When 20% of Top Tokens Aren't Really New Capital, Market Cap Rankings Become Misleading

CoinGecko is now changing how it ranks rehypothecated tokens. These are tokens that represent claims on other assets, like wrapped tokens, liquid-staked tokens, or certain DeFi LP tokens. Essentially, they are IOUs for other crypto assets.

This is an important change for the industry, but at Clarity, we have been handling these variations from day one. Our goal has always been to ensure that analytics reflect native assets, giving investors data they can trust.

Why Rehypothecated Tokens Break Naive Analytics

At first glance, rehypothecated tokens might seem harmless. Treating them like native tokens leads to misleading results:

• They can inflate market cap rankings without introducing new capital. Wrapped ETH or stETH can appear near the top of rankings even though the underlying ETH already exists.
• They clutter dashboards, making it harder to identify the largest and most impactful projects.
• They break calculations, including portfolio returns, DCA comparisons, and category market caps. Including a wrapped token in a DCA calculation can overstate historical gains.

Naive aggregation risks double-counting. For example, if both ETH and stETH are included in a portfolio, ETH's performance could be counted twice, giving a misleading picture of returns.

How Clarity Handles Variations

On Clarity, we classify rehypothecated tokens as variations. The approach is simple but powerful:

1. Mark variations
   When market data is fetched from CoinGecko, tokens that are rehypothecated are flagged as variations. Not every token is flagged; native tokens remain unmarked.
2. Filter for presentation
   Variations are stored in the database but are excluded from user-facing analytics and rankings. This ensures dashboards show accurate, uncluttered results without losing the underlying data.
3. Apply criteria
   Tokens must meet thresholds such as market cap ≥ $10M, 24-hour trading volume ≥ $1M, and at least 1 year of historical data. Variations automatically fail the display criteria, so they do not interfere with rankings or portfolio analytics.

Here is a simplified pseudocode illustrating the process:

      Fetch market data from CoinGecko
              |
              v
      For each token:
        - Is it a variation (rehypothecated)?
              |
              v
      If token meets criteria and is not a variation:
        - Include in rankings and analytics
      Else:
        - Store in database but exclude from frontend
              |
              v
      Return curated data to dashboards
        

Why This Approach Matters

Consider stETH, the liquid-staked version of ETH (Lido), or wrapped BTC (WBTC). Including these in naive market cap calculations can make ETH or BTC projects appear larger than they are. On Clarity, variations are deduplicated by underlying asset.

The aggregation works like this:

1. Identify the underlying native asset for each variation.
2. Deduplicate so each asset only contributes once to rankings, portfolio value, or DCA returns.
3. Aggregate metrics such as market cap and historical returns for the native asset only.

This prevents double-counting, ensures accurate portfolio analytics, and maintains clean market cap rankings.

Here is how naive vs curated data can differ:

Naive systems would display stETH and WBTC alongside native assets, inflating ETH and BTC exposure. Clarity ensures rankings reflect true native market size.

Accurate DCA and Portfolio Analytics

Including variations in historical performance calculations can create false impressions of returns. For example, adding stETH to a portfolio alongside ETH would exaggerate gains because price changes of the underlying asset are counted twice.

By filtering variations and deduplicating underlying assets, Clarity ensures that:

• Historical returns reflect actual performance of native assets.
• DCA vs lump sum comparisons are accurate.
• Portfolio analytics remain reliable for long-term decision-making.

This approach is especially important for investors who rely on historical data to make informed decisions in volatile markets.