Where is BTC in its cycle right now?

How it's calculated200-week MA = simple average of closing prices over the past 1,400 calendar days (200 × 7). It needs 1,400 days of data first, so it starts in June 2014. Color = today's 200-week MA ÷ the 200-week MA 30 days ago − 1, colored continuously from 0% to 16% (same method as Look Into Bitcoin's heatmap). Multiple = price ÷ 200-week MA. Buy/sell signals are bucketed by this multiple's percentile over the past 4 years.

LimitationsMoving averages only reflect the past and react slowly: they tell you where the long-term average price is, not whether price will keep falling. In 2015 price bottomed nearly 40% below the 200-week MA, and in 2022 it stayed below it for more than half a year. The multiple at tops has shrunk every cycle (about 16× in 2017, about 6× in 2021, and at most about 2.5× since 2024), so calling tops with a fixed multiple easily fails.

How it's calculated111-day MA = simple average of the past 111 daily closes; ceiling = simple average of the past 350 daily closes × 2. Ratio = 111-day MA ÷ (350-day MA × 2); the day the ratio goes from below 1 to 1 or above counts as a cross. The name comes from 350 ÷ 111 ≈ 3.15, close to π. The indicator was created by Philip Swift. Buy/sell signals: a ratio ≥ 1 is an outright Sell; otherwise signals are bucketed by the ratio's percentile over the past 4 years.

LimitationsIt only flags tops, not bottoms. Both parameters were chosen by fitting past tops, so there's an element of hindsight: it didn't fire at the higher November 2021 top, nor in the cycle since the 2024 halving (including the October 2025 high). Bitcoin's rallies are getting milder, and the two lines may rarely cross again, so "no cross" does not mean "no top yet".

How it's calculated2-year MA = simple average of the past 730 daily closes; upper band = 2-year MA × 5. Position is computed on a log basis: (log price − log 2-year MA) ÷ (log 5× line − log 2-year MA). Buy/sell signals: below the 2-year MA is a Buy, above the 5× line is a Sell, and in between signals are bucketed by the percentile of "price ÷ 2-year MA" over the past 4 years.

LimitationsThe 5× line hasn't been touched since 2018: the 2021 top and the highs since 2024 were far below it, so it says little about tops in newer cycles. Falling below the 2-year MA doesn't mean an immediate bottom either: after breaking below it in May 2022, price stayed underneath for a year and a half.

How it's calculatedMayer Multiple = daily close ÷ simple average of the past 200 daily closes. Buy/sell signals use fixed thresholds across five levels: below 0.8 Buy, 0.8–1.0 Accumulate, 1.0–1.5 Hold, 1.5–2.4 Trim, above 2.4 Sell.

LimitationsThe 200-day window is fairly short: after a few months of one-directional moves, the MA catches up and the multiple drifts back toward 1, so it can't tell you whether price is expensive on a long-cycle basis. The multiple at tops has fallen every cycle (peaking around 8.2 in 2013, 3.7 in 2017, 2.8 in 2021, and about 1.85 since 2024), and the 2.4 line hasn't been touched once this cycle.

How it's calculatedTake the base-10 log of each day's price and of the number of days since the genesis block (January 3, 2009), then fit a least-squares linear regression on all daily prices since August 2010: log10(price) = a + b × log10(days). The slope b is currently about 5.6, meaning each 1% increase in days lifts the trend price by about 5.6%; as time goes on, 1% of days covers a longer stretch of time, so the yearly growth rate naturally keeps slowing. We then compute how far each day's price deviates from the regression line (the residual), take the 2nd, 20th, 50th, 80th and 98th percentiles of residuals since around October 2012, and shift the regression line by each to get the five lines. So the midline is the regression line plus the median residual, not the regression line itself. "Historical percentile" = the share of past days with a residual less than or equal to today's, and buy/sell signals are bucketed by this percentile.

LimitationsThe power law is just a fit to the past 16 years of data, not a law of physics, and nothing guarantees Bitcoin will keep following it. The parameters shift slightly every day with new data, and early years when price was only a few dollars have a big influence on the slope. As volatility declines, price might trade in a narrow range around the midline for a long time and never reach the top edge, or it might fall out below the bottom edge altogether.

