that transactions within addresses controlled by the same network participant are discarded (see this article for more information), as well as supply-adjusted to account for the increasing baseline of the metric over time. This metric was first put forward by ARK Invest and further developed by Glassnode by adjusting for the circulating supply.
This is the Point-in-Time (PiT) variant of Entity- and Supply-Adjusted CYD. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted 90D Coin Days Destroyed (eCDD-90)
GET https://api.glassnode.com/v1/metrics/indicators/cdd90_account_based_age_adjusted_pit
90D Coin Days Destroyed is the 90 day rolling sum of Coin Days Destroyed (CDD) and shows the amount of coin days that have been destroyed over the past year. This version is entity-adjusted, meaning that transactions within addresses controlled by the same network participant are discarded (see this article for more information), as well as age-adjusted meaning that we normalize by time in order to account for the increasing baseline as time goes by.
This is the Point-in-Time (PiT) variant of Entity-Adjusted 90D Coin Days Destroyed (eCDD-90). PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted ASOL
GET https://api.glassnode.com/v1/metrics/indicators/asol_account_based_pit
Entity-adjusted ASOL is an improved variant of ASOL that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted ASOL therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted ASOL. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted CDD
GET https://api.glassnode.com/v1/metrics/indicators/cdd_account_based_pit
Entity-adjusted CDD is an improved variant of CDD that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted CDD therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted CDD. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted CYD
GET https://api.glassnode.com/v1/metrics/indicators/cyd_account_based_pit
Coin Years Destroyed (CYD) is defined as the 365 day rolling sum of Coin Days Destroyed (CDD), and shows the amount of coin days that have been destroyed over the past year. It is indicative of long-term holder behaviour. This version is entity-adjusted, meaning that transactions within addresses controlled by the same network participant are discarded (see this article for more information). This metric was first put forward by ARK Invest.
This is the Point-in-Time (PiT) variant of Entity-Adjusted CYD. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Dormancy
GET https://api.glassnode.com/v1/metrics/indicators/dormancy_account_based_pit
Entity-adjusted Dormancy is an improved variant of Average Coin Dormancy that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted Dormancy therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Dormancy. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Dormancy Flow
GET https://api.glassnode.com/v1/metrics/indicators/dormancy_flow_pit
Entity-adjusted Dormancy Flow is the ratio of the current market capitalization and the annualized dormancy value (measured in USD). Entity-adjusted Dormancy Flow can be used to time market lows and assess whether the bull market remains in relatively normal conditions. It helps confirm whether Bitcoin is in a bullish or bearish primary trend. This metric was put forward by David Puell. For more information please read his introductory article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Dormancy Flow. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Liveliness
GET https://api.glassnode.com/v1/metrics/indicators/liveliness_account_based_pit
Entity-adjusted Liveliness is an improved variant of Liveliness that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted Liveliness therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Liveliness. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Long-Term Holder ASOL
GET https://api.glassnode.com/v1/metrics/indicators/asol_lth_account_based_pit
Long-Term Holder variant of Entity-Adjusted ASOL. Average Spent Output Lifespan (ASOL) is the average age (in days) of spent transaction outputs. Transactions between addresses of the same entity ("in-house" transactions) are discarded. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Long-Term Holder ASOL. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Long-Term Holder CDD
GET https://api.glassnode.com/v1/metrics/indicators/cdd_lth_account_based_pit
Long-Term Holder variant of Entity-Adjusted CDD. Coin Days Destroyed (CDD) for any given transaction is calculated by taking the number of coins in a transaction and multiplying it by the number of days it has been since those coins were last spent. Transactions between addresses of the same entity ("in-house" transactions) are discarded. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Long-Term Holder CDD. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Long-Term Holder Dormancy
GET https://api.glassnode.com/v1/metrics/indicators/dormancy_lth_account_based_pit
Long-Term Holder variant of Entity-Adjusted Dormancy. Dormancy is the average number of days destroyed per coin transacted, and is defined as the ratio of coin days destroyed and total transfer volume. Transactions between addresses of the same entity ("in-house" transactions) are discarded. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Long-Term Holder Dormancy. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted LTH Realized Loss
GET https://api.glassnode.com/v1/metrics/indicators/realized_loss_lth_account_based_pit
Entity-Adjusted variant of Realized Loss for Long-Term Holders, which denotes the total profit (in USD) of all moved coins whose price at their last movement was lower than the price at the current movement. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Volume transferred between addresses owned by the same entity cluster is excluded. As such, no value is realized during internal or “in-house” transfers.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted LTH Realized Loss. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted LTH Realized Loss to Exchanges
GET https://api.glassnode.com/v1/metrics/indicators/realized_loss_lth_to_exchanges_account_based_pit
Entity-Adjusted variant of Realized Loss for coins that are sent from Long-Term Holders to exchanges. Realized loss denotes the total loss (in USD) of all moved coins whose price at their last movement was higher than the price at the current movement. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
Note that exchange metrics are based on our labeled data of exchange addresses that we constantly keep updating, as well as data science techniques and statistical information that changes over time. Therefore these metrics are mutable – the data is stable, but especially most recent data points are subject to slight fluctuations as time progresses.
