Market Value to Realized Value (MVRV) is the ratio of Bitcoin's market cap to its realized cap — equivalently, spot price divided by Realized price. Introduced by Murad Mahmudov and David Puell in 2018, it is the most widely-cited single on-chain cycle-positioning metric and reads as "how far above (or below) its aggregate cost basis is the network currently trading?" The Z-score variant normalizes the metric across cycles and is operationally more useful for cross-cycle comparison. Historically, bull-cycle peaks have reached 3.5-4× (2013, 2017, 2021) and bear troughs 0.7-0.8× (2015, 2018-2019, 2022) — a roughly 5× peak-to-trough range that constitutes the primary cycle-positioning signal in contemporary on-chain work. Cohort-specific variants (LTH MVRV, STH MVRV; see Long-term vs short-term holder behavior) refine the aggregate signal, and MVRV is foundational to James Check's framework and to nearly every serious cycle analysis in the contemporary literature.
Why this note matters
MVRV is the flagship on-chain cycle-positioning metric. Three load-bearing roles:
- It is the most-cited on-chain metric in serious analytical work. Sustained Bitcoin on-chain commentary from the past five years (Check’s Week On-Chain archive, Ryan’s On-Chain Mind, Glassnode reports, BitMEX Research) leans on MVRV repeatedly as the primary cycle-positioning reference.
- It operationalizes Realized price for decision-making. Realized price is foundational but not itself a decision-ready signal; MVRV converts the price-to-cost-basis relationship into a ratio whose extremes have empirical regularities across cycles.
- It is the bridge to cohort analysis. The aggregate is the foundational form; the cohort-specific variants (LTH MVRV, STH MVRV) extend the framework to capture cohort-specific behavior and are operationally more informative.
The metric has flaws — discussed below — but its centrality to contemporary on-chain analysis is genuine. The questions are how to weight it, how to interpret extremes, and how to integrate it with cohort variants and macro context.
What this metric measures
The conceptual claim. MVRV measures how far above its aggregate cost basis the Bitcoin network is currently trading. Equivalent framings:
- “What ratio of unrealized profit is embedded in the current price?”
- “By what multiple has the average holder’s position appreciated since acquisition?”
- “How over- or under-valued is Bitcoin relative to where its holders actually paid?”
These framings are all equivalent to the same ratio: market cap ÷ realized cap.
The mathematical form.
where is spot price, is circulating supply, realized cap is the sum of UTXOs valued at their creation prices, and realized price is realized cap ÷ supply. The three formulations are algebraically identical.
The interpretation as a multiplicative factor. MVRV = 2 means the network is trading at 2× its aggregate cost basis. MVRV = 4 means 4× — common at cycle peaks. MVRV < 1 means the average UTXO is currently unprofitable — characteristic of deep bear-market capitulation.
What it is not. MVRV is not a true mark-to-market profit-and-loss measure for any individual holder — different holders have very different cost bases. It is a network-aggregate cycle-positioning signal, not an individual-portfolio metric. The cohort variants (Long-term vs short-term holder behavior) get closer to individual-cohort behavioral readings but still aggregate across cohort members.
How it’s calculated
The basic ratio.
where the denominator is the realized cap as defined in Realized price and the numerator is current spot price × circulating supply.
The MVRV Z-score variant. Raw MVRV has the property that its absolute level varies somewhat across cycles. The Z-score normalizes:
where is the standard deviation of market cap over a long window (typically the entire historical sample). The Z-score is operationally more useful than raw MVRV for cross-cycle comparison because it accounts for the fact that absolute MVRV peaks have diminished across cycles (consistent with Diminishing returns thesis).
The empirical Z-score thresholds are:
- Z-score > 7 historically marked cycle peaks (2013, 2017, 2021); the 2024-2025 cycle peaked in August 2025 without the Z-score approaching 7 — a markedly attenuated top.
- Z-score < 0 has historically marked cycle bottoms (2015, 2018-2019, 2022); a Z-score around -1 has been the recurring deep-capitulation signal.
Cohort-specific MVRV. The same machinery applied to cohort-restricted UTXO sets produces:
- LTH MVRV — long-term-holder (155+ day) UTXOs only. Captures the conviction-cohort’s valuation. LTH MVRV peaks last (LTH cohort distributes near cycle tops); LTH MVRV bottoms first (LTH cohort accumulates through bear markets).
