Long-Term Holder (LTH)

What Is a Long-Term Holder?

A long-term holder (LTH) is an on-chain analytics classification developed by Glassnode to identify Bitcoin entities whose coins have remained unspent for more than 155 days. The concept was first formalized in Glassnode's October 2020 research paper "Quantifying Short-Term and Long-Term Holder Bitcoin Supply," which established a statistically rigorous boundary between active market participants and committed holders.

The complementary classification is the short-term holder (STH): an entity whose coins have been held for fewer than 155 days. STH coins are statistically more likely to be re-spent, making them a more liquid and active portion of the supply. Together, the LTH/STH framework divides the entire circulating Bitcoin supply into two behaviorally distinct cohorts that move in opposition across market cycles.

The distinction matters because LTH behavior is one of the strongest signals available for understanding where Bitcoin sits in its market cycle. When long-term holders accumulate, they remove supply from active circulation. When they distribute, they inject supply back into the market. These dynamics are measurable on-chain with precision that traditional financial markets lack entirely.

How It Works

The 155-Day Threshold

The 155-day boundary is not arbitrary: it comes from empirical analysis of UTXO spending probability curves. Glassnode researchers measured how likely a UTXO is to be spent at each day of its lifespan and found a power-law relationship: for every tenfold increase in a coin's age, its probability of being spent decreases by approximately a factor of ten. The regression fit achieved an R-squared of 0.995.

Within the first 155 days, spending probability declines rapidly in an exponential pattern. After 155 days, the curve flattens and converges with the near-constant (very low) spending rates observed for coins older than one year. The researchers identified 155 days as the precise inflection point by comparing spending probability slopes across age cohorts.

To illustrate the spending decay:

Once a coin survives 155 days without being spent, it has crossed from the high-turnover zone into the low-probability zone. Statistically, it behaves like a coin that has been held for a year or more.

Classification Mechanism

Glassnode's LTH classification is entity-adjusted, not based on raw addresses or individual UTXOs. Entities are clusters of addresses estimated to be controlled by the same actor, identified through clustering heuristics. A single user with ten addresses is treated as one entity, not ten separate holders.

Rather than applying a hard cutoff at exactly 155 days, the system uses a logistic (sigmoid) function to create a smooth transition:

• At 155 days: an entity's balance contributes 50% to LTH supply and 50% to STH supply
• At approximately 177 days: 90% is attributed to LTH supply
• At approximately 200 days: the transition reaches 99%, effectively complete

This smooth transition prevents abrupt reclassification of large balances. The system also uses volume-weighted averaging for mixed balances: if a long-term holder acquires a small amount of new coins, the heavy weight of their older balance keeps the entity classified as LTH. Bitcoin held on exchanges is excluded entirely, since exchange addresses represent custodial pools rather than individual holder behavior.

Key LTH Metrics

LTH Supply

LTH Supply measures the total amount of BTC held by entities classified as long-term holders. It is the broadest measure of conviction in the Bitcoin market. As of mid-2026, LTH supply sits near all-time highs at approximately 79% of circulating supply, representing roughly 15 to 16.6 million BTC depending on the measurement date.

LTH supply rises during bear markets as coins age past the 155-day threshold without being spent. It falls during bull markets as long-term holders sell into strength, transferring coins to new short-term holders. The rate of change in LTH supply is as informative as the absolute level: a rapid decline signals active distribution, while steady growth signals deep accumulation.

LTH-SOPR

The Spent Output Profit Ratio for long-term holders (LTH-SOPR) measures the profit ratio of outputs that were held for 155+ days before being spent. The formula divides the realized value of spent outputs at the time of spending by their value at the time of creation.

LTH-SOPR = Σ(value at time of spend) / Σ(value at time of creation)

// LTH-SOPR > 1.0 → long-term holders selling at a profit
// LTH-SOPR = 1.0 → break-even (often acts as support in bull markets)
// LTH-SOPR < 1.0 → long-term holders selling at a loss (capitulation)

LTH-SOPR has distinctive amplitude compared to aggregate SOPR. Because long-held coins carry enormous unrealized gains during bull markets, LTH-SOPR can reach double or even triple-digit values at cycle peaks. Conversely, when LTH-SOPR drops below 1.0, it marks periods of capitulation that have historically coincided with major market bottoms.

HODL Waves

HODL Waves present the age distribution of the entire Bitcoin supply as a stacked area chart, with coins grouped into twelve age bands ranging from less than one day to more than ten years. Originally coined by Dhruv Bansal of Unchained Capital in 2018, the visualization uses warmer colors (red, orange) for recently moved coins and cooler colors (green, blue) for long-dormant coins.

