Litepaper — v0.1 Beta
The Next Generation
of Prediction Markets
of Prediction Markets
01 — Executive Summary
Why Prediction Markets Need a New Foundation
Prediction markets represent one of the most powerful mechanisms for aggregating distributed knowledge into actionable probability estimates. Yet the existing landscape — dominated by platforms such as Polymarket — continues to face persistent structural limitations: fragmented liquidity pools, high transaction latency, and onboarding friction that discourages broad participation.
Hyperpredict is built to resolve these constraints at their root. By deploying on the Hyperliquid L1 — a blockchain purpose-built for high-frequency financial applications — we deliver an institutional-grade trading experience for real-world event outcomes, with sub-second finality and deep native liquidity.
"Hyperpredict bridges the gap between real-world event forecasting and the high-performance throughput of the Hyperliquid ecosystem."
Our mission is to provide the most liquid, transparent, and censorship-resistant venue for forecasting everything from macroeconomic shifts to cultural events — accessible to any participant with a Web3 wallet.
02 — Infrastructure
Why Hyperliquid?
The choice of underlying infrastructure is not incidental — it is the core architectural decision that defines what a prediction market can and cannot offer its users. Hyperliquid L1 was selected for three compounding reasons.
Performance
Near-zero transaction latency enables real-time order placement and cancellation, matching the responsiveness users expect from centralized venues.
Liquidity
Hyperliquid's settlement layer provides direct access to established liquidity pools, reducing slippage and enabling efficient position sizing at scale.
Native Assets
Seamless integration with USDC and native ecosystem assets removes cross-chain complexity, allowing users to trade without bridging or wrapping.
Censorship Resistance
All settlement logic executes on-chain with full transparency. No centralized intermediary can alter, delay, or reverse confirmed outcomes.
03 — Core Mechanics
How the Platform Operates
Hyperpredict's trading layer is designed to combine the capital efficiency of order-book models with the accessibility of automated liquidity mechanisms.
Order Execution Model
Hyperpredict employs a hybrid model: a Central Limit Order Book (CLOB) for primary execution — ensuring price discovery driven by real market participants — augmented by automated market-making to guarantee baseline liquidity for all listed markets, regardless of trading volume.
Oracle Integration
Outcome integrity is enforced through a multi-source oracle architecture. Where applicable, we integrate with established decentralized data providers — including Pyth Network and Hyperliquid-native feeds — and apply cryptographic aggregation to prevent single-point manipulation. Each market's data source is specified transparently at creation.
Resolution Process
Market resolution follows a tiered process. For quantitative markets (price levels, economic indices), resolution is fully automated via oracle consensus. For qualitative or ambiguous outcomes, resolution defaults to a designated committee of verifiable data feeds, with a community dispute window prior to final settlement.
04 — Market Categories
What You Can Trade
Hyperpredict supports three fundamental market structures, covering the full spectrum of real-world forecasting use cases.
Binary Markets
Yes / No outcomes. Clean, direct exposure to a single event — for example: "Will BTC close above $100k before end of year?"
Categorical Markets
Multiple discrete outcomes. Suited for elections, tournament brackets, or protocol governance decisions where more than two results are possible.
Scalar Markets
Continuous value prediction. Users take positions on a specific numerical outcome — such as the next CPI print or the 90-day average ETH gas fee — with payoffs proportional to accuracy.
During the Limited Beta, coverage focuses on crypto-native indicators and select macroeconomic data points. The full market taxonomy — including cultural events and geopolitical outcomes — will be introduced progressively as the platform scales.
05 — Tokenomics & Ecosystem
Incentives and Fee Architecture
A sustainable prediction market must align the incentives of traders, liquidity providers, and the protocol itself. Hyperpredict's economic model is designed around three principles: transparency, fairness, and long-term ecosystem health.
Beta Incentives
Early participants who contribute meaningful volume, liquidity, or feedback during the Limited Beta phase will be recognized in the protocol's genesis distribution. Specific allocation details will be communicated ahead of the transition to public access.
Fee Structure
Trading fees during the Beta are minimized to cover network operational costs only. Upon full launch, fees will be distributed across three recipients: a protocol insurance fund (covering edge-case resolution failures), liquidity providers (rewarding capital deployment), and protocol-level governance. The precise split will be published prior to mainnet.
06 — Roadmap
Phased Deployment
Hyperpredict is being built in three deliberate phases, each predicated on the successful completion of the previous one.
Phase 1 — Current
Limited Beta
Core infrastructure deployment. Whitelist-based access, binary and categorical market testing, oracle integration, and initial stress-testing of the settlement layer.
Phase 2
Market Expansion
Introduction of scalar markets, expanded coverage categories, mobile-optimized interface, and public access with full fee structure activated.
Phase 3
Full Decentralization
Permissionless market creation, community-governed resolution, and full protocol autonomy transferred to on-chain governance.
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