Can public chain trading volume still be trusted? The truth behind the data in the Solana and Starknet controversy

January 15 News, Solana’s official verified account publicly criticized Starknet on the X platform, directly pointing out the severe mismatch between its on-chain activity and network valuation, and targeting the “employed trading volume” driven by incentive mechanisms. Although the statement carries obvious emotional overtones, it unexpectedly sparked a systematic discussion on the valuation methods of public chains.

In the tweet, Solana stated that Starknet’s daily active users and real transaction volume are extremely low, yet it still maintains a market cap close to 1 billion USD and a higher fully diluted valuation. Subsequent data verification showed that the relevant final valuation referenced an old snapshot from 2024, and Starknet’s current fully diluted valuation is about 900 million USD, but the controversy has not disappeared because of this.

The core issue is whether the valuation of blockchain networks truly reflects actual usage. Valuation itself is not equivalent to on-chain activity, but in the current cycle, some networks’ pricing methods seem to inherently bind trading volume to real demand.

The market is gradually realizing that some key indicators are easily exaggerated, especially nominal perpetual contract trading volume and active addresses. Perpetual contract trading volume is usually calculated based on nominal size; even if traders only put in a small margin, the total position size is still counted, which can be rapidly amplified under zero-fee or reward point mechanisms.

In contrast, REV (Real Economic Value) is regarded as a more meaningful indicator. This metric combines on-chain transaction fees with MEV tips paid by users to prioritize execution, better reflecting whether users are willing to pay for block space. High trading volume but low REV often indicates that activity is mainly driven by incentives rather than natural economic activity.

Taking data from mid-January 2026 as an example, Solana recorded over 150 billion USD in total trading volume within 30 days, with a fully diluted valuation to trading volume ratio of about 0.59. Trading activity is distributed across multiple decentralized application scenarios, and on-chain fees have remained high for a long time, indicating a relatively dispersed demand structure.

By comparison, some Layer 2 networks’ trading volumes are highly concentrated in a single incentive protocol. For example, Arbitrum’s nominal trading volume is over half from a single perpetual contract application, which is still in the reward phase. Once airdrops end, there is considerable uncertainty about whether the related trading volume can be sustained.

Starknet’s situation is even more extreme. Its nominal perpetual trading volume is mainly concentrated in a single protocol, while the 30-day on-chain fees are only about 180,000 USD, forming a stark contrast with hundreds of billions of USD in nominal trading scale. This indicates that trading activity is more driven by incentive arbitrage rather than genuine user demand.

It should be emphasized that a lower FDV-to-trading volume ratio does not necessarily mean undervaluation, but rather a form of sustainability testing. Either trading volume eventually converts into stable revenue, pushing up valuation; or it quickly falls back after incentives fade, exposing structural bubbles.

From a data perspective, trading volume concentration is becoming an important forward-looking signal. When more than half of a chain’s activity depends on a single protocol or incentive scheme, its lifecycle is often highly tied to that mechanism. Once the incentives expire, the indicators may shrink significantly in a short period.

Although Solana’s recent statement is considered somewhat performative and some data references are not rigorous, the direction of the discussion it has sparked is of practical significance. In the 2026 crypto market, DEX trading volume, perpetual contract data, REV metrics, and trading concentration are gradually becoming key dimensions to distinguish between “genuine demand public chains” and “incentive-driven traffic.”