- STH MVRV — short-term-holder UTXOs only. Captures the reactive cohort’s valuation. STH MVRV is more volatile, peaks first, and bottoms later.
- Variant: LTH realized price as support, STH realized price as resistance. Operationally, LTH realized price has acted as structural support during pullbacks; STH realized price has acted as resistance during bear-market rallies. See Long-term vs short-term holder behavior.
Data-provider variants. Glassnode, Coin Metrics, Checkonchain, and others all publish MVRV with slightly different methodological choices (price sources, UTXO handling, cohort definitions). The differences are small for cycle-positioning purposes.
What it tells you
Cycle-positioning signal. MVRV is the primary contemporary on-chain cycle-positioning metric. The interpretive framework:
| MVRV Z-score | Interpretation | Historical cycle phase |
|---|---|---|
| > 7 | Extreme overheating | Cycle tops (2013, 2017, 2021) |
| 4-7 | Elevated; distribution territory | Late-cycle bull (2021 H1, late 2017) |
| 2-4 | Above average; mid-to-late bull | Mid-bull (2017 mid, 2021 early) |
| 0-2 | Normal range | Recovery, early bull, normal markets |
| -1 to 0 | Below average; capitulation territory | Late bear (2018 H2, 2022 H2) |
| < -1 | Deep capitulation | Cycle bottoms (Jan 2015, Dec 2018, Nov 2022) |
The thresholds are empirical, not theoretical. They have held across the available cycle data; future cycles may shift them, particularly given Diminishing returns thesis.
Relationship to spot-price extremes. MVRV extremes typically precede or coincide with spot-price extremes:
- Cycle peaks: MVRV reaches its highest values within weeks of spot peaks. MVRV is rarely a clean leading indicator at peaks — the metric overheats simultaneously with price.
- Cycle bottoms: MVRV extremes often coincide with spot bottoms but have produced occasional brief leading signals. The 2022 bottom had a Z-score below -1 for several weeks before the eventual reversal began.
Cross-cycle comparison. MVRV peaks have declined cycle-over-cycle in raw form (2013 peak ~6×, 2017 peak ~4.5×, 2021 peak ~3.5-4×). The Z-score normalization is partial compensation but the underlying attenuation is real and consistent with Diminishing returns thesis. Future cycle peaks should be expected to be lower than past peaks.
Practical cycle-positioning use. Conservative deployment:
- Z-score > 7 is a signal to reduce-or-trim positions (subject to portfolio framework, see Portfolio approaches to Bitcoin)
- Z-score < -1 is a signal to add or accelerate accumulation
- Z-score in the normal range is non-informative; positioning should be driven by longer-horizon framework rather than MVRV signal
Empirical track record
Cycle peak signals.
| Cycle | Peak Z-score | Peak spot | Days from Z-peak to spot-peak |
|---|---|---|---|
| 2013 | ~10 (depending on early-cycle volatility) | $1,200 | ~0 (peak simultaneous) |
| 2017 | ~7 | $19,800 | ~0-15 |
| 2021 | ~7 | $69,000 | ~0 (peak simultaneous; lower Z-score reflected diminishing returns) |
| 2024-2025 | below prior >7 peaks (markedly attenuated) | ~$124,000 (Aug 2025) | ~0 (peak roughly simultaneous) |
The 2024-2025 cycle produced a notable feature: MVRV Z-score never approached the >7 levels of prior cycles, even as spot reached a new all-time high around $124,000 in August 2025. This is consistent with Diminishing returns thesis: each cycle’s peak overheating is less extreme than the prior cycle’s. The August-2025 top was the most attenuated in Bitcoin’s history — ETF-era demand blunted the blow-off — and the subsequent 2026 drawdown carried MVRV back below 1 into capitulation territory. Whether that drawdown has fully bottomed remains contested; that peak overheating keeps attenuating cycle-over-cycle is now the clearer signal.
