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Tokenholder revenue has surged 5x since 2024, yet buyback execution remains broken.
In our latest report, we explore adaptive buyback models to address the flaws of current buyback mechanisms.
Before planning a buyback, teams should ask if they should at all. They only make sense once revenue and reserves are healthy.
In our sample of project buybacks, teams return ~64% of revenue on average, and those with stronger traction start buybacks at higher valuations.
Not all buybacks are equal.
By tracking the P/S ratio, we find that buybacks at lower valuations preserve far more treasury value than those executed near peaks, even when repurchasing at the same price.
Anchoring execution to valuation can keep teams disciplined across cycles.
The Dynamic FDV model scales buyback intensity with valuation, buying more when it counts, and less when the market’s crowded. In practice, this approach helps preserve treasury and lower average cost.
While the above models can help decide when to buy, they don’t address how those buys are paced.
Smoothing buybacks over time can remove short-lived spikes, dampen reflexivity, and create a steadier baseline for assessing performance and market impact.
If teams set a buyback price range, they can explore options-based covered puts to earn upfront income while executing.
This approach spreads purchases across multiple price levels, smooths entries, and still generates revenue even if prices never reach those predefined levels.
Projects should match buybacks to organic rather than total trading volume.
Oversizing allocations based on inflated volume can distort prices, create slippage, and send false signals to the market. Calibrating buybacks to organic activity helps prevent these effects.
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