These past few days, it’s not just about MMT hedging, but also yesterday’s two upward spikes in Monad and Megaeth’s pre-market contracts, and this morning’s massive pump by Soon (probably hedging for the November 23rd NFT unlock). Honestly, Clob-style contract hedging is way too easy to target when it comes to altcoins. Is there any team out there developing something specifically for pre-market hedging designs like MMT/Monad/MegaETH? Feels like there’s some PMF potential here—my gut says it’d lean toward a prediction market format. The simplest idea would be “multi-tiered range predictions,” like breaking Monad’s TGE price into multiple tiers from 1B to 5B. But that feels a bit too basic and uninspired. Is there any prediction market mechanism (probably something AMM-like) that could allow a large number of users to bet on what they think is the fair TGE price, inject liquidity into a pool, and then have an oracle determine a fair price at TGE? The pool would then distribute rewards based on the difference between users’ bets and the final TGE price—the closer the prediction, the bigger the reward, and vice versa. Projects could even allocate a portion of tokens for airdrops to users whose predictions have the smallest deviation from the actual TGE price. This would stimulate liquidity and encourage people to aim for the real TGE price. I consulted GPT, Grok, and Surf for ideas. Surf suggested a “predictive perpetual” model—CLOB + tiered shares, combined with circuit breakers + segmented liquidation mechanisms. Honestly, it left me a bit confused. GPT leaned toward Polymarket’s early LMSR AMM approach, where users buy “price range tokens” to form a continuous price expectation, which could then be used for futures or options. Grok proposed a Gaussian Parimutuel continuous settlement method. During the betting phase, users submit normal distribution parameters, and after TGE, rewards are distributed based on the TWAP price. The core formula (continuous Parimutuel + squared accuracy weighting) determines proportions based on probability density × bet squared. It’s even more convoluted than Surf’s idea, but I feel like it’s closest to my own “range accuracy reward” concept. Any wild ideas, fam? Who knows, maybe we can spin up a project out of this, haha.