Grayscale names five DeFi tokens with revenue models

Grayscale Research identified five DeFi tokens-Hyperliquid (HYPE), Aave (AAVE), Uniswap (UNI), Sky (SKY) and Maple (MAPLE)—in a report published June 16, citing recurring fee revenue and cash-flow metrics as the basis for their selection.

The report notes DeFi protocols generated nearly $25 billion in cumulative fees from real users since 2023, with rising on-chain fee revenue across exchanges, lending, staking and derivatives.

Grayscale places tokens on a spectrum where bitcoin behaves like a commodity and protocols with steady income resemble cash-flow businesses. The firm adds that revenue alone does not determine token value; how earnings are returned to holders affects value accrual.

The report lists mechanisms that return earnings to holders-token burns, buybacks, rebates and staking-and highlights protocols that channel most fees to token holders.

Hyperliquid routes trading fees into buying and burning HYPE, a model the report links to HYPE entering the top 10 by market capitalization. HYPE trades near $72.

Uniswap distributes fee revenue back to UNI holders; the report notes recent price movement tied to those distributions and records UNI trading around $3.30.

Aave is identified as the largest DeFi lender. Grayscale estimates an intrinsic value for AAVE near $75 and characterizes the token as undervalued against its lending franchise.

Sky is cited for an on-chain collateral-backed stablecoin that the report says is finding product-market fit; SKY trades near $0.06. Maple is flagged for institutional lending, where strong risk-adjusted returns and disciplined underwriting are listed as drivers of token value for MAPLE.

The report reads: “crypto is repricing from narrative to fundamentals. Protocols with real revenue, disciplined capital allocation, and transparent token economics are outperforming.”

Grayscale frames the current market phase as one in which investors can assess many tokens using revenue, cash flow and payout policy to compare relative value across protocols.