While HODL Waves and LTH supply are separate metrics, they are conceptually linked. The bands from six months onward broadly correspond to LTH territory. A "HODL wave" manifests when a large volume of Bitcoin transacts near a price peak, creating a surge in young coin bands, then slowly ages into each successive band as holders refuse to sell. The Realized Cap HODL Waves variant weights each band by the USD value at which coins last moved, revealing the economic significance of each age cohort rather than just the coin count.

LTH Cost Basis and MVRV

The LTH Realized Price represents the average on-chain cost basis of the long-term holder cohort: the volume-weighted price at which all LTH coins last moved. As of mid-2026, this figure sits near $50,000. The LTH-MVRV ratio (market price divided by LTH Realized Price) shows the aggregate unrealized profit multiple for the cohort.

When LTH-MVRV is elevated, long-term holders carry large unrealized gains and have increasing incentive to sell. When it approaches or drops below 1.0, long-term holders are near break-even or underwater, meaning selling pressure from this cohort is minimal. This dynamic makes the LTH Realized Price a historically strong support level during corrections.

Use Cases

Market Cycle Analysis

The primary use case for LTH metrics is identifying where Bitcoin sits in its market cycle. The LTH/STH dynamic follows a predictable pattern:

1. Accumulation phase: LTH supply increases as holders buy at depressed prices or simply hold through downturns, reducing active supply
2. Price floor establishment: reduced selling pressure from LTHs establishes support levels, with LTH Realized Price acting as strong support
3. Distribution phase: as prices rise significantly, LTHs begin selling, LTH supply declines, and LTH-SOPR rises above 1.0
4. Cycle peak: LTH distribution accelerates, LTH-NUPL reaches euphoric levels, and supply transfers from experienced holders to newer market participants

The LTH/STH supply ratio has preceded every major Bitcoin cycle turning point since 2011. For deeper analysis of whether these patterns still hold, see Is Bitcoin's Four-Year Cycle Dead?

Accumulation and Distribution Signals

Traders and analysts monitor LTH behavior for early signals of trend changes. Rising LTH supply during a price decline suggests that experienced holders view current prices as attractive: a bullish signal. Declining LTH supply during a price rally suggests that experienced holders are taking profits: a potential warning of an approaching top.

The Coin Days Destroyed metric complements LTH analysis by measuring the economic weight of spending activity. When old coins move, they destroy accumulated coin days, producing spikes that often align with LTH distribution events.

Institutional and ETF Analysis

Since the launch of spot Bitcoin ETFs in early 2024, LTH metrics have gained new significance. ETFs act as large-scale absorbers of LTH distribution, creating a demand sink that did not exist in prior cycles. Spot ETFs and corporate treasury buyers have absorbed roughly 57% of the increase in short-term holder supply since early 2024. This structural shift means LTH distribution may occur "heavier and earlier" than in prior cycles without the same price impact, as institutional demand offsets selling pressure from long-term holders.

Risks and Considerations

Entity Clustering Limitations

Because LTH classification relies on entity clustering heuristics, the metrics are inherently probabilistic. Glassnode acknowledges that entity-based metrics are mutable: established history is stable, but recent data points may revise as clustering algorithms improve. Analysts should treat LTH metrics as strong approximations rather than exact measurements.

Exchange and Custodial Blind Spots

Coins held on exchanges are excluded from LTH/STH supply calculations because exchange addresses represent custodial pools. However, this means that a user who deposits Bitcoin on an exchange and holds it there for years is not counted as a long-term holder. Similarly, coins held by ETF custodians may not be classified the same way as self-custodied coins, potentially understating true long-term conviction.

Past Performance Caveat

While LTH supply cycles have aligned with Bitcoin price cycles historically, this is an empirical observation rather than a guaranteed relationship. Structural changes to the market, such as the introduction of ETFs, the growth of Bitcoin ETFs, and the rise of institutional custody, may alter the traditional LTH distribution pattern. No on-chain metric should be used as a sole trading signal.

UTXO Model Dependency

LTH metrics as defined by Glassnode are specific to UTXO-based blockchains. The methodology tracks unspent transaction outputs and their age, which does not directly translate to account-model chains like Ethereum. While Glassnode has extended LTH/STH breakdowns to additional networks (Solana, BNB, Tron, and others as of 2025), the underlying methodology differs from the original Bitcoin-native approach.

This glossary entry is for informational purposes only and does not constitute financial or investment advice. Always do your own research before using any protocol or technology.