Platform · Continuous / Distribution Markets
Dekant
The first continuous-outcome prediction market on Solana · draw a curve, get paid by how close you call it.
- Mechanism
- Continuous / Distribution Markets
- Chain
- Solana
- Status
- Live (devnet)
- Founded
- 2026
- Market types
- Continuous distribution (Gaussian MVP; distribution-general by design)
- Audience
- Power user · Quant · Crypto-native · Forecasters
- Website
- dekant.xyz
- @Dekantfi
Pricing mechanism
L2-norm CFAMM whose state is a probability density. Traders trade probability distributions, not buckets. Gaussian (mu, sigma) is the current MVP shape because it's intuitive; the protocol is distribution-general by design, with a roadmap to broader function/distribution models and eventually user-defined custom shapes (skew, multi-modal, custom uncertainty).
Settlement
Flexible multi-oracle model (not a single centralized resolver). Today: multiple admin-vetted centralized oracle providers; each market creator picks which oracle they trust. Roadmap: automated oracles for objective markets (e.g. Pyth for BTC-at-timestamp), UMA-style dispute/social-consensus resolution, and a complaint mechanism that can revoke a centralized oracle's privileges if it loses user trust.
Strengths
- First production on-chain implementation of Paradigm's Distribution Markets (Dec 2024) - traders trade a probability distribution, not a discrete bucket
- Distribution-general by design: Gaussian is only the MVP shape; roadmap supports broader models and user-defined custom shapes (skew, spread, multi-modal)
- Flexible multi-oracle model (creator-selectable, admin-vetted) with a decentralization roadmap (Pyth automated, UMA-style dispute, revocable centralized oracles) - not a single centralized resolver
- One curve replaces a 35+ binary strike ladder; Solana speed makes real-time curve interaction feasible
Weaknesses
- Mainnet not deployed (devnet only)
- Onboarding hard for non-power users (per early feedback); distribution UX is unfamiliar
About this mechanism
Trader expresses a full probability distribution (or precise point) over a numerical outcome; payoff is proximity-based. Genuine outcome-shape pricing rather than picking a side.