Cycle bottom signals.
| Cycle | Trough Z-score | Trough spot | Days from Z-trough to spot-trough |
|---|---|---|---|
| 2015 | ~-1 | $200 | Coincident |
| 2018-2019 | ~-0.5 to -1 | $3,200 | Coincident |
| 2022 | ~-1 | $15,500 | Coincident |
Cycle bottoms have been more consistently coincident with Z-score extremes than cycle peaks. The pattern is interpretable: cycle bottoms exhaust at the level where capitulation is structural (median holder underwater), while cycle peaks can extend further than MVRV would suggest if late-cycle inflows continue.
Cross-validation with other metrics. MVRV extremes typically align with other on-chain extremes (NUPL extremes, SOPR resistance breaks, cohort-specific behavior). The cross-validation is part of why systematic frameworks (Check’s, Ryan’s) integrate MVRV with multiple complementary metrics rather than treating it as standalone.
Limitations
The aggregate cost-basis approximation. MVRV inherits Realized price’s limitation that realized cap is a proxy for cost basis, not the literal economic cost basis. Self-custody transfers, exchange deposits, UTXO consolidation, and transaction batching all reset cost-basis timestamps without corresponding economic acquisitions. The bias is systematic and small for aggregate analysis but limits the metric’s precision.
The ETF-era distortion (2024+). Large ETF wallets have UTXO cost bases near current spot prices because the creation/redemption mechanism trades at-spot. This inflates realized cap relative to “true” historical cost basis, which compresses MVRV relative to its historical calibration. The 2024-2025 cycle’s apparently-suppressed MVRV peaks may partially reflect this distortion rather than only Diminishing returns thesis. Disentangling the two effects is an open analytical question.
Cycle attenuation makes thresholds unreliable. The Z-score normalization partially compensates for the declining peak amplitudes across cycles, but the compensation is imperfect. A reader using MVRV >7 as a cycle-top signal in the 2024-2025 cycle may have already missed the peak; a reader using MVRV >4 may have triggered too early. The thresholds need recalibration as evidence accumulates, but the historical sample is small.
Diminishing-returns calibration uncertainty. If Diminishing returns thesis holds, the thresholds for extreme MVRV will continue to decline cycle-over-cycle. The metric is genuinely useful for cycle-positioning but the specific thresholds are moving targets.
Lagging on the upside. MVRV is not a leading indicator at cycle peaks — it overheats simultaneously with price. The metric does not give meaningful lead time for top-calling; it can only confirm extremes in real time. The cohort variants (especially LTH cohort behavior — LTH distribution begins before spot peaks) carry more leading content than aggregate MVRV.
Cohort variants more informative. Aggregate MVRV blends cohort behaviors. LTH MVRV and STH MVRV carry more signal because they separate the conviction-cohort from the reactive-cohort. Aggregate MVRV is the gateway concept; the cohort variants are the deployment-ready forms.
Custodial-cohort blindness. Bitcoin held in custodial-exchange wallets, ETFs, and corporate treasuries shows up on-chain at the wallet level but doesn’t reveal the individual cohort behaviors of the underlying beneficial owners. As more Bitcoin sits in custodial structures, the MVRV signal becomes increasingly muddied by what’s happening inside those custodial buckets, which is not visible on-chain.
Counter-arguments and tensions
”MVRV is just curve-fitting cycle peaks and troughs”
The argument: The empirical regularity of MVRV at cycle extremes could be coincidence. Four cycles is not enough data to establish robust thresholds; the next cycle may invalidate the framework. The thresholds (>7 peaks, ←1 troughs) are essentially derived from the historical sample they’re tested on, so the apparent fit is uninformative.
Response: Partially right. Four cycles is a small sample, and the thresholds are sample-derived. But the underlying mechanism is more substantive than pure pattern-matching: MVRV measures the gap between spot price and aggregate cost basis, which is a behaviorally meaningful quantity (holder profit/loss exposure). The metric being mean-reverting at cycle scale follows from holder behavior (capitulation at deep underwater levels, profit-taking at deep above-water levels), not from curve-fitting. The thresholds may need recalibration but the conceptual content is real.
The cycle-attenuation interpretation problem
The argument: MVRV peaks have declined cycle-over-cycle. If the trend continues, MVRV becomes less and less informative — eventually the metric’s extremes won’t reach historically-meaningful levels at all. The framework loses operational content as Bitcoin matures.
