2025-12-11 10:28:34

Market Scoring Rules got interesting when AMMs started using them for outcome pricing in thin markets. LMSR—that's Logarithmic Market Scoring Rule—became the go-to solution here.

What makes it work? The logarithmic curve design. Basically prevents any single large holder from completely wrecking the price discovery process. When liquidity's scarce, this math keeps things from going sideways fast.

Smart mechanism for managing risk when order books can't.

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YieldHunter

· 12-14 10:08

lmsr's logarithmic curve is genuinely elegant but ngl, most degens still don't understand why it matters for thin markets... if you look at the data on actual slippage metrics, the difference is night and day compared to vanilla amms. technically speaking, the protection against whale manipulation is real but people still sleep on impermanent loss implications here

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MemeTokenGenius

· 12-13 04:14

LMSR is indeed awesome, a nemesis for big players trying to dump the market.

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AirdropHunterXM

· 12-11 17:54

LMSR these things do have some features, but how many actually enjoy using them comfortably in a thin market?

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DaoDeveloper

· 12-11 10:57

lmsr's logarithmic curve is honestly genius for preventing whale manipulation... way cleaner than watching thick order books get rekt in low-liquidity scenarios tbh

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ForumMiningMaster

· 12-11 10:56

LMSR this thing does have some substance, but the truly usable projects are scarce.

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DaoResearcher

· 12-11 10:55

According to the arguments in the white paper, the logarithmic curve design of LMSR indeed demonstrates incentive compatibility in thin markets, but here is a problem—what are the assumptions behind the hypothesis? We need to carefully examine the fragility of price discovery. It is worth noting that even with the smoothing properties of the logarithmic function, in high volatility environments, the influence of large traders can still bypass mechanism design through derivatives such as flash loans. Quoting Vitalik's perspective on oracle risks, a single-price mechanism always faces unresolved issues of multiple equilibria when dealing with complex games. It is recommended to first review the on-chain data of the Manifold Markets governance proposal, and you'll understand why purely mathematical solutions always encounter pitfalls in real-world deployment.

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