Source publication: November 6, 2026, at 21:49:42 (UTC+8). Based on analysis by Marc Arjoon, CFA (@marcarjoon), translated and compiled by TechFlow. All observations below refer to the source’s historical analysis, not live market conditions.
The familiar Layer 1 investment narrative links more network usage to greater token value. More users generate more transactions, transactions generate fees, and those fees supposedly provide a valuation anchor.
Marc Arjoon’s analysis tests that story against several alternatives. His central finding: Bitcoin exposure dominates shorter-term price movements, while capital held within an ecosystem appears more closely associated with valuation than transaction activity alone. That supports an interpretation of Layer 1 tokens as monetary assets competing for liquidity, rather than businesses valued primarily on fee cash flows.
The evidence is not a complete causal model, however, and several conventional valuation ratios failed the tests that would make them reliable pricing tools.
Bitcoin sets the short-term backdrop
Arjoon regressed monthly logarithmic changes in Layer 1 market capitalizations against Bitcoin, then added four onchain time series: protocol revenue, or REV, measured in native tokens; active addresses; decentralized exchange trading volume; and stablecoin supply.
His conclusion was that Bitcoin beta remained the dominant influence over trading-relevant horizons. In other words, a chain’s operating metrics did not displace its sensitivity to the broader Bitcoin-led market.
Measurement also matters. When a native token appreciates, fees paid in that token rise in dollar terms without necessarily indicating greater underlying activity. Dollar-denominated total value locked, or TVL, can have a similar problem when a substantial share consists of the network’s own token.
Ethereum and Solana tell different revenue stories
Ethereum provided the clearest example of revenue and valuation moving apart. Between the week of the Dencun upgrade and August 2025, its trailing 12-month REV fell 60%, while its market capitalization rose.
Arjoon interpreted this as a consequence of policy design rather than a collapse in demand: introducing blob fees and raising gas limits were intended to make Layer 1 blockspace cheaper. He attributed Ethereum’s 2025 price rebound primarily to demand from spot ETFs and publicly listed companies’ treasury allocations.
Solana showed a different pattern. From January 2023, its trailing 12-month protocol revenue and market capitalization both increased approximately 15-fold, peaked in the same week, and subsequently declined together.
The supplied source omits the dollar amounts for Ethereum’s revenue and market-cap comparison, as well as Solana’s peak and subsequent levels. Those figures cannot be reproduced reliably.
More addresses do not translate neatly into more value
Active addresses and market capitalization tended to drift in the same direction over a full cycle, particularly for Solana and TRON. At a weekly frequency, however, the relationship weakened considerably.
The source illustrated that divergence with comparisons beginning in January 2022:
- Ethereum’s active addresses increased 26%, while its market capitalization fell 34%.
- Solana’s active addresses increased 17-fold, while its market capitalization rose only 17%.
DEX volume tracked market capitalization more closely than address counts, especially on Solana, where both rose from their 2023 lows and peaked together. But dollar-denominated trading volume partly incorporates token-price movements, making some of that relationship mechanical. Arjoon suggested that a growing share of tokenized assets in trading volume could provide a further test of whether the relationship holds.
The analysis also challenged a simple application of Metcalfe’s law, which proposes that network value scales with the square of its user count. Fitting market capitalization against active addresses produced elasticities of 0.56 for Ethereum and 0.62 for both Solana and BNB—closer to square-root scaling than square scaling.
Longer histories exposed another constraint: address growth slows as networks mature. The source reported that Bitcoin’s active addresses had grown by 1.3 times since January 2016, compared with a 252-fold increase in market capitalization. For Ethereum, it reported address growth of 2.6 times and market-cap growth of 4.5 times since February 2018, with address changes explaining 84% of market-cap variation in that fit. Solana’s shorter history broadly followed a similar trajectory.
Valuation multiples mostly failed the reliability test
Arjoon examined six approaches:
- A Metcalfe multiple.
- An Odlyzko multiple, using users multiplied by the natural logarithm of users.
- Network value to transactions, based on stablecoin transfer volume.
- Market capitalization relative to DEX volume.
- Market capitalization relative to protocol revenue, or Mcap/REV.
- Market capitalization relative to stablecoin supply.
For a multiple to be useful, he argued, it should reliably revert toward a mean and help predict subsequent returns when valuations are low.
None consistently demonstrated mean reversion. Mcap/REV was the only measure whose low valuation percentiles predicted positive returns over the following 13 weeks on more than one chain—Ethereum and TRON. That is a narrower result than establishing a universal Layer 1 valuation rule.
Capital depth offers a different explanation
Ethereum’s position within the source’s major-chain comparison was much larger in capital measures than in activity measures:
| Metric | Ethereum’s share |
|---|---|
| Market capitalization | 59% |
| Stablecoin supply | 53% |
| Stablecoin transfer volume | 60% |
| DeFi TVL | 70% |
| Tokenized real-world assets | 75% |
| Lending-protocol TVL | 76% |
| Active addresses | 5% |
| Onchain transaction count | Approximately 1% |
Across chains, market-cap rankings aligned most closely with TVL rankings, with a Spearman rank correlation of 0.87. The correlation was 0.63 for stablecoin supply, compared with 0.45 for active addresses and 0.17 for transaction counts.
The source also noted that ETH itself no longer represented an overwhelming majority of Ethereum’s TVL, reducing the extent to which that measure simply reflected ETH’s own price.
These are cross-sectional rankings, not proof of causation. Nevertheless, Arjoon reported that they aligned with the time-series findings, including when the analysis was extended to more than 40 chains.
Holder structure adds another distinction
The analysis found that no Layer 1 matched Bitcoin’s base of long-term unmoved holdings. Even including native staking, only 4% of Solana’s supply and 10% of Ethereum’s supply had remained unmoved for more than three years, compared with 42% for Bitcoin.
The top 100 non-staking Solana addresses controlled 49% of liquid SOL, versus reported top-100 address shares of 27% for Ethereum and 17% for Bitcoin.
The source also counted approximately 66,000 Solana addresses, 538,000 Ethereum addresses and 3.67 million Bitcoin addresses above a specified dollar-value holding threshold. That threshold is missing from the supplied text, limiting the comparison’s usefulness. The source itself cautioned that the differences might largely reflect the assets’ different market capitalizations.
Meanwhile, spot ETFs and publicly listed company treasuries held 11.9% of Ethereum’s total supply, close to Bitcoin’s 12.2% and above Solana’s 7.9%, according to the analysis.
The narrative: competing for capital, not just transactions
Arjoon’s conclusion is not that network usage or revenue is irrelevant. Rather, the evidence presented does not support treating transaction counts, address growth or fee income as interchangeable valuation anchors.
Bitcoin remained the main short-term influence. Over longer valuation comparisons, TVL, stablecoin supply and the depth of capital held within an ecosystem showed stronger relationships with market value than raw interaction counts.
The resulting narrative is a competition to attract and retain capital. It remains an interpretation of the reported evidence—not a demonstrated causal law, a dependable trading model or proof that any individual Layer 1 is fairly valued.