How it's calculatedEach line = closing price on day N after the halving ÷ closing price on halving day, for N from 0 to 1,460. Halving dates: 2012-11-28, 2016-07-09, 2020-05-11, 2024-04-20. Buy/sell signals are based on days since the current halving: 0–364 days early phase, 365–599 days top window, 600–759 days decline phase, 760–999 days bottom window, 1,000+ days recovery phase.

LimitationsThere are only 3 complete cycles of history, a very small sample, so the "patterns" may be partly coincidence. Each halving's supply shock is smaller than the last: this cycle cut daily new issuance from about 900 BTC to about 450 BTC, a tiny fraction of the nearly 20 million coins already in circulation. New factors such as spot ETFs and interest rates matter more and more, and the 4-year cycle could change shape or disappear. The 2012 cycle started at only about $12, so its gains can't be compared directly with later cycles.

How it's calculatedRealized price = realized cap ÷ circulating supply. Realized cap values each coin at the price it last moved on-chain and adds them all up. Short- and long-term holder cost bases use the same method, counting only coins held less than or more than 155 days respectively; the 155-day threshold was introduced by Glassnode and is the industry standard. All three lines come directly from bitview.space daily data with no further processing by BTCEveryDay.

LimitationsTrades inside exchanges don't happen on-chain and don't update a coin's last traded price, so these cost bases reflect on-chain transfer prices, not exactly what each person actually paid. Lost coins (such as Satoshi's early mined coins) are counted at extremely low cost, pulling the network cost basis down. If the data source can't tell whether wallets belong to the same person, sending coins to yourself also counts as changing hands: those coins' cost is reset to the price at the time, and they're counted as short-term holder coins again.

How it's calculatedMVRV = market value ÷ realized value, both from bitview.space. The Z-Score is calculated by BTCEveryDay: (market value − realized value) ÷ cumulative standard deviation of market value. "Cumulative" means each day's standard deviation uses only market value from the start of the data up to that day, never future data; the earliest period with less than a year of data is not calculated. Buy/sell signals use its percentile over the past 4 years (1,461 days), not fixed thresholds like 7 and 0.

LimitationsAs Bitcoin grows larger and less volatile, readings at each top keep falling, and the 7 line may no longer be reachable. The denominator is a cumulative standard deviation, increasingly dominated by recent years' larger market cap, so the same reading doesn't mean exactly the same thing in different eras; different websites calculate the standard deviation differently and from different start dates, so values will differ too. It also inherits the biases of realized price: trades inside exchanges aren't on-chain, and lost coins are counted at low cost.

How it's calculatedNUPL = (market value − realized value) ÷ market value, equivalent to 1 − 1 ÷ MVRV. Values come directly from bitview.space. The sentiment stages are split at 0, 25%, 50% and 75%, a common rule of thumb in the industry rather than a rigorous statistical result. Buy/sell signals use its percentile over the past 4 years.

LimitationsNUPL and MVRV express the same information in different forms, so don't treat them as two independent pieces of evidence. Top readings also get lower each cycle, and the "Euphoria" band hasn't truly been reached in the last two cycles. It also inherits the biases of realized price: lost coins are counted at extremely low cost, making network-wide unrealized profit look higher than it is.

How it's calculatedSOPR = total value of all coins moved on-chain that day at the price when moved ÷ their total value at the price when they last changed hands. Short-term holder SOPR counts only coins held less than 155 days. We take daily values from bitview.space and, because the raw daily data is very noisy, apply a 7-day simple average. Buy/sell signals use the percentile of short-term holder SOPR (7-day avg) over the past 4 years.

LimitationsMoving coins on-chain isn't necessarily selling: deposits to exchanges and transfers between your own wallets are counted too, so it's only an approximation of selling, and trades inside exchanges aren't on-chain and can't be seen. Glassnode's original SOPR excludes coins moved within 1 hour of being received; we haven't verified in detail how bitview.space handles this. It reflects short-term sentiment and is useful for judging the strength of a pullback or bounce, not for calling cycle tops and bottoms on its own.