This is the Point-in-Time (PiT) variant of Entity-Adjusted LTH Realized Loss to Exchanges. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted LTH Realized Profit
GET https://api.glassnode.com/v1/metrics/indicators/realized_profit_lth_account_based_pit
Entity-Adjusted variant of Realized Profit for Long-Term Holders, which denotes the total profit (in USD) of all moved coins whose price at their last movement was lower than the price at the current movement. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Volume transferred between addresses owned by the same entity cluster is excluded. As such, no value is realized during internal or “in-house” transfers.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted LTH Realized Profit. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted LTH Realized Profit to Exchanges
GET https://api.glassnode.com/v1/metrics/indicators/realized_profit_lth_to_exchanges_account_based_pit
Entity-Adjusted variant of Realized Profit for coins that are sent from Long-Term Holders to exchanges. Realized profit denotes the total profit (in USD) of all moved coins whose price at their last movement was lower than the price at the current movement. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
Note that exchange metrics are based on our labeled data of exchange addresses that we constantly keep updating, as well as data science techniques and statistical information that changes over time. Therefore these metrics are mutable – the data is stable, but especially most recent data points are subject to slight fluctuations as time progresses.
This is the Point-in-Time (PiT) variant of Entity-Adjusted LTH Realized Profit to Exchanges. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted LTH Transfer Volume
GET https://api.glassnode.com/v1/metrics/transactions/transfers_volume_entity_adjusted_from_lth_sum_pit
The total estimated amount of coins moved by long-term holders. Volume transferred within addresses of the same entity is excluded. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted LTH Transfer Volume. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
c | string | currency: NATIVE, USD |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted LTH Transfer Volume in Loss
GET https://api.glassnode.com/v1/metrics/transactions/transfers_volume_entity_adjusted_from_lth_loss_sum_pit
The total estimated amount of coins moved by long-term holders in loss. Volume transferred within addresses of the same entity is excluded. Coins are considered to be in loss when the price at the time the coins are spent is lower than the entity's average on-chain acquisition price for its funds. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted LTH Transfer Volume in Loss. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
c | string | currency: NATIVE, USD |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted LTH Transfer Volume in Profit
GET https://api.glassnode.com/v1/metrics/transactions/transfers_volume_entity_adjusted_from_lth_profit_sum_pit
The total estimated amount of coins moved by long-term holders in profit. Volume transferred within addresses of the same entity is excluded. Coins are considered to be in profit when the price at the time the coins are spent is higher than the entity's average on-chain acquisition price for its funds. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted LTH Transfer Volume in Profit. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
c | string | currency: NATIVE, USD |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted LTH-NUPL
GET https://api.glassnode.com/v1/metrics/indicators/nupl_more_155_account_based_pit
Entity-adjusted LTH-NUPL is an improved variant of Long-Term Holders Net Unrealized Profit/Loss (LTH-NUPL) that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted LTH NUPL therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article. An entity is considered as a Long-Term Holder if the time since its averaged purchasing date is more than 155 days.
This is the Point-in-Time (PiT) variant of Entity-Adjusted LTH-NUPL. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted LTH/STH Transfer Volume in Profit/Loss
GET https://api.glassnode.com/v1/metrics/transactions/transfers_volume_entity_adjusted_from_lth_sth_profit_loss_relative_pit
The relative amount of coins moved by by long- and short-term holders in profit/loss. Volume transferred within addresses of the same entity is excluded. Coins are considered to be in profit/loss when the price at the time the coins are spent is higher/lower than the entity's average on-chain acquisition price for its funds. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted LTH/STH Transfer Volume in Profit/Loss. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted MSOL
GET https://api.glassnode.com/v1/metrics/indicators/msol_account_based_pit
Entity-adjusted MSOL is an improved variant of MSOL that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted MSOL therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted MSOL. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted MVRV
GET https://api.glassnode.com/v1/metrics/indicators/mvrv_account_based_pit
Entity-adjusted MVRV is an improved variant of MVRV Ratio that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted MVRV therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted MVRV. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted NUPL
GET https://api.glassnode.com/v1/metrics/indicators/net_unrealized_profit_loss_account_based_pit
Entity-adjusted NUPL is an improved variant of Net Unrealized Profit/Loss (NUPL) that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted NUPL therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted NUPL. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted NVT
GET https://api.glassnode.com/v1/metrics/indicators/nvt_entity_adjusted_pit
The Network Value to Transactions (NVT) Ratio is computed by dividing the market cap by the transferred on-chain volume measured in USD. This entity-adjusted version of the NVT Ratio uses entity-adjusted on-chain volume and is therefore more accurate as it accounts for actual economic throughput.
