SatoshiMacro
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SatoshiMacro
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Quantitative Bitcoin cycle analysis. Former institutional trader. SMM Model: 48 signals across 6 tiers, 7-of-7 cycle calls. Free at satoshimacro.com
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$BTC | EOFY 2026 is 36 days out. AU crypto holders who sold inside 12 months pay full marginal rate (47 percent at the top bracket). Sold after 12 months and you get the 50 percent CGT discount, which halves the effective rate.
The asymmetry is structural. A 30,000 AUD gain inside 12 months costs ~14,100 AUD in tax at the top rate. The same gain outside 12 months costs ~7,050 AUD. Same dollars realised, half the tax bill.
The 2026 Federal Budget signalled replacement of the 50 percent CGT discount with indexation from 1 July 2027 onward for non-super-fund holders. SMSF holders keep the equivalent under Division 115 (effective ~10 percent rate on long-term gains).
My read: the holding-period decision is the most important tax-side variable for any AU disposal. Map every position against the 12-month threshold before you click sell.
Free AU-resident CGT calculator that handles personal-name, sole trader, and SMSF cases: https://satoshimacro.com/crypto/cgt-calculator/
Reading as of 25 May 2026.
#CryptoTax #Australia #EOFY #SatoshiMacro
$BTC | EOFY 2026 is 36 days out. AU crypto holders who sold inside 12 months pay full marginal rate (47 percent at the top bracket). Sold after 12 months and you get the 50 percent CGT discount, which halves the effective rate.
The asymmetry is structural. A 30,000 AUD gain inside 12 months costs ~14,100 AUD in tax at the top rate. The same gain outside 12 months costs ~7,050 AUD. Same dollars realised, half the tax bill.
The 2026 Federal Budget signalled replacement of the 50 percent CGT discount with indexation from 1 July 2027 onward for non-super-fund holders. SMSF holders keep the equivalent under Division 115 (effective ~10 percent rate on long-term gains).
My read: the holding-period decision is the most important tax-side variable for any AU disposal. Map every position against the 12-month threshold before you click sell.
Free AU-resident CGT calculator that handles personal-name, sole trader, and SMSF cases: https://satoshimacro.com/crypto/cgt-calculator/
Reading as of 25 May 2026.
#CryptoTax #Australia #EOFY #SatoshiMacro
The asymmetry is structural. A 30,000 AUD gain inside 12 months costs ~14,100 AUD in tax at the top rate. The same gain outside 12 months costs ~7,050 AUD. Same dollars realised, half the tax bill.
The 2026 Federal Budget signalled replacement of the 50 percent CGT discount with indexation from 1 July 2027 onward for non-super-fund holders. SMSF holders keep the equivalent under Division 115 (effective ~10 percent rate on long-term gains).
My read: the holding-period decision is the most important tax-side variable for any AU disposal. Map every position against the 12-month threshold before you click sell.
Free AU-resident CGT calculator that handles personal-name, sole trader, and SMSF cases: https://satoshimacro.com/crypto/cgt-calculator/
Reading as of 25 May 2026.
#CryptoTax #Australia #EOFY #SatoshiMacro
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MVRV Z-Score: A Walkthrough of the Most Misused On-Chain Indicator$BTC | MVRV Z-Score: A Walkthrough of the Most Misused On-Chain Indicator
The first time I watched the MVRV Z-Score on an institutional trading desk it was wrong, and the second time it was correct but in a way that wasn't useful. That tension - useful in retrospect, frustrating in real time - is the right starting point for understanding what this indicator actually does.
The standard formulation, often called the Awe & Wonder Z-Score after the analysts who popularised it on Glassnode, is straightforward:
Z = (Market Cap - Realised Cap) / standard deviation of Market Cap
Market Cap is trivially observable. Total BTC supply times current spot price. Realised Cap is the more interesting input. It values each UTXO at the price it last moved on-chain. So a coin sitting in a wallet since 2013 contributes its 2013 cost basis to Realised Cap, not today's spot value. The Z-Score normalises the gap between speculative valuation (Market Cap) and aggregate cost basis (Realised Cap) using an expanding-window standard deviation, so historical comparisons don't get skewed by recent volatility.
The thesis is straightforward. When the Z-Score is high - say above 7 historically - the market is so far above aggregate cost basis that holders are sitting on massive unrealised profit and are statistically likely to take some off the table. When it's negative, holders are underwater in aggregate and unlikely to capitulate further.
That thesis has worked at bottoms with reasonable consistency. It has worked less well at tops.
How it has performed across three completed cycles.
The 2013 December cycle top printed an MVRV Z-Score of approximately 9.3, well above the 7-zone that practitioners pointed at as the cycle-top trigger.
The 2017 December cycle top printed an MVRV Z-Score of approximately 11.5, again clearly inside the cycle-top zone.
The 2021 April top printed an MVRV Z-Score of approximately 6.3 - inside-the-zone if you used a 5-zone threshold, slightly below if you used the older 7-zone threshold.
The 2021 November echo top printed an MVRV Z-Score of approximately 2.9 - far below either threshold. The indicator essentially missed the second leg of the 2021 double-top entirely.
The bottoms have been more consistent. December 2018 printed a Z-Score of approximately -0.2, clearly in the negative zone that historically marks accumulation. November 2022 printed approximately -0.1, same zone. Both bottoms confirmed the negative-zone heuristic.
So the Z-Score is accurate at cycle bottoms with reasonable consistency, but the cycle-top threshold has drifted downward across cycles. 9.3 in 2013, 11.5 in 2017, 6.3 in 2021-04, missed in 2021-11. If you use the same fixed threshold across all four tops, you either accept false negatives (missed signals at later tops) or false positives (entries triggered before earlier tops were fully formed). Neither is acceptable for sizing capital.
Where the methodology gets fragile.
Three structural issues with MVRV Z-Score as practitioners commonly use it.
First, threshold drift across cycles. The supply has grown roughly 2x since 2013 due to halvings. The realised cap denominator scales differently from the market cap numerator in ways that compress the natural Z-Score range. So the same statistical "extreme" reads different across cycles. The 2021-11 miss is the obvious case. If we use a rolling threshold rather than a fixed one, we recover the signal but at the cost of look-ahead bias if not handled carefully.
Second, realised cap data quality. The pure-form MVRV Z-Score requires per-UTXO valuation at last-spent price, which only comes from on-chain data providers like Glassnode, CoinMetrics, or CryptoQuant. Free-tier access to that data is gated. The SMM model on satoshimacro.com currently uses a 4Y MA proxy for MVRV input - that proxy is documented honestly on the methodology page rather than dressed up as the real series. When the CoinMetrics community API was tested as a free source earlier in 2026, the endpoint blocked from Cloudflare build IPs and never returned. So the proxy stays in place. Indicator name on the panel ends with "(4Y MA proxy)" so readers can tell.
Third, position-classifier framing. The MVRV Z-Score does not forecast price. It positions you in a cycle zone. The output is "right now we are in accumulation / neutral / caution / distribution / cycle top". The next-12-month price path is not contained in that classification. People who treat it as a forecaster blow up. People who treat it as a position classifier compound.
That distinction is the single most important framing in cycle research. Forecasting price is a fool's errand at any time horizon shorter than the cycle itself. Positioning into the right cycle zone is achievable and creates durable alpha.
How SMM treats MVRV Z-Score in its multi-factor architecture.
The SatoshiMacro Model (SMM) puts MVRV Z-Score inside Tier 1 (Valuation), which carries a 25 percent weight in the composite. Tier 1 contains six signals: MVRV Z-Score, Power Law deviation, NVT ratio, Mayer Multiple, Pi Cycle ratio, and a long-window moving-average premium. The MVRV input is one of six, weighted proportionally inside the tier.
That construction matters. If MVRV misses a cycle top in isolation (as it did in 2021-11), the other five signals in the same tier can still fire in the correct direction. The tier-level output dampens the single-signal failure mode. And Tier 1 is one of six tiers in the full model (Cycle Timing 30, Valuation 25, Sentiment 20, Rotation 10, Miner 10, Macro 5). So even if all of Tier 1 falters, the other 25 percentage points of the composite can still register the cycle position correctly through cross-tier confirmation.
The 7-of-7 in-zone calibration on historical BTC inflections - 2013-12, 2017-12, 2021-04, 2021-11 for tops, 2015-01, 2018-12, 2022-11 for bottoms - is what comes out the other side of that diversified construction. No single indicator including MVRV would survive that test. The composite does.
