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SKY (formerly MakerDAO) — Revenue Streams
Sky hit a record $124M gross revenue in Q1 2026 — its strongest quarter since founding as MakerDAO in 2017. Annualized fees run at ~$412M and annualized revenue at ~$244M, powered by three streams: loan stability fees (~97% of gross), liquidation fees, and RWA collateral yields via Spark. The protocol targets $611M in full-year 2026 revenue (+81% YoY), underpinned by $6.5B+ of USDS in its savings module — the world's largest interest-bearing stablecoin. Despite record fundamentals, the SKY token has underperformed: a March 2026 governance vote redirected protocol surplus from buybacks toward building a $150M solvency reserve (currently ~$51M), compressing near-term token holder returns and creating a notable valuation gap.
Valuation: The Profitability Paradox
Sky is among DeFi's most cash-generative protocols, yet its P/F and P/S ratios reveal a persistent discount relative to its earnings power. The March 14, 2026 governance restructuring is the key driver: surplus funds now flow into a $150M solvency reserve rather than SKY token buybacks and staking rewards. Until the reserve target is hit (~$75M expected by end-Q2 2026), buyback and distribution rates will remain suppressed. This creates a temporary but real compression in token holder returns — a short-term headwind against a medium-term re-rating catalyst once the reserve is fully funded. Sky's Q1 2026 profit swing ($46M surplus vs. −$13.5M a year prior) suggests the underlying earnings engine is accelerating faster than the market is pricing.
Competitive Context — Where Sky Ranks
Among all DeFi protocols globally, Sky consistently ranks in the top 3–5 by revenue. Its moat is structural: USDS's $6.5B+ in the Sky Savings Rate module provides a sticky, yield-bearing liability base that drives stability fee demand. The Spark lending sub-protocol (sky-lending) extends the revenue base beyond pure CDPs into broader lending markets. The chart below shows Sky's revenue share against the DeFi field — note how its contribution scales disproportionately in high-rate environments.