This is the Point-in-Time (PiT) variant of Entity-Adjusted NVT. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h, 1h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Realized Cap
GET https://api.glassnode.com/v1/metrics/indicators/rcap_account_based_pit
Entity-adjusted Realized Cap is an improved variant of Realized Cap that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted Realized Cap therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Realized Cap. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Realized Loss
GET https://api.glassnode.com/v1/metrics/indicators/realized_loss_account_based_pit
Entity-Adjusted variant of Realized Loss, which denotes the total profit (in USD) of all moved coins whose price at their last movement was lower than the price at the current movement.
Volume transferred between addresses owned by the same entity cluster is excluded. As such, no value is realized during internal or “in-house” transfers.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Realized Loss. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Realized Loss to Exchanges
GET https://api.glassnode.com/v1/metrics/indicators/realized_loss_to_exchanges_account_based_pit
Entity-Adjusted variant of Realized Loss for coins that are sent to exchanges. Realized loss denotes the total loss (in USD) of all moved coins whose price at their last movement was higher than the price at the current movement.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
Note that exchange metrics are based on our labeled data of exchange addresses that we constantly keep updating, as well as data science techniques and statistical information that changes over time. Therefore these metrics are mutable – the data is stable, but especially most recent data points are subject to slight fluctuations as time progresses.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Realized Loss to Exchanges. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Realized Profit
GET https://api.glassnode.com/v1/metrics/indicators/realized_profit_account_based_pit
Entity-Adjusted variant of Realized Profit, which denotes the total profit (in USD) of all moved coins whose price at their last movement was lower than the price at the current movement.
Volume transferred between addresses owned by the same entity cluster is excluded. As such, no value is realized during internal or “in-house” transfers.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Realized Profit. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Realized Profit to Exchanges
GET https://api.glassnode.com/v1/metrics/indicators/realized_profit_to_exchanges_account_based_pit
Entity-Adjusted variant of Realized Profit for coins that are sent to exchanges. Realized profit denotes the total profit (in USD) of all moved coins whose price at their last movement was lower than the price at the current movement.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
Note that exchange metrics are based on our labeled data of exchange addresses that we constantly keep updating, as well as data science techniques and statistical information that changes over time. Therefore these metrics are mutable – the data is stable, but especially most recent data points are subject to slight fluctuations as time progresses.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Realized Profit to Exchanges. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Short-Term Holder ASOL
GET https://api.glassnode.com/v1/metrics/indicators/asol_sth_account_based_pit
Short-Term Holder variant of Entity-Adjusted ASOL. Average Spent Output Lifespan (ASOL) is the average age (in days) of spent transaction outputs. Transactions between addresses of the same entity ("in-house" transactions) are discarded. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Short-Term Holder ASOL. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Short-Term Holder CDD
GET https://api.glassnode.com/v1/metrics/indicators/cdd_sth_account_based_pit
Short-Term Holder variant of Entity-Adjusted CDD. Coin Days Destroyed (CDD) for any given transaction is calculated by taking the number of coins in a transaction and multiplying it by the number of days it has been since those coins were last spent. Transactions between addresses of the same entity ("in-house" transactions) are discarded. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Short-Term Holder CDD. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Short-Term Holder Dormancy
GET https://api.glassnode.com/v1/metrics/indicators/dormancy_sth_account_based_pit
Short-Term Holder variant of Entity-Adjusted Dormancy. Dormancy is the average number of days destroyed per coin transacted, and is defined as the ratio of coin days destroyed and total transfer volume. Transactions between addresses of the same entity ("in-house" transactions) are discarded. Long- and Short-Term Holder supply is defined with respect to the entity's averaged purchasing date with weights given by a logistic function centered at an age of 155 days and a transition width of 10 days.
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Short-Term Holder Dormancy. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted SOPR
GET https://api.glassnode.com/v1/metrics/indicators/sopr_account_based_pit
Entity-adjusted SOPR is an improved variant of SOPR that discards transactions between addresses of the same entity ("in-house" transactions). Entity-adjusted SOPR therefore accounts for real economic activity only, and provides an improved market signal compared to its raw UTXO-based counterpart. For detailed information read this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted SOPR. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |
Entity-Adjusted Spent Volume Age Bands (SVAB)
GET https://api.glassnode.com/v1/metrics/indicators/svab_entity_adjusted_pit
Spent Volume Age Bands (SVAB) is a separation of the on-chain transfer volume based on the coins' age. Each band represents the percentage of spent volume that was previously moved within the time period denoted in the legend. This metric is entity-adjusted and discards transactions between addresses of the same entity ("in-house" transactions).
Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses. For more information see this article.
This is the Point-in-Time (PiT) variant of Entity-Adjusted Spent Volume Age Bands (SVAB). PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.
Query Parameters
| Name | Type | Description |
|---|---|---|
a* | string | asset symbol: BTC |
s | integer | since, unix timestamp |
u | integer | until, unix timestamp |
i | string | frequency interval: 24h |
f | string | format: JSON, CSV |
timestamp_format | string | timestamp format: unix or humanized (RFC 3339) |