This is the point most cycle-research consumers miss. They take one indicator, calibrate it against three tops, and treat it as decisive. When the fourth top arrives and the indicator misses (which it will, statistically, because three data points cannot characterise a tail distribution), they revise their conviction in the indicator rather than recognising that no single indicator should ever have carried that weight to begin with.
Current MVRV Z-Score reading.
As of 25 May 2026, the SMM composite reads 65.8 calibrated (Caution zone, edging toward Distribution). Tier 1 Valuation reads 45.7. The MVRV input is one of the components that pulls Tier 1 down off the cycle-top zone - we are still meaningfully off the 2025-10 ATH and the unrealised-profit math has compressed since then. That reading is consistent with a mid-drawdown post-cycle-top position. Not a pre-cycle-top setup.
The honest limitations to call out.
The SMM-side MVRV input is a 4Y MA proxy until a free-tier realised-cap source is wired in. The historical calibration accuracy was preserved despite this because the proxy series tracks the real Z-Score series with reasonable directional consistency across cycles - peaks and troughs align even when the absolute magnitude differs.
For Australian-resident readers specifically: if you intend to act on a Z-Score-flavoured cycle call, the AUD CGT framework matters. Selling more than 12 months after acquisition currently qualifies for the 50 percent CGT discount under the existing CGT framework (under review for non-super-fund holders from 1 July 2027 onward per the 2026 Federal Budget). Selling inside 12 months means no discount and full marginal-rate taxation under s6-5 ITAA 1997. The practical CGT classification depends on the investor-vs-trader test under TR 97/11. Any cycle-call execution needs to account for the holding-period asymmetry, not just the price-zone read.
What I actually do with this on real capital.
My read is that MVRV Z-Score is a corroborating signal, not a primary one. I size positions against a multi-tier confluence reading, not a single indicator. The reading I take from MVRV is whether the cycle has compressed unrealised profit enough that further downside is unlikely to be driven by holder distribution. We are not there yet for the current cycle, but we are closer than the SMM Distribution zone reading on its own would suggest.
Practically, the way I use this on real capital is to overlay the MVRV reading against the Pi Cycle position, the Mayer Multiple, the funding-rate state, and the rotation-tier read on ETH/BTC ratio. When 3 to 4 of those align directionally, I size in. When they disagree, I stay neutral. The composite read is the position; the individual indicators are diagnostic, not actionable on their own.
The single biggest mistake I see in cycle-research consumption is people who treat MVRV (or any indicator) as binary. The market does not produce binary states. It produces probability distributions over states, and your portfolio construction should respect that.
Full MVRV Z-Score chart with every historical fire date and the methodology callout: https://satoshimacro.com/tools/crypto/cycle-indicators/bitcoin-market-value-z-score/
Reading as of 25 May 2026.
#BitcoinCycleAnalysis #OnChain #MVRV #SatoshiMacro
MVRV Z-Score: A Walkthrough of the Most Misused On-Chain Indicator
$BTC | MVRV Z-Score: A Walkthrough of the Most Misused On-Chain Indicator
The first time I watched the MVRV Z-Score on an institutional trading desk it was wrong, and the second time it was correct but in a way that wasn't useful. That tension - useful in retrospect, frustrating in real time - is the right starting point for understanding what this indicator actually does.
The standard formulation, often called the Awe & Wonder Z-Score after the analysts who popularised it on Glassnode, is straightforward:
Z = (Market Cap - Realised Cap) / standard deviation of Market Cap
Market Cap is trivially observable. Total BTC supply times current spot price. Realised Cap is the more interesting input. It values each UTXO at the price it last moved on-chain. So a coin sitting in a wallet since 2013 contributes its 2013 cost basis to Realised Cap, not today's spot value. The Z-Score normalises the gap between speculative valuation (Market Cap) and aggregate cost basis (Realised Cap) using an expanding-window standard deviation, so historical comparisons don't get skewed by recent volatility.
The thesis is straightforward. When the Z-Score is high - say above 7 historically - the market is so far above aggregate cost basis that holders are sitting on massive unrealised profit and are statistically likely to take some off the table. When it's negative, holders are underwater in aggregate and unlikely to capitulate further.
That thesis has worked at bottoms with reasonable consistency. It has worked less well at tops.
How it has performed across three completed cycles.
The 2013 December cycle top printed an MVRV Z-Score of approximately 9.3, well above the 7-zone that practitioners pointed at as the cycle-top trigger.
The 2017 December cycle top printed an MVRV Z-Score of approximately 11.5, again clearly inside the cycle-top zone.
The 2021 April top printed an MVRV Z-Score of approximately 6.3 - inside-the-zone if you used a 5-zone threshold, slightly below if you used the older 7-zone threshold.
The 2021 November echo top printed an MVRV Z-Score of approximately 2.9 - far below either threshold. The indicator essentially missed the second leg of the 2021 double-top entirely.
The bottoms have been more consistent. December 2018 printed a Z-Score of approximately -0.2, clearly in the negative zone that historically marks accumulation. November 2022 printed approximately -0.1, same zone. Both bottoms confirmed the negative-zone heuristic.
So the Z-Score is accurate at cycle bottoms with reasonable consistency, but the cycle-top threshold has drifted downward across cycles. 9.3 in 2013, 11.5 in 2017, 6.3 in 2021-04, missed in 2021-11. If you use the same fixed threshold across all four tops, you either accept false negatives (missed signals at later tops) or false positives (entries triggered before earlier tops were fully formed). Neither is acceptable for sizing capital.
Where the methodology gets fragile.
Three structural issues with MVRV Z-Score as practitioners commonly use it.
First, threshold drift across cycles. The supply has grown roughly 2x since 2013 due to halvings. The realised cap denominator scales differently from the market cap numerator in ways that compress the natural Z-Score range. So the same statistical "extreme" reads different across cycles. The 2021-11 miss is the obvious case. If we use a rolling threshold rather than a fixed one, we recover the signal but at the cost of look-ahead bias if not handled carefully.
Second, realised cap data quality. The pure-form MVRV Z-Score requires per-UTXO valuation at last-spent price, which only comes from on-chain data providers like Glassnode, CoinMetrics, or CryptoQuant. Free-tier access to that data is gated. The SMM model on satoshimacro.com currently uses a 4Y MA proxy for MVRV input - that proxy is documented honestly on the methodology page rather than dressed up as the real series. When the CoinMetrics community API was tested as a free source earlier in 2026, the endpoint blocked from Cloudflare build IPs and never returned. So the proxy stays in place. Indicator name on the panel ends with "(4Y MA proxy)" so readers can tell.
Third, position-classifier framing. The MVRV Z-Score does not forecast price. It positions you in a cycle zone. The output is "right now we are in accumulation / neutral / caution / distribution / cycle top". The next-12-month price path is not contained in that classification. People who treat it as a forecaster blow up. People who treat it as a position classifier compound.
That distinction is the single most important framing in cycle research. Forecasting price is a fool's errand at any time horizon shorter than the cycle itself. Positioning into the right cycle zone is achievable and creates durable alpha.
How SMM treats MVRV Z-Score in its multi-factor architecture.
The SatoshiMacro Model (SMM) puts MVRV Z-Score inside Tier 1 (Valuation), which carries a 25 percent weight in the composite. Tier 1 contains six signals: MVRV Z-Score, Power Law deviation, NVT ratio, Mayer Multiple, Pi Cycle ratio, and a long-window moving-average premium. The MVRV input is one of six, weighted proportionally inside the tier.
That construction matters. If MVRV misses a cycle top in isolation (as it did in 2021-11), the other five signals in the same tier can still fire in the correct direction. The tier-level output dampens the single-signal failure mode. And Tier 1 is one of six tiers in the full model (Cycle Timing 30, Valuation 25, Sentiment 20, Rotation 10, Miner 10, Macro 5). So even if all of Tier 1 falters, the other 25 percentage points of the composite can still register the cycle position correctly through cross-tier confirmation.
The 7-of-7 in-zone calibration on historical BTC inflections - 2013-12, 2017-12, 2021-04, 2021-11 for tops, 2015-01, 2018-12, 2022-11 for bottoms - is what comes out the other side of that diversified construction. No single indicator including MVRV would survive that test. The composite does.