Response: Substantive concern. The Z-score normalization is partial compensation but not complete. The honest reading is that MVRV will become a less-dramatic-extremes metric over time, and the operational thresholds need to migrate downward. The metric remains useful but the specific calibration is dynamic rather than static. The cohort variants partially compensate because cohort dynamics may be less attenuated than aggregate dynamics.
”Custodial and ETF distortion has invalidated the metric”
The argument: Post-2024 ETF flows and broader custodial-institutional adoption have fundamentally changed what realized cap captures. The metric was calibrated on self-custody-dominated cycles; the new regime is different enough that historical thresholds don’t apply.
Response: Partially right but probably overstated. ETF flows do change the realized-cap composition. But ETF accumulation has been gradual and has occurred at gradually-rising spot prices, which is similar to the pattern of self-custodial accumulation in prior cycles. The metric is contaminated, not broken. Cohort-specific MVRV (especially LTH MVRV restricted to non-ETF holders, if data permits) recovers most of the signal. The framework needs adaptation, not abandonment.
The cointegration-and-spurious-regression critique
The argument: Market cap and realized cap are both trending non-stationary series. Their ratio is bounded only because spot mean-reverts toward realized over cycles. Statistical tests for the relationship’s robustness give weak results.
Response: Realized cap is constructed from spot prices over time and so shares a common time trend with spot — the relationship is mathematically built in rather than statistically inferred. The ratio MVRV is genuinely mean-reverting on cycle timescales because cycle peaks and troughs are real behavioral phenomena, not statistical artifacts. The critique applies more to free-standing time-series regressions than to ratio metrics. It is a methodological caution but not a refutation.
”MVRV is redundant with NUPL”
The argument: NUPL is mathematically equivalent to (1 − 1/MVRV) at the aggregate level. Why build separate notes for two metrics that contain the same information?
Response: Substantially right at the aggregate level. The two metrics are mathematically related; the practical reason to distinguish them is presentation: MVRV is a ratio (good for “X times the cost basis” framings); NUPL is a fraction (good for “Y% of unrealized profit” framings and for the named-phase psychological labels: hope, optimism, belief, euphoria, etc.). The cohort variants diverge slightly because of how supply weights enter the construction. The honest reading is that NUPL is a presentation variant of MVRV rather than an analytically distinct metric, which is why the NUPL note explicitly notes this relationship.
”MVRV doesn’t account for fiat regime change”
The argument: MVRV is denominated in USD. If the dollar inflates substantially, MVRV-based valuation framings become misleading — Bitcoin can appear “fairly valued” by MVRV while losing purchasing power against real goods. The metric is silent on macro regime change.
Response: Real concern for tail scenarios. MVRV is genuinely USD-denominated and shares all the limitations of USD-denominated valuation. For hyperinflation or other major-fiat-regime-change scenarios, MVRV is uninformative; the framework needs supplementation with real-asset-denominated comparisons. This is a limitation of MVRV-as-currency-framework, not of MVRV-as-cycle-positioning-tool within a stable-fiat baseline.
The leading-indicator failure at peaks
The argument: MVRV is not a leading indicator at cycle tops. It overheats simultaneously with price, so it can confirm but not anticipate peaks. For users wanting top-calling content, MVRV alone is insufficient.
Response: Substantially right. MVRV is a cycle-positioning metric, not a top-calling metric. Top-calling requires integration with cohort-distribution signals (LTH distribution preceding peaks), exchange-flow signals, and macro signals. The systematic frameworks (Check, Ryan) treat MVRV as one input among several, not as a standalone top-caller. The honest reading is that MVRV is a powerful cycle-context metric with known limitations as a leading signal.
Open questions for further development
- How should MVRV thresholds be recalibrated for the post-ETF regime? Specific calibration adjustments — perhaps cohort-restricted variants excluding ETF UTXOs — would strengthen the metric for forward analysis.
- What is the appropriate weight on aggregate MVRV vs cohort-specific MVRV in operational decision-making? Cohort variants carry more signal but require additional cohort-definition machinery.