How it's calculatedFollowing Hans Hauge's definition: Reserve Risk = price ÷ HODL Bank. The HODL Bank is tied to "coin days destroyed": a coin that sits unmoved accumulates 1 "coin day" per day, and when it's moved, those accumulated coin days are "destroyed". Few coin days destroyed means old coins are rarely sold and holders keep "forgoing the sale", so the HODL Bank keeps growing; when lots of old coins move, it gets drawn down. Values come directly from bitview.space; the exact HODL Bank accumulation formula follows bitview's implementation, which we haven't verified in detail. Buy/sell signals use its percentile over the past 4 years.

LimitationsThe magnitude of these values may differ from other websites, so only compare this line with its own history; the fixed thresholds commonly cited online don't apply directly. Top readings decline each cycle, making fixed thresholds for tops increasingly unlikely to trigger. The HODL Bank has been accumulating since Bitcoin's genesis, so each day's change matters less and less over time and it reacts slowly. Coins held by exchanges or ETF custodians that sit unmoved for long periods are also counted as "strong holding".

How it's calculatedRHODL = realized value of 1-week-old coins ÷ realized value of 1–2-year-old coins. "Coin age" is how long it's been since a coin last changed hands; "realized value" is the total of those coins valued at their last traded prices. The indicator was created by Philip Swift; the original version also multiplies by the number of days since Bitcoin's genesis to offset early-year bias. We haven't verified whether bitview.space's values include this step, so don't compare them directly with other websites. Buy/sell signals use its percentile over the past 4 years.

LimitationsMuch of the past week's movement is coins shuffling between exchanges and wallets, not all of it new money coming in. Bitcoin's ownership structure is changing (more ETFs and custodians), top readings decline each cycle, and fixed thresholds aren't reliable. Low readings can persist for a long time, making it hard to tell from this alone when a bottom is over.

How it's calculatedLong-term holder supply = supply that hasn't moved on-chain for more than 155 days (Glassnode definition, data from bitview.space). 30-day net change = today's supply − supply 30 days ago. The signal level in the signal box ranks this net change within the past 4 years (percentile): the more accumulation, the closer to the "Buy" side; the more distribution, the closer to the "Sell" side. The chart shows the last 6 years.

LimitationsThe net change mixes two things: younger coins automatically "graduating" into long-term coins after 155 days, and old coins being moved out. So even in a bear market with no buyers, the number rises simply because coins get older. Exchanges and custodians moving their own old coins also count as "distribution". Backtests show that a year after "accumulating" has actually done worse than after "distributing", so we don't use it alone for a buy/sell verdict.

How it's calculatedEach day we count the addresses with a balance above 1,000 BTC and their combined balance; data from bitview.space. The chart starts in 2013.

LimitationsAddresses aren't people: a single exchange, ETF custody or mining pool address often holds tens of thousands of coins pooled from many users, while one large holder may spread coins across many addresses. When exchanges consolidate or split wallets, the count can jump suddenly for reasons unrelated to buying or selling.

How it's calculatedData from OKX's public liquidation-orders endpoint (BTC-USDT perpetual, filled liquidation orders). Each amount = number of contracts × 0.01 BTC × bankruptcy price (the price at which the position's margin is fully lost), summed by hour, showing the last 7 days. The "24h liquidations" figure at the top is the total for the last 24 hours.

LimitationsIt only counts one contract on one exchange (OKX); market-wide liquidations are far larger than the numbers here, so it's useful for seeing the rhythm and which side is getting liquidated, not the total. Each fetch goes back at most about 1,000 orders, so in extreme markets with lots of liquidations between fetches, some may be missed.

How it's calculatedWe take the funding rate of the Bybit BTCUSDT perpetual, settled every 8 hours, add up the periods within each day (UTC) to get the daily rate, then × 365 for an annualized percentage; the orange line is its 7-day simple average. The live rate at the top is the current period's rate, × 3 × 365 to annualize. Buy/sell signals use the 7-day average's percentile over the past 4 years, in five buckets of 20 percentile points each: the lower, the more it leans Buy; the higher, the more it leans Sell. The backtest looks at price moves 30 days after the signal.