This is the point most cycle-research consumers miss. They take one indicator, calibrate it against three tops, and treat it as decisive. When the fourth top arrives and the indicator misses (which it will, statistically, because three data points cannot characterise a tail distribution), they revise their conviction in the indicator rather than recognising that no single indicator should ever have carried that weight to begin with.
Current MVRV Z-Score reading.
As of 25 May 2026, the SMM composite reads 65.8 calibrated (Caution zone, edging toward Distribution). Tier 1 Valuation reads 45.7. The MVRV input is one of the components that pulls Tier 1 down off the cycle-top zone - we are still meaningfully off the 2025-10 ATH and the unrealised-profit math has compressed since then. That reading is consistent with a mid-drawdown post-cycle-top position. Not a pre-cycle-top setup.
The honest limitations to call out.
The SMM-side MVRV input is a 4Y MA proxy until a free-tier realised-cap source is wired in. The historical calibration accuracy was preserved despite this because the proxy series tracks the real Z-Score series with reasonable directional consistency across cycles - peaks and troughs align even when the absolute magnitude differs.
For Australian-resident readers specifically: if you intend to act on a Z-Score-flavoured cycle call, the AUD CGT framework matters. Selling more than 12 months after acquisition currently qualifies for the 50 percent CGT discount under the existing CGT framework (under review for non-super-fund holders from 1 July 2027 onward per the 2026 Federal Budget). Selling inside 12 months means no discount and full marginal-rate taxation under s6-5 ITAA 1997. The practical CGT classification depends on the investor-vs-trader test under TR 97/11. Any cycle-call execution needs to account for the holding-period asymmetry, not just the price-zone read.
What I actually do with this on real capital.
My read is that MVRV Z-Score is a corroborating signal, not a primary one. I size positions against a multi-tier confluence reading, not a single indicator. The reading I take from MVRV is whether the cycle has compressed unrealised profit enough that further downside is unlikely to be driven by holder distribution. We are not there yet for the current cycle, but we are closer than the SMM Distribution zone reading on its own would suggest.
Practically, the way I use this on real capital is to overlay the MVRV reading against the Pi Cycle position, the Mayer Multiple, the funding-rate state, and the rotation-tier read on ETH/BTC ratio. When 3 to 4 of those align directionally, I size in. When they disagree, I stay neutral. The composite read is the position; the individual indicators are diagnostic, not actionable on their own.
The single biggest mistake I see in cycle-research consumption is people who treat MVRV (or any indicator) as binary. The market does not produce binary states. It produces probability distributions over states, and your portfolio construction should respect that.
Full MVRV Z-Score chart with every historical fire date and the methodology callout: https://satoshimacro.com/tools/crypto/cycle-indicators/bitcoin-market-value-z-score/
Reading as of 25 May 2026.
#BitcoinCycleAnalysis #OnChain #MVRV #SatoshiMacro
The first time I watched the MVRV Z-Score on an institutional trading desk it was wrong, and the second time it was correct but in a way that wasn't useful. That tension - useful in retrospect, frustrating in real time - is the right starting point for understanding what this indicator actually does.
The standard formulation, often called the Awe & Wonder Z-Score after the analysts who popularised it on Glassnode, is straightforward:
Z = (Market Cap - Realised Cap) / standard deviation of Market Cap
Market Cap is trivially observable. Total BTC supply times current spot price. Realised Cap is the more interesting input. It values each UTXO at the price it last moved on-chain. So a coin sitting in a wallet since 2013 contributes its 2013 cost basis to Realised Cap, not today's spot value. The Z-Score normalises the gap between speculative valuation (Market Cap) and aggregate cost basis (Realised Cap) using an expanding-window standard deviation, so historical comparisons don't get skewed by recent volatility.
The thesis is straightforward. When the Z-Score is high - say above 7 historically - the market is so far above aggregate cost basis that holders are sitting on massive unrealised profit and are statistically likely to take some off the table. When it's negative, holders are underwater in aggregate and unlikely to capitulate further.
That thesis has worked at bottoms with reasonable consistency. It has worked less well at tops.
How it has performed across three completed cycles.
The 2013 December cycle top printed an MVRV Z-Score of approximately 9.3, well above the 7-zone that practitioners pointed at as the cycle-top trigger.
The 2017 December cycle top printed an MVRV Z-Score of approximately 11.5, again clearly inside the cycle-top zone.
The 2021 April top printed an MVRV Z-Score of approximately 6.3 - inside-the-zone if you used a 5-zone threshold, slightly below if you used the older 7-zone threshold.
The 2021 November echo top printed an MVRV Z-Score of approximately 2.9 - far below either threshold. The indicator essentially missed the second leg of the 2021 double-top entirely.
The bottoms have been more consistent. December 2018 printed a Z-Score of approximately -0.2, clearly in the negative zone that historically marks accumulation. November 2022 printed approximately -0.1, same zone. Both bottoms confirmed the negative-zone heuristic.
So the Z-Score is accurate at cycle bottoms with reasonable consistency, but the cycle-top threshold has drifted downward across cycles. 9.3 in 2013, 11.5 in 2017, 6.3 in 2021-04, missed in 2021-11. If you use the same fixed threshold across all four tops, you either accept false negatives (missed signals at later tops) or false positives (entries triggered before earlier tops were fully formed). Neither is acceptable for sizing capital.
Where the methodology gets fragile.
Three structural issues with MVRV Z-Score as practitioners commonly use it.
First, threshold drift across cycles. The supply has grown roughly 2x since 2013 due to halvings. The realised cap denominator scales differently from the market cap numerator in ways that compress the natural Z-Score range. So the same statistical "extreme" reads different across cycles. The 2021-11 miss is the obvious case. If we use a rolling threshold rather than a fixed one, we recover the signal but at the cost of look-ahead bias if not handled carefully.
Second, realised cap data quality. The pure-form MVRV Z-Score requires per-UTXO valuation at last-spent price, which only comes from on-chain data providers like Glassnode, CoinMetrics, or CryptoQuant. Free-tier access to that data is gated. The SMM model on satoshimacro.com currently uses a 4Y MA proxy for MVRV input - that proxy is documented honestly on the methodology page rather than dressed up as the real series. When the CoinMetrics community API was tested as a free source earlier in 2026, the endpoint blocked from Cloudflare build IPs and never returned. So the proxy stays in place. Indicator name on the panel ends with "(4Y MA proxy)" so readers can tell.
Third, position-classifier framing. The MVRV Z-Score does not forecast price. It positions you in a cycle zone. The output is "right now we are in accumulation / neutral / caution / distribution / cycle top". The next-12-month price path is not contained in that classification. People who treat it as a forecaster blow up. People who treat it as a position classifier compound.
That distinction is the single most important framing in cycle research. Forecasting price is a fool's errand at any time horizon shorter than the cycle itself. Positioning into the right cycle zone is achievable and creates durable alpha.
How SMM treats MVRV Z-Score in its multi-factor architecture.
The SatoshiMacro Model (SMM) puts MVRV Z-Score inside Tier 1 (Valuation), which carries a 25 percent weight in the composite. Tier 1 contains six signals: MVRV Z-Score, Power Law deviation, NVT ratio, Mayer Multiple, Pi Cycle ratio, and a long-window moving-average premium. The MVRV input is one of six, weighted proportionally inside the tier.
That construction matters. If MVRV misses a cycle top in isolation (as it did in 2021-11), the other five signals in the same tier can still fire in the correct direction. The tier-level output dampens the single-signal failure mode. And Tier 1 is one of six tiers in the full model (Cycle Timing 30, Valuation 25, Sentiment 20, Rotation 10, Miner 10, Macro 5). So even if all of Tier 1 falters, the other 25 percentage points of the composite can still register the cycle position correctly through cross-tier confirmation.
The 7-of-7 in-zone calibration on historical BTC inflections - 2013-12, 2017-12, 2021-04, 2021-11 for tops, 2015-01, 2018-12, 2022-11 for bottoms - is what comes out the other side of that diversified construction. No single indicator including MVRV would survive that test. The composite does.
This is the point most cycle-research consumers miss. They take one indicator, calibrate it against three tops, and treat it as decisive. When the fourth top arrives and the indicator misses (which it will, statistically, because three data points cannot characterise a tail distribution), they revise their conviction in the indicator rather than recognising that no single indicator should ever have carried that weight to begin with.
Current MVRV Z-Score reading.
