Originally published at SatoshiMacro. This is a syndicated re-post of editorial research from satoshimacro.com; the original is the authoritative version.
There's a Bitcoin cycle indicator that has caught every major top since 2013 and every major bottom too. It is not in most retail dashboards. It does not appear on Twitter charts every week. It is called the Risk Metric, popularised by Benjamin Cowen in 2019, and I have been using a version of it from a Sydney institutional-trading desk since well before that.
The version that sits inside the SatoshiMacro Model is calibrated against seven historical cycle inflections. The live current reading is on the page. This piece is about how the Risk Metric is built, what its honest limitations are, and how an Australian-resident retail investor should actually use it given the 12-month CGT discount eligibility ladder.
What the Bitcoin Risk Metric actually measures
The Risk Metric is a normalised cycle-position index. The output is a single value between 0 and 1, where 0 means deep accumulation territory (statistically the cycle bottom) and 1 means peak distribution territory (statistically the cycle top).
Cowen's published version uses a combination of inputs:
- Log price regression deviation
- Network value vs realised value spread
- Long-term moving average divergence
- Long-term holder behaviour metrics
The math compresses all of those into one 0-to-1 ratio. The model has been recalibrated three times since first publication, in 2020, 2021, and 2024, because each new cycle adds price-history data that shifts the baseline.
My version inside the SatoshiMacro Model uses a similar architecture but the inputs differ. I lean more heavily on the on-chain valuation tier and less on price-statistical signals. That choice reflects what I learned on the institutional side: derivatives positioning data telegraphs cycle inflections, but pure price statistics get fooled by trending markets.
What it has caught historically
Seven of seven in-zone calls on documented Bitcoin cycle inflections since 2013:
- December 2013 cycle top: Risk Metric printed near the upper extreme. Cowen's version, when retroactively calculated, hits the same zone.
- December 2017 cycle top: model held in distribution territory for the full month.
- April 2021 cycle top: high reading. Note this was the first top of the 2021 double-cycle.
- October 2025 cycle top cluster: Bitcoin printed all-time high at USD 126,198 on 2025-10-06; the metric flagged distribution territory across September and October.
- January 2015 cycle bottom: deep accumulation reading.
- December 2018 cycle bottom: deep accumulation.
- November 2022 cycle bottom: deep accumulation.
Four tops, three bottoms, all caught inside the respective extreme bands. The model is a position classifier, not a forecaster. It tells you where the cycle currently sits relative to historical extremes; it does not tell you what happens tomorrow.
Where the Risk Metric sits inside the SatoshiMacro Model
The Risk Metric feeds Tier 1 Valuation at 25 per cent of total model weight. Tier 1 also includes:
- Pi Cycle Top and Pi Cycle Bottom momentum-divergence signals
- Mayer Multiple 200-day moving average valuation ratio
- Bitcoin Power Law log-log regression deviation
- MVRV Z-Score realised-cap normalised deviation
When three or more Tier 1 signals fire above cycle-top threshold simultaneously, the SatoshiMacro Model surfaces a cycle-position warning above the main gauge. That confluence framing is the actual edge.
Every documented Bitcoin cycle top since 2013 was caught only when 3 to 5 indicators across multiple tiers fired simultaneously inside a 4 to 8 week window. Pi Cycle missed the November 2021 echo top. Mayer fired there. MVRV had cycled down. The Risk Metric did not refire. Confluence catches what individual indicators miss; no single indicator is the answer.
Honest limitations of the Risk Metric
Three things to know before you trust it:
- The November 2021 echo top was a partial miss. The Risk Metric printed cycle-top territory in April 2021 but did not refire in November because the underlying valuation inputs had already cycled down from the April peak. A trader using only the Risk Metric to time the November echo would have been late.
- Calibration drift. Each cycle adds new price-history data that shifts the log regression baseline. The thresholds that defined cycle-top territory in 2017 are not exactly the same as the thresholds that define it in 2026. The model has to be recalibrated periodically or it slowly drifts out of usefulness.
- The four-year halving cycle assumption. The Risk Metric, like most Bitcoin cycle models, implicitly assumes the four-year halving cycle continues to drive price-cycle structure. If the structural cycle bends, which it might as spot ETF flows reshape demand, the model's calibration starts to break.
Australian-resident framing: the CGT discount ladder
The Risk Metric's 0-to-1 scale maps cleanly onto a 12-month CGT discount eligibility ladder. Here is how I think about it from a Sydney-based perspective:
- Risk Metric in upper-extreme band: distribution-eligible. Tranche disposal across this window. Prioritise lots purchased outside the previous 12 months so the 50 per cent CGT discount applies.
- Risk Metric in neutral band: no tactical action. This is most of the time. The model is correctly telling you to do nothing.
- Risk Metric in lower-extreme band: accumulation. Start the 12-month CGT clock on new lots. Tranche purchase.
For Australian residents thinking about EOFY 2026 tactical positioning before the 1 July 2027 CGT discount cut-over, the crypto tax-loss harvesting calculator on the site walks through the Part IVA framework, cost-base method choice, and carry-forward record-keeping mechanics.
Frequently asked questions
What is the Bitcoin Risk Metric?
The Bitcoin Risk Metric is a 0-to-1 normalised cycle-position indicator that compresses multiple on-chain and price-statistical inputs into a single score. Values in the upper extreme band historically mark cycle-top territory. Values in the lower extreme band mark cycle-bottom accumulation territory.
Who created the Bitcoin Risk Metric?
Benjamin Cowen published the original Risk Metric formulation in 2019, building on earlier work by various crypto researchers on cycle-position normalisation. The model has been recalibrated three times since first publication.
How accurate is the Bitcoin Risk Metric?
The metric has caught all four documented Bitcoin cycle tops since 2013 (December 2013, December 2017, April 2021, October 2025) and all three confirmed bottoms (January 2015, December 2018, November 2022) inside the respective extreme bands. The November 2021 echo top is a documented partial miss because the metric did not refire after the April 2021 cycle top.
Is the Bitcoin Risk Metric better than the Mayer Multiple or MVRV Z-Score?
No single indicator is better than another. Each measures something slightly different. The Mayer Multiple is a 200-day moving average valuation ratio. MVRV Z-Score is a realised-cap normalised deviation. The Risk Metric is a multi-factor composite. The best play is confluence: run all of them inside a single framework like the SatoshiMacro Model and look for clusters where three or more fire simultaneously.
Where can I see the current Bitcoin Risk Metric reading?
The live current reading, full historical chart back to 2013, and the cycle-comparison view that overlays current-cycle position against 2012, 2016, and 2020 trajectories are all on satoshimacro.com/tools/crypto/cycle-indicators/bitcoin-risk-metric/. The model is free with no paywall.
Closing
The Bitcoin Risk Metric is one of the cleanest single-indicator cycle-position reads available. The methodology is documented. The calibration record is strong. But it is not a forecasting tool. It is a position classifier.
The most important lesson I took from ten years on the institutional side: trust confluence, not single indicators. Never confuse "the cycle is late" with "I know what happens tomorrow." Run a basket. Look for clusters. Size your positions against the confluence read, not the loudest single signal.
Live SatoshiMacro Model with current Risk Metric reading and all 48 underlying signals: satoshimacro.com/tools/crypto/satoshimacro-model/.
Disclosure: I built and maintain SatoshiMacro. The model is free and ad-supported (broker affiliate links on the main site, not in this post). This post is editorial, not financial advice.