- At what MVRV level does the framework break down entirely? A pure framework relying on historical thresholds will eventually fail; what is the regime-change signature that would indicate the metric has lost predictive content?
- How does MVRV interact with macro extremes? When MVRV is in normal range but Bitcoin and global liquidity is at an extreme, which signal should dominate? The integration framework is the topic of Using on-chain data for macro positioning.
- Can MVRV be derived as a function of Bitcoin’s monetization stage? A first-principles derivation from Monetization S-curve and The Power Law model would integrate the on-chain layer with the longer-horizon trajectory framework.
- What is the appropriate way to communicate MVRV’s diminishing-amplitude problem to less-sophisticated users? Retail users who learned MVRV >7 as a cycle-top signal may use it incorrectly in future cycles. The framework’s practical communication is an ongoing challenge.
- Should MVRV be weighted by holder-cohort capital concentration? Whale-cohort MVRV may carry more signal than retail-cohort MVRV; the framework’s natural extension toward entity-weighted analysis is an open direction.
Canonical sources for this note
Primary framework sources
- Murad Mahmudov and David Puell, “An Introduction to MVRV” (2018) — the canonical introduction of the metric
- David Puell, various follow-up analyses including the Puell Multiple miner-revenue metric
- Coin Metrics State of the Network reports — ongoing MVRV documentation and analysis
- Glassnode MVRV documentation — methodological detail and ongoing cycle commentary
- Checkonchain platform — James Check’s analytical framework treating MVRV as a flagship metric
Practitioner literature
- James Check, extensive Glassnode Week On-Chain newsletters during the 2020-2023 tenure — applied MVRV analysis across the 2020-2022 cycle
- James Check, ongoing Checkonchain platform analysis 2024+
- Ryan (On-Chain Mind), various video analyses applying MVRV in accessible format
- Various Bitcoin Magazine and BitMEX Research pieces on MVRV applications
The MVRV Z-score variant
- Awe & Wonder (pseudonymous), original MVRV Z-score formulation — normalization framework that has become standard
Adjacent on-chain literature
- David Puell and various co-authors on the Puell Multiple (miner-revenue analog) — adjacent on-chain valuation metric
- Various analyses of MVRV in comparison with NUPL, SOPR, and other valuation metrics
Critical perspectives
- Various Coin Metrics and academic engagements with on-chain metric robustness
- Within-Bitcoin debates about MVRV’s reliability across the cycle-attenuation regime
- Critiques of single-metric reliance in cycle-positioning
Related notes
- On-chain analytics and market psychology — sub-MOC parent
- Realized price — definitional foundation; MVRV is price ÷ realized price
- NUPL — closely related valuation metric; mathematically a presentation variant of MVRV
- SOPR — realized-side analog; uses cost-basis machinery on spent outputs
- HODL waves — cohort framework for cycle-positioning
- Long-term vs short-term holder behavior — produces cohort-specific MVRV variants
- Coin Days Destroyed — complementary cohort-behavior metric
- Whale behavior — entity-weighted cohort framework
- Exchange flows — custodial-flow framework; complements MVRV
- Sentiment indicators — off-chain sentiment proxies
- Psychological phases of the market cycle — synthesis where MVRV extremes mark phase transitions
- Using on-chain data for macro positioning — operational bridge to macro frameworks
- The Power Law model — longer-horizon trajectory framework; MVRV-extreme readings fit within Power Law corridor context
- Stock-to-flow model — engaged critically; alternative framework
- Four-year halving cycles — cycle structure MVRV extremes anchor
- Diminishing returns thesis — cycle-over-cycle attenuation framework MVRV peaks empirically demonstrate
- Bitcoin and global liquidity — macro framework MVRV extremes integrate with
- Bitcoin and the ISM PMI cycle — macro framework
- Monetization S-curve — adoption framework
- Portfolio approaches to Bitcoin — practical allocation framework MVRV signals inform
- James Check — primary contemporary anchor; MVRV framework developer
- Ryan - On-Chain Mind — adjacent contemporary anchor
- Dylan LeClair — adjacent on-chain voice
- Plan B — S2F framework (engaged critically); alternative cycle framework
- Giovanni Santostasi — Power Law modeler; adjacent
- Lyn Alden — macro-empirical thinker; adjacent