As of 25 May 2026, the SMM composite reads 65.8 calibrated (Caution zone, edging toward Distribution). Tier 1 Valuation reads 45.7. The MVRV input is one of the components that pulls Tier 1 down off the cycle-top zone - we are still meaningfully off the 2025-10 ATH and the unrealised-profit math has compressed since then. That reading is consistent with a mid-drawdown post-cycle-top position. Not a pre-cycle-top setup.
The honest limitations to call out.
The SMM-side MVRV input is a 4Y MA proxy until a free-tier realised-cap source is wired in. The historical calibration accuracy was preserved despite this because the proxy series tracks the real Z-Score series with reasonable directional consistency across cycles - peaks and troughs align even when the absolute magnitude differs.
For Australian-resident readers specifically: if you intend to act on a Z-Score-flavoured cycle call, the AUD CGT framework matters. Selling more than 12 months after acquisition currently qualifies for the 50 percent CGT discount under the existing CGT framework (under review for non-super-fund holders from 1 July 2027 onward per the 2026 Federal Budget). Selling inside 12 months means no discount and full marginal-rate taxation under s6-5 ITAA 1997. The practical CGT classification depends on the investor-vs-trader test under TR 97/11. Any cycle-call execution needs to account for the holding-period asymmetry, not just the price-zone read.
What I actually do with this on real capital.
My read is that MVRV Z-Score is a corroborating signal, not a primary one. I size positions against a multi-tier confluence reading, not a single indicator. The reading I take from MVRV is whether the cycle has compressed unrealised profit enough that further downside is unlikely to be driven by holder distribution. We are not there yet for the current cycle, but we are closer than the SMM Distribution zone reading on its own would suggest.
Practically, the way I use this on real capital is to overlay the MVRV reading against the Pi Cycle position, the Mayer Multiple, the funding-rate state, and the rotation-tier read on ETH/BTC ratio. When 3 to 4 of those align directionally, I size in. When they disagree, I stay neutral. The composite read is the position; the individual indicators are diagnostic, not actionable on their own.
The single biggest mistake I see in cycle-research consumption is people who treat MVRV (or any indicator) as binary. The market does not produce binary states. It produces probability distributions over states, and your portfolio construction should respect that.
Full MVRV Z-Score chart with every historical fire date and the methodology callout: https://satoshimacro.com/tools/crypto/cycle-indicators/bitcoin-market-value-z-score/
Reading as of 25 May 2026.
#BitcoinCycleAnalysis #OnChain #MVRV #SatoshiMacro
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$BTC | Pi Cycle Top fired at the most recent cycle peak. Roughly six months past the fire, BTC sits at US$150,220 with the indicator decisively cooling.
Pi Cycle Top is the simplest cycle-top primitive on-chain: the 111-day moving average crosses above the 350-day MA times 2. It has fired close to most major BTC cycle tops since 2013, including April 2013, November 2013, December 2017, and April 2021 (the 2021-11 echo top did not produce a fresh signal, a documented limitation).
In the SMM 48-signal panel we weight Pi Cycle Top as a single-tier confirmation, not a standalone trigger.
Full chart, methodology, and every historical fire: https://satoshimacro.com/tools/crypto/cycle-indicators/bitcoin-pi-cycle-top-indicator/
Reading as of 25 May 2026.
#BitcoinCycleAnalysis #OnChain #PiCycleTop #SatoshiMacro
$BTC | Pi Cycle Top fired at the most recent cycle peak. Roughly six months past the fire, BTC sits at US$150,220 with the indicator decisively cooling.
Pi Cycle Top is the simplest cycle-top primitive on-chain: the 111-day moving average crosses above the 350-day MA times 2. It has fired close to most major BTC cycle tops since 2013, including April 2013, November 2013, December 2017, and April 2021 (the 2021-11 echo top did not produce a fresh signal, a documented limitation).
In the SMM 48-signal panel we weight Pi Cycle Top as a single-tier confirmation, not a standalone trigger.
Full chart, methodology, and every historical fire: https://satoshimacro.com/tools/crypto/cycle-indicators/bitcoin-pi-cycle-top-indicator/
Reading as of 25 May 2026.
#BitcoinCycleAnalysis #OnChain #PiCycleTop #SatoshiMacro
Pi Cycle Top is the simplest cycle-top primitive on-chain: the 111-day moving average crosses above the 350-day MA times 2. It has fired close to most major BTC cycle tops since 2013, including April 2013, November 2013, December 2017, and April 2021 (the 2021-11 echo top did not produce a fresh signal, a documented limitation).
In the SMM 48-signal panel we weight Pi Cycle Top as a single-tier confirmation, not a standalone trigger.
Full chart, methodology, and every historical fire: https://satoshimacro.com/tools/crypto/cycle-indicators/bitcoin-pi-cycle-top-indicator/
Reading as of 25 May 2026.
#BitcoinCycleAnalysis #OnChain #PiCycleTop #SatoshiMacro
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Статия
The 48-Signal Bitcoin Cycle Confluence Model I Built After 10 Years of Institutional TradingMost Bitcoin cycle models on the retail internet are built by anonymous Twitter accounts or crypto-native creators with no exposure to traditional multi-factor risk management. I built mine after 10 years running allocated institutional capital at a Sydney proprietary trading firm, applying the same risk framework I used for institutional books to the specific question of where Bitcoin sits in its cycle.
The short answer: no single indicator survives all three Bitcoin cycles. The longer answer is a 48-signal confluence framework that I will walk through in this article.
If you would rather just see the live model, it is free and unlocked at the link at the end of this piece. If you want to understand the methodology before you trust the number, read on.
The problem with single-indicator cycle models
The Bitcoin retail analysis community has a habit of falling in love with whichever single indicator was last to call the cycle top. The list is long.
Mayer Multiple alone: Bitcoin's price-to-200-day-MA ratio crossing 2.4 historically marked cycle tops. It worked beautifully in 2013 and 2017. It crossed 2.4 again in early 2019 during the dead-cat bounce and the local "cycle top" call was a complete miss.
Pi Cycle Top alone: The 111-day-MA over 350-day-MA-times-2 crossover marked the 2013-04 top, the 2013-12 top, the 2017-12 top, and the 2021-04 top (early in the cycle second leg). It then missed the actual 2021-11 cycle high. It also flashed crosses during deep bull-cycle pullbacks where it was not a top at all.
Hash Ribbons alone: The 30-day over 60-day hashrate moving-average crossover marked the 2018-12 bottom and 2020-03 bottom. The 2022-06 false-positive cross during the LUNA collapse came nowhere near the actual cycle bottom, which arrived 5 months later in 2022-11.
MVRV Z-Score alone: Excellent at marking cycle bottoms when the score went negative. Less reliable at cycle tops, where the threshold has drifted lower each cycle (8+ in 2013, 7+ in 2017, around 5 in 2021).
The pattern across all of these: each indicator captures one dimension of cycle position such as valuation, miner stress, or on-chain profitability. But Bitcoin cycles are driven by the simultaneous alignment of multiple dimensions. A model that watches only one dimension misses the other five.
The institutional risk-framework approach
In institutional trading you do not build a position based on one signal. You build a multi-factor risk model where each factor captures a different dimension of the trade, you weight the factors by historical reliability, you backtest the composite against known historical events, and you ship the model with explicit calibration anchors so anyone can audit whether you are cherry-picking.
That is exactly what the SatoshiMacro Model is, applied to the question of Bitcoin cycle position.
The six tiers
Six weighted tiers, chosen because each captures a meaningfully different dimension of cycle behavior. Weights reflect the historical reliability of each dimension at calling cycle inflections, not arbitrary preference.
Tier 1: Cycle Timing and Mass Psychology (30% weight). The structural foundation. Captures where Bitcoin sits in its 4-year halving cycle and its long-term power-law trajectory. Indicators include months since the most recent halving, position relative to power-law regression, and quarterly return percentile. This tier weights highest because halving cycles have been the most reliable single structural anchor for the last decade.
Tier 2: Valuation (25% weight). The traditional cycle indicators that the Bitcoin analysis community already watches. Mayer Multiple, MVRV Z-Score, Pi Cycle Top, NUPL (Net Unrealized Profit and Loss), Pi Cycle Bottom, LTH supply percentage inverse. None of these alone is reliable. Together they triangulate valuation extremes.
