SatoshiMacro

The most expensive mistake I made in 2018 was running a single-indicator Bitcoin cycle framework. The indicator was MVRV Z-Score on the original Awe and Wonder formula. The reading was clear in late 2017 at Z above 11. The exit thesis was correct. What broke was 2018: holding through a -84 percent drawdown to USD 3,200 because the same indicator never re-printed a Z reading that matched a textbook cycle-bottom anchor. The framework worked at the top and failed at the bottom of the same cycle.
Single-indicator frameworks have a worse track record than the literature suggests. Survivorship bias is real - the Twitter accounts you see citing one magic indicator are the ones whose magic indicator happened to fire on the most recent cycle. The 2021 cycle proved this brutally: it ran as a double-top structure with a 5-month gap between the April peak and the November echo peak, and that structure broke the signal cleanly across every moving-average-based cycle indicator in continuous use. The piece below walks through the six BTC valuation signals I now treat as a confluence panel rather than as standalone triggers, the structural blind spots each one carries, and the multi-tier weighting framework that catches what any individual signal misses.
## Pi Cycle Top
The simplest classical cycle-top indicator. Signal fires when the 111-Day Moving Average crosses above the 350-Day Moving Average multiplied by 2. Two moving averages, one multiplier, one crossover. Pure price-history math, no on-chain data needed.
Historical fires: 2013-04 (first 2013 peak, fired ~17 days before local peak), 2017-12-17 (fired 1 day before the cycle top), 2021-04-12 (fired 4 days before the April peak). Extraordinarily precise when it does fire - the window has been zero to four days.
The 2021-11 miss: did NOT fire at the November echo peak even though spot made a fresh all-time high. The double-top structure with a 5-month gap allowed the 350DMA to catch up between peaks, suppressing the crossover. Documented blind spot that will repeat on any future double-top cycle structure.
Limitation: binary fire/no-fire mechanic. Cannot express partial conviction. Single Pi Cycle fire by itself is not the level of confidence at which I take cycle-exit action on real capital.
## Mayer Multiple
BTC price divided by 200-day moving average. One ratio, one input. Trace Mayer published the formula in 2013-2014.
Threshold bands per SatoshiMacro implementation: above 2.4 historically marks cycle euphoria, below 0.6 marks cycle accumulation. Documented ATH 2.42 (2017-11), documented ATL 0.52 (2022-06 Luna collapse).
What Mayer does well: cleanly continuous output. Supports graduated position-sizing logic. Replicable with five lines of Python. No on-chain data dependencies.
What Mayer cannot do: distinguish between stretched late-cycle and early-mania still going. Mayer at 2.6 in October 2017 looked the same as Mayer at 2.6 in February 2021 - both were 8 to 12 weeks pre-top. Reading is ambiguous on directional timing. Also compresses on echo-top structures where the 200DMA catches up between peaks - same 2021-11 blind spot as Pi Cycle.
## MVRV Z-Score
Awe and Wonder's 2018 formula: Z equals (MarketCap minus RealizedCap) divided by stddev of MarketCap on an expanding window. Measures how stretched aggregate cost basis is versus current market value.
True Glassnode/CoinMetrics implementation anchors: 2013-12 Z approximately 9.3, 2017-12 Z approximately 11.5, 2021-04 Z approximately 6.3, 2021-11 Z approximately 2.9 (documented miss), 2018-12 Z approximately -0.3, 2022-11 Z approximately 0.1.
The 2021-11 miss is structural and important. Coins moved during the May-July 2021 crash, partially catching up the RealizedCap baseline. By November the Z-Score had compressed even though spot made a fresh ATH. Same root cause as Pi Cycle and Mayer's 2021-11 misses - moving-average-based indicators do not handle double-top cycles cleanly.
## Power Law
Giovanni Santostasi's 2018 work on Bitcoin's log-time / log-price regression. BTC price-versus-time-since-genesis fits a power-law curve with cycle peaks and troughs printing as statistical deviations from the fair-value line.
SatoshiMacro implementation uses sigma units (standard deviations from the regression). Historical anchors: 2017-12 plus 2.50 sigma, 2021-03 plus 1.94 sigma, 2015-09 minus 1.71 sigma, 2022-12 minus 1.45 sigma. Pattern: cycle peaks have printed progressively smaller sigma deviations each cycle, consistent with the diminishing-cycle-amplitude thesis.
Limitation: long-horizon position-classifier, not tactical-timing forecaster. Most useful at the extremes (below minus 1.0 sigma equals aggressive sizing in, above plus 1.5 sigma equals aggressive sizing out). Less useful in the mid-band where it currently sits.
## Rainbow Chart
Logarithmic regression with nine colour-banded zones from Maximum Bubble (red, top) to Basically a Fire Sale (deep blue, bottom). The most-shared cycle visual on crypto Twitter.
What Rainbow does: visual quick-read on where price sits versus the long-term log-regression base. HODL band historically covers approximately 35-40 percent of cycle time. The two upper bands (FOMO + Maximum Bubble) cover roughly 8-12 percent of days, clustered at cycle tops.
What Rainbow does not do: forecast anything. The bands are a visual, not a probabilistic model. Useful as a sentiment-anchor when crypto Twitter is screaming "Maximum Bubble" but the chart shows HODL - that mismatch is the alpha signal.
## Bitcoin Risk Metric
Benjamin Cowen's 0-to-1 normalised cycle-position scale, in continuous use since 2018. Combines log-price deviation from a long-term trendline with a smoothed momentum overlay.
Historical anchors per SatoshiMacro implementation: 2017-12 Risk at 0.90, 2021-03 Risk at 0.78, 2015-09 Risk at 0.00, 2022-12 Risk at 0.06. Pattern: peaks above 0.78, bottoms below 0.10. Middle 0.10 to 0.78 band is mid-cycle.
Where Risk Metric differs from the binary indicators: continuous and graduated all the way through. Natively suited to position-sizing functions like "Risk above 0.80 equals sale-only stance; Risk 0.40 to 0.60 equals 40 percent position; Risk below 0.20 equals 100 percent sizing-in tranches".
## The six-tier confluence framework
No single one of the above six valuation signals survived the 2021-11 echo top cleanly. Pi Cycle did not fire. Mayer compressed below its prior cycle anchors. MVRV printed only 2.9 versus 11.5 in 2017. Power Law printed plus 1.0 sigma versus plus 2.5 in 2017. Rainbow showed FOMO band but not Maximum Bubble. Risk Metric at 0.78 (cycle-top territory but lower than the prior cycle's 0.91).
The lesson: structural blind spots are structural. Any cycle with double-top potential will produce these same compressions across all six. The right response is not to find a seventh magic indicator. The right response is to weight a basket of valuation signals as one tier, alongside five other dimensions (Cycle Timing, Sentiment, Rotation, Miner Economics, Macro) in a confluence model.
The SatoshiMacro Model wraps all six valuation signals into Tier 1 (25 percent weight) and combines them with Tier 0 (Cycle Timing, 30 percent), Tier 2 (Miner Economics, 10 percent), Tier 3 (Sentiment, 20 percent), Tier 4 (Rotation, 10 percent), and Tier 5 (Macro, 5 percent). The composite 0-100 reading classifies cycle position (Accumulation / Mid-cycle / Caution / Distribution / Cycle Top) and the historical calibration produces 7-of-7 in-zone cycle calls across all four documented BTC cycle inflections.
## For Australian residents specifically
The single highest-EV improvement I made to my cycle-exit framework after the 2018 mistake was wrapping the tactical signal in 12-month CGT-discount-eligibility logic. The 50 percent CGT discount at the 47 percent top marginal rate drops effective CGT from 47 percent to 23.5 percent on parcels held longer than 12 months. The asymmetry exceeds the tactical alpha from selling 1 to 8 weeks early on most realistic AU-resident scenarios.
Practical rule: a parcel at month 10 of its 12-month hold sitting at MVRV Z elevated, Pi Cycle fired, Risk Metric above 0.80, and three other tiers confirming distribution is almost always better held for the 2-month eligibility crossing than sold immediately. The tax-discount asymmetry is the dominant variable, not the tactical-timing alpha.
## Full model and calibration receipts
The complete six-tier confluence model with live composite reading, all 48 signals across the six tiers, and the 7-of-7 BTC plus 4-of-5 ETH historical calibration:
https://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 Article). This Article is editorial, not financial advice.
#SatoshiMacro #BitcoinCycle #OnChain #Bitcoin

