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In today’s newsletter, Markus Thielen from 10x Research explains why a cycle-smart strategy outperforms traditional Dollar-Cost Averaging for bitcoin.
Then, in “Ask an Expert,” Eric Tomaszewski from Verde Capital Management, shares why advisors should look past surface-level numbers to find where real value is actually growing.
If you have two minutes, TrackInsight is benchmarking how advisors are incorporating crypto ETFs into client portfolios. Take this 2-minute survey and get early access to the results.
The same playbook that works for the S&P 500 is destroying capital in bitcoin. Understanding why changes how you allocate.
Dollar-cost averaging (DCA) is one of the most sensible strategies in traditional finance. Spread purchases over time, smooth out volatility and avoid the psychological trap of market timing. For equities and bonds, assets that consistently appreciate, it is close to optimal for most retail investors.
However, applying DCA to bitcoin is one of the most common and costly mistakes I see advisors make on clients' behalf.
Bitcoin has completed four full market cycles since 2011. Each followed roughly the same pattern: a halving event reduces the supply of new coins, adoption demand accelerates, price appreciates dramatically, leverage builds in the system, then the cycle reverses with drawdowns that have historically exceeded 70%.
The peak-to-trough drawdown for a buy-and-hold bitcoin investor across the full history is −80%. That is not a tail-risk scenario — It happened three times. The typical outcome: capitulation near the bottom, followed by missing the recovery. The long-run return looks extraordinary on a chart.
DCA smooths the path only marginally. An investor who bought steadily through the 2021–2022 cycle still experienced catastrophic mark-to-market losses during the bear phase. The strategy offers psychological comfort, not mathematical protection, because it does not reduce exposure when the regime has structurally turned negative.
The alternative to DCA is regime awareness. Bitcoin spends extended periods, typically 12 to 18 months, in identifiable bull or bear regimes, either compounding at an extraordinary rate or losing most of those gains. The key insight is that these regimes are not random. They are detectable in advance using observable data across both price behavior and the on-chain economics of the Bitcoin network.
In our research, we track ten independent signals, spanning momentum, trend and on-chain cost-basis metrics, that collectively identify the regime. The finding is straightforward: when most signals are positive, bitcoin's average monthly return has been +25%. When the majority are negative, the average is 6%[CP1], a 31-percentage-point spread.
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