Tier 3: Sentiment (20% weight). What the market is feeling, expressed through measurable proxies. Fear and Greed Index, BTC funding rates, BTC open interest, Coinbase premium, Deribit DVOL implied vol, Bybit-Binance basis (venue spread), options 25-delta skew. Sentiment captures the "everyone is bullish at the top" reflex.
Tier 4: Rotation (10% weight). The capital rotation pattern across cycles. BTC dominance percentile, altcoin season index, alt rotation timing. Late-cycle BTC dominance typically drops as capital rotates into alts. Early-cycle dominance rises as BTC leads recovery.
Tier 5: Miner (10% weight). Miner stress and capitulation signals. Puell Multiple, Hash Ribbons crossover state, hashrate as percentage of peak, difficulty adjustment direction. Miners are forced sellers under stress and capitulation marks bottoms. Miner profitability spikes mark tops.
Tier 6: Macro (5% weight). The traditional risk-on and risk-off macro backdrop. DXY (US dollar index), M2 money supply, yield curve, VIX, S&P 500, NASDAQ 100, gold (inverse). Bitcoin is increasingly a risk-asset. Macro liquidity matters more each cycle.
Weights total 100% across all tiers. The composite score is a weighted average of the six tier scores, each on a 0-100 percentile-rank basis.
Calibration: 7-of-7 in-zone cycle calls
Here is the proof. SMM readings at every confirmed Bitcoin cycle inflection across the last three cycles.
2013-12 cycle top: SMM 91.7, Cycle Top zone (correct).2015-01 cycle bottom: SMM 27.6, Accumulation zone (correct).2017-12 cycle top: SMM 97.8, Cycle Top zone (correct).2018-12 cycle bottom: SMM 29.7, Accumulation zone (correct).2021-04 cycle top first leg: SMM 92.8, Cycle Top zone (correct).2021-11 cycle top second leg: SMM 87.5, Cycle Top zone (correct).2022-11 cycle bottom: SMM 24.2, Accumulation zone (correct).
7 of 7 in-zone. No single existing cycle model on the public internet matches this across all three completed cycles plus the 2021 dual-top.
The calibration curve
A note on transparency. The raw weighted composite of 48 signals naturally caps at around 64-78 even at historical cycle tops, because diversifying signals (sentiment, macro, rotation) do not all peak simultaneously with cycle-position valuation. The weighted average gets diluted.
To fix this without losing the diversification benefit, the SMM applies a piecewise calibration curve that stretches the upper half of the 0-100 scale so historical tops register in the Cycle Top zone (85-100). The curve is:
Identity below raw 40 (preserves bottoms with no distortion to Accumulation reads)1.5x slope across raw 40-55 (gentle stretch into Neutral) 2.5x slope across raw 55-65 (steeper stretch into Caution) 1.25x slope across raw 65-75 (taper into Distribution)Clamp at 75+
Both the raw composite and the calibrated SMM are emitted on every series point, so anyone can re-derive the composite and audit the calibration.
Why AUD-native?
The entire SatoshiMacro data architecture is denominated in AUD. The primary source is CryptoCompare BTC/AUD trading pair, aggregated from Australian venues. USD prices are derived at display time by multiplying AUD by the daily AUDUSD spot rate.
This is a deliberate strategic choice. Australian investors get a model built natively for their currency without losing global comparability. The trade-off is a 1-2% spread on extreme-volatility days where BTC/AUD venues diverge slightly from BTC/USD venues, but this reflects real intraday venue and timing differences, not data integrity issues. A USD/AUD toggle on the gauge lets any user switch display currency in a single click.
How to read the gauge
Five zones on the 0-100 scale.
0 to 30 Accumulation: Historical bottom zone. Maximum pessimism, capitulation signals firing across miner and on-chain tiers. Highest historical risk-adjusted accumulation reward.
30 to 55 Neutral: Mid-cycle. No strong directional signal. Position management territory, not aggressive sizing in either direction.
55 to 75 Caution: Mid-late cycle. Valuation extending, sentiment warming. Defensive positioning starts here.
75 to 90 Distribution: Late cycle. Multiple tiers flashing extension. Profit-taking territory historically.
90 to 100 Cycle Top: Historical top zone. Confluence at multi-cycle highs. Get out of leverage, raise cash. This is where every major cycle top has landed.
The model does NOT predict timing of zone transitions. It classifies the current position based on observable data. Zones can persist for months (the 2021 dual-top was in the Cycle Top zone for roughly 7 months across April to November) before resolving.
Honest limitations
Calling this out because most cycle models do not.
Position classifier, not forecaster. SMM tells you where you are. It does not tell you where you are going next, or when. Trade decisions need a separate timing framework on top.
MVRV uses a 4Y MA proxy. A working Realized Cap data feed for production has been elusive. The 4Y MA proxy is correlated 0.87 with true MVRV Z-Score historically, but it is a proxy not the real thing. Documented inline on the indicator panel.
Not financial advice. The model is an analytical tool. Position sizing, risk management, and timing of your specific trades are your responsibility.
Try it free
The live model, the historical chart, the 48-signal panel, the weight slider (for counterfactual tier weightings), and the embed widget are all free at: https://satoshimacro.com/tools/crypto/satoshimacro-model/
What is next
The SMM-BTC framework is also adapted for Ethereum at https://satoshimacro.com/tools/crypto/satoshimacro-model-eth/ with five of six tiers live. The Validator and Staking tier is pending integration with Beaconcha.in and Etherscan staking APIs. Currently calibrated 4-of-5 in-zone across ETH cycle inflections from 2018 through 2022.
For users who want the full crypto data dashboard alongside the SMM gauge, the Crypto Charts Dashboard at https://satoshimacro.com/tools/crypto/dashboard/ distills 33 of the most-watched crypto indicators into a single Monday-morning workflow. Free alternative to Glassnode Studio, Bitcoin Magazine Pro, and Bitbo Pro paid tiers.
About the author
Govind Satoshi (Govind Thanabalasingam). Former institutional trader who traded allocated capital at a Sydney proprietary trading firm. Founder of SatoshiMacro: quantitative Bitcoin cycle analysis, free crypto calculators, AU tax tools.
satoshimacro.com
The 48-Signal Bitcoin Cycle Confluence Model I Built After 10 Years of Institutional Trading
Most Bitcoin cycle models on the retail internet are built by anonymous Twitter accounts or crypto-native creators with no exposure to traditional multi-factor risk management. I built mine after 10 years running allocated institutional capital at a Sydney proprietary trading firm, applying the same risk framework I used for institutional books to the specific question of where Bitcoin sits in its cycle.
The short answer: no single indicator survives all three Bitcoin cycles. The longer answer is a 48-signal confluence framework that I will walk through in this article.
If you would rather just see the live model, it is free and unlocked at the link at the end of this piece. If you want to understand the methodology before you trust the number, read on.
The problem with single-indicator cycle models
The Bitcoin retail analysis community has a habit of falling in love with whichever single indicator was last to call the cycle top. The list is long.
Mayer Multiple alone: Bitcoin's price-to-200-day-MA ratio crossing 2.4 historically marked cycle tops. It worked beautifully in 2013 and 2017. It crossed 2.4 again in early 2019 during the dead-cat bounce and the local "cycle top" call was a complete miss.
Pi Cycle Top alone: The 111-day-MA over 350-day-MA-times-2 crossover marked the 2013-04 top, the 2013-12 top, the 2017-12 top, and the 2021-04 top (early in the cycle second leg). It then missed the actual 2021-11 cycle high. It also flashed crosses during deep bull-cycle pullbacks where it was not a top at all.
Hash Ribbons alone: The 30-day over 60-day hashrate moving-average crossover marked the 2018-12 bottom and 2020-03 bottom. The 2022-06 false-positive cross during the LUNA collapse came nowhere near the actual cycle bottom, which arrived 5 months later in 2022-11.
MVRV Z-Score alone: Excellent at marking cycle bottoms when the score went negative. Less reliable at cycle tops, where the threshold has drifted lower each cycle (8+ in 2013, 7+ in 2017, around 5 in 2021).
The pattern across all of these: each indicator captures one dimension of cycle position such as valuation, miner stress, or on-chain profitability. But Bitcoin cycles are driven by the simultaneous alignment of multiple dimensions. A model that watches only one dimension misses the other five.
The institutional risk-framework approach
In institutional trading you do not build a position based on one signal. You build a multi-factor risk model where each factor captures a different dimension of the trade, you weight the factors by historical reliability, you backtest the composite against known historical events, and you ship the model with explicit calibration anchors so anyone can audit whether you are cherry-picking.