LimitationsIt uses Bybit only; rates differ slightly between exchanges, but the direction is basically the same. Funding reflects short-term crowding and can stay elevated for months in a bull market, so relying on it alone can make you sell too early. Exchanges may change settlement intervals and rate caps in extreme markets, so data before and after isn't fully comparable.

How it's calculatedDaily open interest of the Bybit BTCUSDT perpetual (public open-interest endpoint, intervalTime=1d), in BTC. The live open interest at the top comes from Bybit's market snapshot, with the dollar value converted at the current price; Hyperliquid's BTC open interest is shown for comparison.

LimitationsIt's just one Bybit contract and excludes Binance, CME and other exchanges as well as coin-margined contracts, so it only shows the trend, not the market-wide total. Open interest itself doesn't tell you the direction; read it together with the funding rate and long/short account ratio.

How it's calculatedBybit: public account-ratio endpoint (BTCUSDT, daily), share of accounts holding longs ÷ share holding shorts. OKX: public long-short-account-ratio endpoint (BTC contracts, daily). A ratio of 1.5 means 60% of accounts are long and 40% short.

LimitationsIt only reflects accounts on these two exchanges, and every account counts as one regardless of position size. There's no fixed "too high" threshold, and the normal level differs across exchanges and periods. Reading it contrarily keeps failing in a one-directional trend: retail stays long throughout a bull market, and price can keep rising.

How it's calculatedCumulative net flows = sum of daily total net flows since the first trading day. Grayscale's GBTC was converted into an ETF from an older trust founded in 2013, with a 1.5% management fee, far above the 0.15%–0.25% of other funds; after the conversion, long-time holders redeemed heavily, and those outflows are included. For both GBTC and BTC (Grayscale Bitcoin Mini Trust), only share changes after conversion and listing as ETFs are counted; coins already in the trusts before conversion don't count as inflows.

LimitationsFunds without historical data (FBTC, BITB, BRRR, BTCO) are only counted from the day BTCEveryDay started collecting, so their inflows since launch aren't included, and the total here will be lower than common third-party figures. Cumulative amounts are converted at each day's NAV and don't reflect subsequent price changes of those coins.

How it's calculatedLatest holdings are taken directly from issuers' published figures. Historical holdings = shares outstanding that day × current BTC per share × a management-fee back-adjustment factor. Management fees are paid by deducting BTC from the fund every day, so the further back you go, the more BTC each share held; we back-calculate day by day using each fund's annual fee rate (0.15%–1.5%).

LimitationsHistorical holdings are estimates: most issuers offered fee waivers for an initial period after launch, so back-calculating at the full fee rate makes holdings during that period slightly too high. Funds without historical data (FBTC, BITB, BRRR, BTCO) aren't in the chart.

How it's calculatedTake daily network hashrate and compute its 30-day and 60-day simple moving averages. When the 30-day MA is below the 60-day MA, the status is "capitulating"; the first day it returns to 30-day MA ≥ 60-day MA counts as a "capitulation over" signal (green dashed line). In the signal box, the 60 days after a signal count as "Buy", and no direction is given at other times. The original Hash Ribbons (Charles Edwards, 2019) also requires short-term price momentum to turn positive to confirm a buy; we only use the hashrate crossover without that condition.

LimitationsHashrate can't be measured directly; it's an estimate inferred from block times and difficulty, and the daily data is very noisy, so the moving averages produce quite a few false crossovers. There are far more green dashed lines on the chart than major bottoms. A drop in hashrate isn't always due to unprofitability either: when China banned mining in May–July 2021, hashrate fell by about half because of policy, not price. Backtests show the chance of BTC being higher a year after a signal is only a few percentage points above average, so it's best used as a reference, not for buy/sell decisions on its own.

How it's calculatedPuell Multiple = miners' mining revenue that day (USD) ÷ average daily mining revenue over the past 365 days (USD); data from bitview.space. The red-zone threshold of 4 and green-zone threshold of 0.5 on the chart are common rules of thumb; the signal box doesn't use these fixed lines but instead looks at the current reading's historical percentile over the past 4 years (below 20% is the Buy bucket, above 80% the Sell bucket).

