Rolling Volatility

Bitcoin Rolling Volatility plots three series on a shared linear axis capped at 250%. Each series is the annualised standard deviation of daily log returns over its window: 30 days (the tightest, most reactive line), 90 days (the quarterly lens), and 365 days (the yearly lens, the smoothest). The √365 annualisation factor converts a daily standard deviation to a yearly one under the standard independent-returns assumption. A muted reference line at 60% marks the S&P 500's crisis-peak realised volatility — where traditional equity vol stood in October 2008 and again in March 2020.

Today: 30-day 37.8%, 90-day 60.2%, 365-day 43.0% — regime Normal. The lifetime average 30-day reading across 5,735 defined days is 73.4%; that's the gravity pull for the short window. Spot auto-refreshes a few times a day in the browser; the three series rebuild overnight.

Three steps, applied to every rolling window:

rt = ln(pt / pt−1)
voln(t) = stdev(rt−n+1..t) × √365

Step one: take the daily log return as the natural log of today's close divided by yesterday's. Step two: compute the sample standard deviation across the trailing n-day window. Step three: multiply by the square root of 365 to annualise. The 30-day series becomes defined on the thirtieth daily close; the 90-day on the ninetieth; the 365-day on the first anniversary. Pre-warm-up rows are left blank on each series.

Calendar days, not trading days. Bitcoin trades every day — weekends, holidays, mid-year — so the trading-day vs calendar-day distinction that matters for equities collapses here. The √365 annualisation factor reflects that. A reader cross- referencing equity-style realised vol (which uses √252) should multiply our numbers by √(252/365) ≈ 0.83 for an apples-to-apples comparison. The full derivation, including the epoch boundaries and the 250% chart cap, is on the methodology page.

The three windows tell three stories. The 30-day line catches event regimes — cluster-events around capitulation, post-event recoveries, flash crashes. The 90-day line filters most of that noise and reads regime transitions. The 365-day line is the maturation lens: it has compressed every halving epoch, and it is the headline statistic this chart contributes. The regime bands below bucket the 30-day window because that is where the immediate signal lives.

Cycle anchors against all three windows surface two patterns. First: cycle tops and cycle troughs both produce elevated short-window vol, but tops produce it on the way up (parabolic acceleration) and troughs produce it on the way down (capitulation). Second: every cycle peak's 30-day vol has been lower than the previous cycle's, with one structural exception (the 2020 Covid flush, which printed an event-driven peak higher than the 2017 cycle top's). The 365-day column compresses monotonically.

The page's distinctive contribution is the per-epoch table. Most competitor pages publish a single rolling line; few publish the per-halving-epoch decomposition. Here every halving period is a row, with the mean and standard deviation of each of the three windows computed against the days inside that epoch. The compression of the 365-day mean across rows is the chart's headline empirical observation.

Three patterns are visible. First, the 365-day mean has fallen every epoch from 93.1% in Era II to 47.6% in Era V. Maturation of market depth, the launch of regulated derivatives in late 2017, and the 2024 spot-ETF channel all dampen what a given dollar of flow does to price. Second, the 30-day mean has fallen by less than the 365-day mean — cluster events still produce big short-window readings even when the long-window regime is calm. Third, the epoch-internal stdev (the second number in each cell) is itself shrinking, meaning each epoch's vol regime is more uniform than the one before it.

The traditional-finance reference for context: the CBOE VIX — implied vol on the S&P 500, which historically tracks realised vol with a small premium — averages near 19–20 over its 35-year history and peaked at 89.5 (October 2008) and 82.7 (March 2020). Bitcoin's recent epoch-mean 365-day realised vol of 47.6% is roughly 2−3× the long-run S&P benchmark. A decade ago the multiple was 5−10×. The compression is real, structural, and ongoing — but Bitcoin remains materially more volatile than any major equity index.

The implied-vol counterpart is Deribit's DVOL index, which applies the VIX methodology to BTC options and tracks the 30-day forward-looking implied vol. DVOL has tracked our 30-day realised vol with a typical premium in the 5−15-percentage-point range. Persistent gaps between implied and realised — either direction — have been useful regime indicators around cycle inflections; that analysis lives outside this chart's scope but is referenced on the methodology page.

For a dollar-cost-averaging investor. The compression is your friend. Falling vol means a steady buy program is exposed to smaller drawdowns relative to position size, on average, than the same program would have been a decade ago. That said, the 30-day window still spikes during stress events; sizing should reflect the realised cluster-event maximum, not the lifetime mean. The drawdown page is the right place to read peak drawdowns alongside the vol lifetime distribution.

For a cycle-timing trader. Persistent gaps between 30-day and 365-day vol have been useful regime indicators. When 30-day runs well above 365-day for several weeks, the chart is in a regime-transition window — either an early bull or an early bear, depending on direction. Pair with rolling CAGR for direction and halving-cycle overlay for cycle position.

For a researcher. The series, the per-epoch statistics, and the cycle-anchor table are all reproducible from the daily-close history under the documented annualisation convention. The Welford- equivalent rolling-stdev pass and the √365 annualisation choice are documented on the methodology page. Cross-reference against Deribit's published DVOL series for the implied-vs-realised gap.

Realised, not implied. The chart is backward-looking by construction. It tells you what happened, not what options markets are pricing for the next 30 days. For forward expectations, the right read is Deribit's DVOL or a similar implied-vol index. The gap between realised and implied is itself informative; it is not on this chart.

Daily closes only. Intra-day volatility is structurally higher than the close-to-close vol we measure. A flash crash that printed and recovered in the same UTC day registers as zero log-return here; a wick-and-fill candle is invisible. The chart understates the lived experience of trading Bitcoin, especially on weekends when traditional- market-hours dynamics don't apply. Five-minute or hourly candles would print materially higher numbers on the same definition.

Independence assumption breaks during cluster events. The √365 annualisation factor assumes daily returns are independent. They mostly are, except during cluster events where a multi-day capitulation produces autocorrelated negative returns and a multi-day melt-up produces autocorrelated positive ones. Annualised volatility under-states realised dispersion during clusters and over-states it during fully mean-reverting whipsaw weeks.

Survivorship bias. The chart only includes Bitcoin. Indices that include other cryptoassets — many of which have failed or de-listed — would show much higher historical vol. Cross-asset comparisons should account for the fact that Bitcoin is the survivor of a much wider universe.

Future regimes are not knowable. Vol could compress further with deeper institutional flow and broader regulatory clarity; it could expand on a stress event, a regulatory shock, or a credit cycle that propagates into crypto. The past compression is real and structural; the next epoch is not predicted by the last.

Canonical questions from Google's “People also ask” block for bitcoin volatility, answered against the data on this page.