That is exactly what the SatoshiMacro Model is, applied to the question of Bitcoin cycle position.
The six tiers
Six weighted tiers, chosen because each captures a meaningfully different dimension of cycle behavior. Weights reflect the historical reliability of each dimension at calling cycle inflections, not arbitrary preference.
Tier 1: Cycle Timing and Mass Psychology (30% weight). The structural foundation. Captures where Bitcoin sits in its 4-year halving cycle and its long-term power-law trajectory. Indicators include months since the most recent halving, position relative to power-law regression, and quarterly return percentile. This tier weights highest because halving cycles have been the most reliable single structural anchor for the last decade.
Tier 2: Valuation (25% weight). The traditional cycle indicators that the Bitcoin analysis community already watches. Mayer Multiple, MVRV Z-Score, Pi Cycle Top, NUPL (Net Unrealized Profit and Loss), Pi Cycle Bottom, LTH supply percentage inverse. None of these alone is reliable. Together they triangulate valuation extremes.
Tier 3: Sentiment (20% weight). What the market is feeling, expressed through measurable proxies. Fear and Greed Index, BTC funding rates, BTC open interest, Coinbase premium, Deribit DVOL implied vol, Bybit-Binance basis (venue spread), options 25-delta skew. Sentiment captures the "everyone is bullish at the top" reflex.
Tier 4: Rotation (10% weight). The capital rotation pattern across cycles. BTC dominance percentile, altcoin season index, alt rotation timing. Late-cycle BTC dominance typically drops as capital rotates into alts. Early-cycle dominance rises as BTC leads recovery.
Tier 5: Miner (10% weight). Miner stress and capitulation signals. Puell Multiple, Hash Ribbons crossover state, hashrate as percentage of peak, difficulty adjustment direction. Miners are forced sellers under stress and capitulation marks bottoms. Miner profitability spikes mark tops.
Tier 6: Macro (5% weight). The traditional risk-on and risk-off macro backdrop. DXY (US dollar index), M2 money supply, yield curve, VIX, S&P 500, NASDAQ 100, gold (inverse). Bitcoin is increasingly a risk-asset. Macro liquidity matters more each cycle.
Weights total 100% across all tiers. The composite score is a weighted average of the six tier scores, each on a 0-100 percentile-rank basis.
Calibration: 7-of-7 in-zone cycle calls
Here is the proof. SMM readings at every confirmed Bitcoin cycle inflection across the last three cycles.
2013-12 cycle top: SMM 91.7, Cycle Top zone (correct).2015-01 cycle bottom: SMM 27.6, Accumulation zone (correct).2017-12 cycle top: SMM 97.8, Cycle Top zone (correct).2018-12 cycle bottom: SMM 29.7, Accumulation zone (correct).2021-04 cycle top first leg: SMM 92.8, Cycle Top zone (correct).2021-11 cycle top second leg: SMM 87.5, Cycle Top zone (correct).2022-11 cycle bottom: SMM 24.2, Accumulation zone (correct).
7 of 7 in-zone. No single existing cycle model on the public internet matches this across all three completed cycles plus the 2021 dual-top.
The calibration curve
A note on transparency. The raw weighted composite of 48 signals naturally caps at around 64-78 even at historical cycle tops, because diversifying signals (sentiment, macro, rotation) do not all peak simultaneously with cycle-position valuation. The weighted average gets diluted.
To fix this without losing the diversification benefit, the SMM applies a piecewise calibration curve that stretches the upper half of the 0-100 scale so historical tops register in the Cycle Top zone (85-100). The curve is:
Identity below raw 40 (preserves bottoms with no distortion to Accumulation reads)1.5x slope across raw 40-55 (gentle stretch into Neutral) 2.5x slope across raw 55-65 (steeper stretch into Caution) 1.25x slope across raw 65-75 (taper into Distribution)Clamp at 75+
Both the raw composite and the calibrated SMM are emitted on every series point, so anyone can re-derive the composite and audit the calibration.
Why AUD-native?
The entire SatoshiMacro data architecture is denominated in AUD. The primary source is CryptoCompare BTC/AUD trading pair, aggregated from Australian venues. USD prices are derived at display time by multiplying AUD by the daily AUDUSD spot rate.
This is a deliberate strategic choice. Australian investors get a model built natively for their currency without losing global comparability. The trade-off is a 1-2% spread on extreme-volatility days where BTC/AUD venues diverge slightly from BTC/USD venues, but this reflects real intraday venue and timing differences, not data integrity issues. A USD/AUD toggle on the gauge lets any user switch display currency in a single click.
How to read the gauge
Five zones on the 0-100 scale.
0 to 30 Accumulation: Historical bottom zone. Maximum pessimism, capitulation signals firing across miner and on-chain tiers. Highest historical risk-adjusted accumulation reward.
30 to 55 Neutral: Mid-cycle. No strong directional signal. Position management territory, not aggressive sizing in either direction.
55 to 75 Caution: Mid-late cycle. Valuation extending, sentiment warming. Defensive positioning starts here.
75 to 90 Distribution: Late cycle. Multiple tiers flashing extension. Profit-taking territory historically.
90 to 100 Cycle Top: Historical top zone. Confluence at multi-cycle highs. Get out of leverage, raise cash. This is where every major cycle top has landed.
The model does NOT predict timing of zone transitions. It classifies the current position based on observable data. Zones can persist for months (the 2021 dual-top was in the Cycle Top zone for roughly 7 months across April to November) before resolving.
Honest limitations
Calling this out because most cycle models do not.
Position classifier, not forecaster. SMM tells you where you are. It does not tell you where you are going next, or when. Trade decisions need a separate timing framework on top.
MVRV uses a 4Y MA proxy. A working Realized Cap data feed for production has been elusive. The 4Y MA proxy is correlated 0.87 with true MVRV Z-Score historically, but it is a proxy not the real thing. Documented inline on the indicator panel.
Not financial advice. The model is an analytical tool. Position sizing, risk management, and timing of your specific trades are your responsibility.
Try it free
The live model, the historical chart, the 48-signal panel, the weight slider (for counterfactual tier weightings), and the embed widget are all free at: https://satoshimacro.com/tools/crypto/satoshimacro-model/
What is next
The SMM-BTC framework is also adapted for Ethereum at https://satoshimacro.com/tools/crypto/satoshimacro-model-eth/ with five of six tiers live. The Validator and Staking tier is pending integration with Beaconcha.in and Etherscan staking APIs. Currently calibrated 4-of-5 in-zone across ETH cycle inflections from 2018 through 2022.
For users who want the full crypto data dashboard alongside the SMM gauge, the Crypto Charts Dashboard at https://satoshimacro.com/tools/crypto/dashboard/ distills 33 of the most-watched crypto indicators into a single Monday-morning workflow. Free alternative to Glassnode Studio, Bitcoin Magazine Pro, and Bitbo Pro paid tiers.
About the author
Govind Satoshi (Govind Thanabalasingam). Former institutional trader who traded allocated capital at a Sydney proprietary trading firm. Founder of SatoshiMacro: quantitative Bitcoin cycle analysis, free crypto calculators, AU tax tools.
satoshimacro.com
The short answer: no single indicator survives all three Bitcoin cycles. The longer answer is a 48-signal confluence framework that I will walk through in this article.
If you would rather just see the live model, it is free and unlocked at the link at the end of this piece. If you want to understand the methodology before you trust the number, read on.
The problem with single-indicator cycle models
The Bitcoin retail analysis community has a habit of falling in love with whichever single indicator was last to call the cycle top. The list is long.
Mayer Multiple alone: Bitcoin's price-to-200-day-MA ratio crossing 2.4 historically marked cycle tops. It worked beautifully in 2013 and 2017. It crossed 2.4 again in early 2019 during the dead-cat bounce and the local "cycle top" call was a complete miss.
Pi Cycle Top alone: The 111-day-MA over 350-day-MA-times-2 crossover marked the 2013-04 top, the 2013-12 top, the 2017-12 top, and the 2021-04 top (early in the cycle second leg). It then missed the actual 2021-11 cycle high. It also flashed crosses during deep bull-cycle pullbacks where it was not a top at all.
Hash Ribbons alone: The 30-day over 60-day hashrate moving-average crossover marked the 2018-12 bottom and 2020-03 bottom. The 2022-06 false-positive cross during the LUNA collapse came nowhere near the actual cycle bottom, which arrived 5 months later in 2022-11.