LimitationsWith each halving, miner revenue shrinks as a share of market cap, so Puell's peaks get lower every cycle: the 2021 bull market only reached about 3.4, and it hasn't entered the red zone since 2018, so insisting that "4 is the top" will miss tops. Readings in the year around each halving are distorted by the reward cut. Data sources differ on whether miner revenue includes fees, so values may vary somewhat.

How it's calculatedHashprice = total miner revenue that day (block rewards + transaction fees, converted to USD at that day's price) ÷ network hashrate (in TH/s); data from bitview.space. The industry also often quotes it in dollars per PH/s per day, which is 1,000× the value in this chart.

LimitationsIt only counts revenue, not costs. Electricity prices and machine efficiency vary widely between miners, so at the same Hashprice some make money and others lose it; there's no universal "shutdown line". Hashrate itself is an estimate, so Hashprice is noisy too. It's better for watching miners' situation than for making buy/sell decisions on its own.

How it's calculatedDifficulty adjusts every 2,016 blocks: new difficulty = old difficulty × 20,160 minutes (2,016 blocks × 10 minutes) ÷ the actual time those 2,016 blocks took, and a single adjustment can change it by at most 4× or 1/4. Difficulty × 2³² is roughly the average number of hashes needed to find a block, so "difficulty × 2³² ÷ 600 seconds" approximates network hashrate. The next-adjustment estimate comes from mempool.space, extrapolated from the average block interval so far this epoch.

LimitationsDifficulty only reflects the past two weeks of hashrate, so it lags. The estimated adjustment changes with how fast the remaining blocks in the epoch are found, and gets more accurate closer to the adjustment.

How it's calculatedStablecoin supply is the sum of the circulating market cap of all USD stablecoins tracked by DefiLlama, one value per day; missing days carry forward the previous day's value (for up to 5 days). 30-day change = today's supply ÷ supply 30 days ago − 1. SSR = BTC circulating market cap ÷ stablecoin supply, with BTC market cap from bitview.space.

LimitationsStablecoins aren't only used to buy BTC; they're also used to buy other coins, for DeFi lending and for cross-border transfers, and a substantial share sits idle with exchanges and issuers. This counts all on-chain USD stablecoins combined and can't show which market they're actually used in. Reserve transparency at issuers such as Tether (USDT) is limited.

How it's calculatedFirst compute daily returns (today's close ÷ the previous trading day's close − 1), then calculate the Pearson correlation between BTC's and the other asset's daily returns over a rolling 90-calendar-day window. US stocks and gold don't trade on weekends and holidays, so only days with data on both sides are paired, and it isn't calculated with fewer than 54 paired days (60% of the window). The Nasdaq is the Nasdaq Composite, and gold uses COMEX gold futures prices.

LimitationsBTC's weekend moves aren't included (US markets are closed then), so Monday pairs one day of BTC's move with three days of the Nasdaq's, which biases the correlation slightly lower. Correlation only describes how much things moved together over the past 90 days, not which one drives the other, and it changes quickly; moderate values around 0.3 are very noisy, so don't read too much into them.

How it's calculatedWe take the daily close of the ICE US Dollar Index (Yahoo Finance ticker DX-Y.NYB), carrying forward the previous trading day on weekends and holidays. It's a weighted geometric average of six exchange rates, with the euro carrying the largest weight at about 58%.

LimitationsThe euro makes up more than half of DXY, and emerging-market currencies such as the Chinese yuan aren't included at all, so it mainly reflects the dollar against the euro, not against the whole world. The inverse relationship between the dollar and BTC is only a statistical tendency, and there have been long periods when both rose or fell together.

How it's calculatedWe take the daily close of Yahoo Finance's ^TNX (Cboe 10-Year Treasury Yield Index), carrying forward the previous trading day on weekends and holidays. The "30-day" change at the top = today's yield − the yield 30 days ago, in percentage points (e.g. a rise from 4.0% to 4.5% is 0.5 percentage points).

LimitationsYields rise for different reasons with different implications: a rise driven by a strong economy doesn't necessarily hurt risk assets, while a rise driven by inflation or fiscal-deficit worries is the more typical bearish case. It only represents long-term rates; the Fed's policy rate and balance sheet have a more direct effect on liquidity, and we'll add them in the next version.