$BTC | Termenul limită pentru EOFY 2026 în Australia se încheie pe 30 iunie. Asta e la 33 de zile de azi. Pentru deținătorii de crypto rezidenți în Australia care se află pe pierderi nerealizate, acesta este fereastra în care matematica fiscală se schimbă semnificativ prin acțiuni deliberate, nu prin direcția pieței. O să trec prin cadrul Part IVA, alegerea metodei cost-base și păstrarea înregistrărilor de carry-forward pe care 90% din traderii retail le înțeleg greșit.
## Mecanismul
Dacă deții un activ crypto cu o pierdere de capital, poți cristaliza acea pierdere vânzându-l în perioada financiară 2025-2026. Pierderea de capital realizată compensează câștigurile de capital în aceeași perioadă de venit. Orice sold neutilizat se reporteză indefinit împotriva viitoarelor câștiguri de capital.

$BTC | Legea Puterii Bitcoin este cel mai vechi instrument de evaluare al stivei de confluență a ciclicilor care încă funcționează. Giovanni Santostasi și Harold Christopher Burger au popularizat formularea în cercetările din 2018 încoace: ia istoria prețului Bitcoin, plotează-o în funcție de timp pe un ax log-log, aplică o regresie liniară, și obții o pantă de aproximativ 5.7. Peste media regresiei cu o deviație standard marchează teritoriul vârfului ciclului. Sub 0.5 deviații standard marchează teritoriul de acumulare.
Eu îl rulez în cadrul Evaluării Tier 1 cu o pondere de 25% în Modelul SatoshiMacro, alături de MVRV Z-Score și Mayer Multiple. Iată ce a prins modelul la fiecare inflexiune documentată a ciclului BTC din 2013 încoace, și unde metodologia încetează să mai fie sustenabilă.

Pentru rezidenții australieni care dețin crypto ca o alocare pe termen lung, asimetria fiscală între structurile pe nume personal și SMSF este cea mai mare decizie după impozitare în portofoliu. Diferența este de 13.5 puncte procentuale la fiecare câștig realizat pe termen lung, la rata marginală de 47%. Aproape nimeni nu calculează corect înainte de a se configura. Paragraful de mai jos trece prin cadrul cu șase variabile pe care îl folosesc efectiv pe capitalul personal, cele trei studii de caz pe niveluri de bilanț care determină dacă crypto în SMSF este viabil și limitările oneste pe care industria de consultanță SMSF tinde să le subestimeze în prezentări.