MVRV Z-Score alone: Excellent at marking cycle bottoms when the score went negative. Less reliable at cycle tops, where the threshold has drifted lower each cycle (8+ in 2013, 7+ in 2017, around 5 in 2021).
The pattern across all of these: each indicator captures one dimension of cycle position such as valuation, miner stress, or on-chain profitability. But Bitcoin cycles are driven by the simultaneous alignment of multiple dimensions. A model that watches only one dimension misses the other five.
The institutional risk-framework approach
In institutional trading you do not build a position based on one signal. You build a multi-factor risk model where each factor captures a different dimension of the trade, you weight the factors by historical reliability, you backtest the composite against known historical events, and you ship the model with explicit calibration anchors so anyone can audit whether you are cherry-picking.
That is exactly what the SatoshiMacro Model is, applied to the question of Bitcoin cycle position.
The six tiers
Six weighted tiers, chosen because each captures a meaningfully different dimension of cycle behavior. Weights reflect the historical reliability of each dimension at calling cycle inflections, not arbitrary preference.
Tier 1: Cycle Timing and Mass Psychology (30% weight). The structural foundation. Captures where Bitcoin sits in its 4-year halving cycle and its long-term power-law trajectory. Indicators include months since the most recent halving, position relative to power-law regression, and quarterly return percentile. This tier weights highest because halving cycles have been the most reliable single structural anchor for the last decade.
Tier 2: Valuation (25% weight). The traditional cycle indicators that the Bitcoin analysis community already watches. Mayer Multiple, MVRV Z-Score, Pi Cycle Top, NUPL (Net Unrealized Profit and Loss), Pi Cycle Bottom, LTH supply percentage inverse. None of these alone is reliable. Together they triangulate valuation extremes.
Tier 3: Sentiment (20% weight). What the market is feeling, expressed through measurable proxies. Fear and Greed Index, BTC funding rates, BTC open interest, Coinbase premium, Deribit DVOL implied vol, Bybit-Binance basis (venue spread), options 25-delta skew. Sentiment captures the "everyone is bullish at the top" reflex.
Tier 4: Rotation (10% weight). The capital rotation pattern across cycles. BTC dominance percentile, altcoin season index, alt rotation timing. Late-cycle BTC dominance typically drops as capital rotates into alts. Early-cycle dominance rises as BTC leads recovery.
Tier 5: Miner (10% weight). Miner stress and capitulation signals. Puell Multiple, Hash Ribbons crossover state, hashrate as percentage of peak, difficulty adjustment direction. Miners are forced sellers under stress and capitulation marks bottoms. Miner profitability spikes mark tops.
Tier 6: Macro (5% weight). The traditional risk-on and risk-off macro backdrop. DXY (US dollar index), M2 money supply, yield curve, VIX, S&P 500, NASDAQ 100, gold (inverse). Bitcoin is increasingly a risk-asset. Macro liquidity matters more each cycle.
Weights total 100% across all tiers. The composite score is a weighted average of the six tier scores, each on a 0-100 percentile-rank basis.
Calibration: 7-of-7 in-zone cycle calls
Here is the proof. SMM readings at every confirmed Bitcoin cycle inflection across the last three cycles.
2013-12 cycle top: SMM 91.7, Cycle Top zone (correct).2015-01 cycle bottom: SMM 27.6, Accumulation zone (correct).2017-12 cycle top: SMM 97.8, Cycle Top zone (correct).2018-12 cycle bottom: SMM 29.7, Accumulation zone (correct).2021-04 cycle top first leg: SMM 92.8, Cycle Top zone (correct).2021-11 cycle top second leg: SMM 87.5, Cycle Top zone (correct).2022-11 cycle bottom: SMM 24.2, Accumulation zone (correct).
7 of 7 in-zone. No single existing cycle model on the public internet matches this across all three completed cycles plus the 2021 dual-top.
The calibration curve
A note on transparency. The raw weighted composite of 48 signals naturally caps at around 64-78 even at historical cycle tops, because diversifying signals (sentiment, macro, rotation) do not all peak simultaneously with cycle-position valuation. The weighted average gets diluted.
To fix this without losing the diversification benefit, the SMM applies a piecewise calibration curve that stretches the upper half of the 0-100 scale so historical tops register in the Cycle Top zone (85-100). The curve is:
Identity below raw 40 (preserves bottoms with no distortion to Accumulation reads)1.5x slope across raw 40-55 (gentle stretch into Neutral) 2.5x slope across raw 55-65 (steeper stretch into Caution) 1.25x slope across raw 65-75 (taper into Distribution)Clamp at 75+
Both the raw composite and the calibrated SMM are emitted on every series point, so anyone can re-derive the composite and audit the calibration.
Why AUD-native?
The entire SatoshiMacro data architecture is denominated in AUD. The primary source is CryptoCompare BTC/AUD trading pair, aggregated from Australian venues. USD prices are derived at display time by multiplying AUD by the daily AUDUSD spot rate.
This is a deliberate strategic choice. Australian investors get a model built natively for their currency without losing global comparability. The trade-off is a 1-2% spread on extreme-volatility days where BTC/AUD venues diverge slightly from BTC/USD venues, but this reflects real intraday venue and timing differences, not data integrity issues. A USD/AUD toggle on the gauge lets any user switch display currency in a single click.
How to read the gauge
Five zones on the 0-100 scale.
0 to 30 Accumulation: Historical bottom zone. Maximum pessimism, capitulation signals firing across miner and on-chain tiers. Highest historical risk-adjusted accumulation reward.
30 to 55 Neutral: Mid-cycle. No strong directional signal. Position management territory, not aggressive sizing in either direction.
55 to 75 Caution: Mid-late cycle. Valuation extending, sentiment warming. Defensive positioning starts here.
75 to 90 Distribution: Late cycle. Multiple tiers flashing extension. Profit-taking territory historically.
90 to 100 Cycle Top: Historical top zone. Confluence at multi-cycle highs. Get out of leverage, raise cash. This is where every major cycle top has landed.
The model does NOT predict timing of zone transitions. It classifies the current position based on observable data. Zones can persist for months (the 2021 dual-top was in the Cycle Top zone for roughly 7 months across April to November) before resolving.
Honest limitations
Calling this out because most cycle models do not.
Position classifier, not forecaster. SMM tells you where you are. It does not tell you where you are going next, or when. Trade decisions need a separate timing framework on top.
MVRV uses a 4Y MA proxy. A working Realized Cap data feed for production has been elusive. The 4Y MA proxy is correlated 0.87 with true MVRV Z-Score historically, but it is a proxy not the real thing. Documented inline on the indicator panel.
Not financial advice. The model is an analytical tool. Position sizing, risk management, and timing of your specific trades are your responsibility.
Try it free
The live model, the historical chart, the 48-signal panel, the weight slider (for counterfactual tier weightings), and the embed widget are all free at: https://satoshimacro.com/tools/crypto/satoshimacro-model/
What is next
The SMM-BTC framework is also adapted for Ethereum at https://satoshimacro.com/tools/crypto/satoshimacro-model-eth/ with five of six tiers live. The Validator and Staking tier is pending integration with Beaconcha.in and Etherscan staking APIs. Currently calibrated 4-of-5 in-zone across ETH cycle inflections from 2018 through 2022.
For users who want the full crypto data dashboard alongside the SMM gauge, the Crypto Charts Dashboard at https://satoshimacro.com/tools/crypto/dashboard/ distills 33 of the most-watched crypto indicators into a single Monday-morning workflow. Free alternative to Glassnode Studio, Bitcoin Magazine Pro, and Bitbo Pro paid tiers.
About the author
Govind Satoshi (Govind Thanabalasingam). Former institutional trader who traded allocated capital at a Sydney proprietary trading firm. Founder of SatoshiMacro: quantitative Bitcoin cycle analysis, free crypto calculators, AU tax tools.
satoshimacro.com
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$ETH | Introducing SMM-ETH: A Quantitative Ethereum Cycle Model
A quantitative Ethereum cycle confluence model. 23 signals across 6 weighted tiers (5 of 6 live; Tier 2 Validator/Staking pending), distilled into a single 0-100 cycle position score.
The 6 tiers:
- Cycle Timing & Mass Psychology (30%): post-merge ETH cycle position, ETH-fit power law deviation
- Valuation (25%): ETH-specific power-law regression, Mayer Multiple, NUPL
- Sentiment (20%): Fear & Greed, broad-crypto risk-on proxies, Coinbase premium
- Rotation (10%): ETH/BTC ratio percentile, BTC dominance inverse, altseason index
- Miner / Validator (10%): PENDING - Beaconcha.in + Etherscan staking API integration in progress
- Macro (5%): DXY, M2, yield curve, VIX (shared with SMM-BTC)
ETH-specific differentiator: the Rotation tier is the model anchor. ETH/BTC ratio percentile captures the late-ETH-cycle dynamic that pure BTC models miss.
Lookahead-free expanding-window percentile rank. USD/AUD currency toggle. Calibrated 4-of-5 in-zone across ETH cycle inflections from 2018 through 2022.
Built by a former institutional trader. Companion to SMM-BTC.
100% free. No paywall, no email gate.
Full methodology + interactive gauge:
https://satoshimacro.com/tools/crypto/satoshimacro-model-eth/
#Ethereum #ETH #CycleAnalysis #SatoshiMacro #SMMETH
$ETH | Introducing SMM-ETH: A Quantitative Ethereum Cycle Model
A quantitative Ethereum cycle confluence model. 23 signals across 6 weighted tiers (5 of 6 live; Tier 2 Validator/Staking pending), distilled into a single 0-100 cycle position score.
The 6 tiers:
- Cycle Timing & Mass Psychology (30%): post-merge ETH cycle position, ETH-fit power law deviation
- Valuation (25%): ETH-specific power-law regression, Mayer Multiple, NUPL
- Sentiment (20%): Fear & Greed, broad-crypto risk-on proxies, Coinbase premium
- Rotation (10%): ETH/BTC ratio percentile, BTC dominance inverse, altseason index
- Miner / Validator (10%): PENDING - Beaconcha.in + Etherscan staking API integration in progress
- Macro (5%): DXY, M2, yield curve, VIX (shared with SMM-BTC)
ETH-specific differentiator: the Rotation tier is the model anchor. ETH/BTC ratio percentile captures the late-ETH-cycle dynamic that pure BTC models miss.
Lookahead-free expanding-window percentile rank. USD/AUD currency toggle. Calibrated 4-of-5 in-zone across ETH cycle inflections from 2018 through 2022.
Built by a former institutional trader. Companion to SMM-BTC.
100% free. No paywall, no email gate.
Full methodology + interactive gauge:
https://satoshimacro.com/tools/crypto/satoshimacro-model-eth/
#Ethereum #ETH #CycleAnalysis #SatoshiMacro #SMMETH
A quantitative Ethereum cycle confluence model. 23 signals across 6 weighted tiers (5 of 6 live; Tier 2 Validator/Staking pending), distilled into a single 0-100 cycle position score.
The 6 tiers:
- Cycle Timing & Mass Psychology (30%): post-merge ETH cycle position, ETH-fit power law deviation
- Valuation (25%): ETH-specific power-law regression, Mayer Multiple, NUPL
- Sentiment (20%): Fear & Greed, broad-crypto risk-on proxies, Coinbase premium
- Rotation (10%): ETH/BTC ratio percentile, BTC dominance inverse, altseason index
- Miner / Validator (10%): PENDING - Beaconcha.in + Etherscan staking API integration in progress
- Macro (5%): DXY, M2, yield curve, VIX (shared with SMM-BTC)
ETH-specific differentiator: the Rotation tier is the model anchor. ETH/BTC ratio percentile captures the late-ETH-cycle dynamic that pure BTC models miss.
Lookahead-free expanding-window percentile rank. USD/AUD currency toggle. Calibrated 4-of-5 in-zone across ETH cycle inflections from 2018 through 2022.
Built by a former institutional trader. Companion to SMM-BTC.
100% free. No paywall, no email gate.
Full methodology + interactive gauge:
https://satoshimacro.com/tools/crypto/satoshimacro-model-eth/
#Ethereum #ETH #CycleAnalysis #SatoshiMacro #SMMETH
1
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·
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$BTC | Introducing the SatoshiMacro Model (SMM)
A quantitative Bitcoin cycle confluence model. 48 signals across 6 weighted tiers, distilled into a single 0-100 cycle position score.
The 6 tiers:
- Cycle Timing & Mass Psychology (30%): halving cycle position, power law deviation
- Valuation (25%): Mayer Multiple, MVRV Z-Score, Pi Cycle Top, NUPL
- Sentiment (20%): Fear & Greed, funding rates, open interest, Coinbase premium
- Rotation (10%): BTC dominance, altseason index
- Miner (10%): Puell Multiple, hash ribbons, hashrate vs peak
- Macro (5%): DXY, M2, yield curve, VIX
Lookahead-free expanding-window percentile rank. USD/AUD currency toggle. Calibrated 7-of-7 in-zone across BTC cycle inflections from 2013 through 2022.
Built by a former institutional trader who traded allocated capital at a Sydney prop firm.
100% free. No paywall, no email gate.
Full methodology + interactive gauge + 48-signal panel:
https://satoshimacro.com/tools/crypto/satoshimacro-model/
#Bitcoin #CycleAnalysis #OnChain #SatoshiMacro #SMM
$BTC | Introducing the SatoshiMacro Model (SMM)
A quantitative Bitcoin cycle confluence model. 48 signals across 6 weighted tiers, distilled into a single 0-100 cycle position score.
The 6 tiers:
- Cycle Timing & Mass Psychology (30%): halving cycle position, power law deviation
- Valuation (25%): Mayer Multiple, MVRV Z-Score, Pi Cycle Top, NUPL
- Sentiment (20%): Fear & Greed, funding rates, open interest, Coinbase premium
- Rotation (10%): BTC dominance, altseason index
- Miner (10%): Puell Multiple, hash ribbons, hashrate vs peak
- Macro (5%): DXY, M2, yield curve, VIX
Lookahead-free expanding-window percentile rank. USD/AUD currency toggle. Calibrated 7-of-7 in-zone across BTC cycle inflections from 2013 through 2022.
Built by a former institutional trader who traded allocated capital at a Sydney prop firm.
100% free. No paywall, no email gate.
Full methodology + interactive gauge + 48-signal panel:
https://satoshimacro.com/tools/crypto/satoshimacro-model/
#Bitcoin #CycleAnalysis #OnChain #SatoshiMacro #SMM
A quantitative Bitcoin cycle confluence model. 48 signals across 6 weighted tiers, distilled into a single 0-100 cycle position score.
The 6 tiers:
- Cycle Timing & Mass Psychology (30%): halving cycle position, power law deviation
- Valuation (25%): Mayer Multiple, MVRV Z-Score, Pi Cycle Top, NUPL
- Sentiment (20%): Fear & Greed, funding rates, open interest, Coinbase premium
- Rotation (10%): BTC dominance, altseason index
- Miner (10%): Puell Multiple, hash ribbons, hashrate vs peak
- Macro (5%): DXY, M2, yield curve, VIX
Lookahead-free expanding-window percentile rank. USD/AUD currency toggle. Calibrated 7-of-7 in-zone across BTC cycle inflections from 2013 through 2022.
Built by a former institutional trader who traded allocated capital at a Sydney prop firm.
100% free. No paywall, no email gate.
Full methodology + interactive gauge + 48-signal panel:
https://satoshimacro.com/tools/crypto/satoshimacro-model/
#Bitcoin #CycleAnalysis #OnChain #SatoshiMacro #SMM
1
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EthereumHegotaUpgradePrivacyTransfers
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Everyone is focused on AI becoming more powerful, but very few people are paying attention to what comes with it: surveillance.
As governments, big tech, and AI systems collect more data, financial privacy could become one of the rarest and most valuable things online.
Bitcoin started the movement by giving people ownership over their money without relying on traditional systems. But as the industry evolves, the conversation is beginning to shift from just financial ownership to financial privacy.
That’s why Arthur Hayes saying privacy with money will be “super needed” stands out to me.
It’s not just a bullish call on $ZEC , it’s a bet on where the world is heading.
In a future where every transaction, wallet interaction, and digital footprint can be tracked, privacy may stop being optional and start becoming essential.
Most people are still chasing hype and short-term narratives, while Hayes seems to be positioning for a future where financial freedom itself becomes a premium.
#EthereumHegotaUpgradePrivacyTransfers
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