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Turing Market

Turing M is an AI collective data-driven event derivative financial ecosystem. Built on Web3 technology, it establishes a decentralized prediction market platform focusing on political/sports/entertai

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描述

Project Introduction

Turing Market is described as a financial ecosystem for event derivatives, driven by AI and collective data. Built on Web3 technology, it functions as a decentralized prediction market platform that allows for trading on predictions for events across multiple domains, including politics, sports, and entertainment, aiming to overcome the limitations of traditional financial markets.

Core Features and Innovations

Technology and Trading:

  • AI Data Driven: The platform uses a Model Context Protocol (MCP) that integrates collective data to calibrate market probabilities in real-time.

  • Hybrid Trading Mechanism: It supports trading across multiple binary, mutually-exclusive markets, which enables users to employ complex strategies such as hedging portfolios.

  • Liquidity and Leverage: Turing Market provides 24/7 instant market access and offers up to 10x leveraged trading.

  • Prediction+Derivatives: It pioneers the use of event option contracts, allowing users to take long or short positions.

  • Cross-Market Arbitrage: The platform is designed to enable trading strategies that correlate real-world events with volatility in the crypto market.

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Ecosystem and Community:

  • Token Economy: The native TUIT token is integrated into trading, governance, and staking to create a demand growth flywheel.

  • Social Trading: It features a built-in system for sharing opinions and copy-trading, with plans to integrate DAO governance.

  • Community Co-creation: Users are empowered to propose their own event markets and can receive 1-3% of the transaction shares from their proposed events.

Links

Competitive Advantages & Business Model

  • Prediction Accuracy: The platform claims a 42% improvement in the efficiency of event analysis when compared to competitors.

  • User Incentives: A robust incentive program includes token dividends (sharing 50% of profits), a prediction leaderboard, and rewards for event proposals.

  • Compliance and Security: It ensures security through automated smart contract settlements, a compensation fund financed by 50% of operational costs, and algorithms to prevent manipulation.

  • Revenue Structure: The project targets $120 million in first-year trading volume, with revenue generated from a dual structure of transaction fees (2%) and outcome commissions (2%).

  • Distribution Model: 70% of revenue is allocated for market expansion, including agent and KOL commissions, while the remaining 30% is used for token buybacks and burns.

Technical Architecture

Turing Market operates on a hybrid decentralized exchange model, combining off-chain matching services provided by operators with trustless on-chain settlement. The system uses the TuringMarketFacet smart contract to perform atomic swaps between ERC1155 outcome tokens and ERC20 collateral assets.

Key architectural points include:

  • Orders are signed using the EIP712 standard for structured data signatures.

  • The platform supports matching orders that involve minting and merging operations, allowing for cross-matching between complementary outcome token orders.

  • A symmetric fee mechanism is implemented where fees are collected from the output assets. The fee calculation is designed to preserve market integrity, ensuring that complementary trades incur an equal fee value.

Team

The project is led by a team with extensive experience in their respective fields:

  • Jesse: CEO with over 10 years of experience in SaaS software market expansion.

  • RichRed: Investment Director with years of experience in Crypto market investment.

  • Sam: Chief Talent Officer.

  • David: CTO with years of CEX architecture experience and a track record of delivering multiple CEX projects.

  • George: CPO with over 10 years of leadership in internet financial products.

  • Adam: Chief Development Engineer with over 5 years in blockchain and 10+ years in full-stack development.

  • Rushen: Project Director & Agile Coach with years of project management experience.

  • Reyo: CMO and Chief Community Operations Manager.

Democratizing Access and Governance

  • Breaking Financial Limitations: The project's foundational goal is to establish a decentralized prediction market, aiming to break through the limitations of traditional financial markets.

  • Community-Led Governance: The platform has plans for DAO (Decentralized Autonomous Organization) governance integration, which would give the community direct control over the platform's future.

  • Community Co-creation: Users are empowered to propose their own event markets. This allows the community to shape the platform's content and direction, moving away from a centralized, top-down approach.

Equitable Economic Incentives

  • Profit Sharing: A significant portion of profits (50%) are shared with users through token dividends, creating a more equitable distribution of the platform's success.

  • Rewarding Contributions: Users who propose new event markets receive a 1-3% share of the transactions from those markets, directly rewarding their active participation and contribution.

  • Fair Revenue Use: 30% of the platform's revenue is allocated for token buybacks and burns, a mechanism that can benefit all token holders.

Market and Algorithmic Fairness

  • Anti-Manipulation: The platform implements anti-manipulation algorithms to ensure a fair trading environment for all participants.

  • Trustless Settlement: Settlements are completed "trustlessly on-chain," which removes the need for a central intermediary and reduces the potential for biased or unfair settlement practices.

  • Symmetric Fee Mechanism: The fee structure is explicitly designed to be symmetric to "preserve market integrity". This ensures that fees are applied fairly and predictably, regardless of the trade's specifics, as detailed in the example where selling 100 A at $0.99 and buying 100 A' at $0.01 incur an equal fee value.

Matching Scenarios

Asset Definitions

  • A - ERC1155 outcome token

  • A' - ERC1155 complementary outcome token*

  • C - ERC20 collateral token

  • All examples assume A and A' are priced at 0.5 USDC each

*Note: Complementary relationship means 1 outcome token + 1 complementary token can be merged into 1 collateral token, and vice versa (i.e., A + A' = C). Assume outcome tokens and collateral tokens have the same decimal precision. Examples assume C is USDC.

Scenario 1 - Minting Transaction

  • user1 buys 100 A, transfers 50 C to exchange

  • user2 buys 100 A', transfers 50 C to exchange

  • Exchange mints 100 A for user1, 100 A' for user2

const takerOrder = {
    salt: randomId(),
    maker: user1,
    tokenId: 1, // Token ID for A'
    tokenAmount: 100 * 10**6,
    tokenPriceInPaymentToken: 0.5 * 10**6, // 0.5 USDC (could be 0 for market orders)
    paymentTokenAddress: '0xxxxx', // USDC address
    slippageBps: 100, // Allowed slippage (0 indicates limit order)
    deadline: 1672531200, // Expiration timestamp
    side: 1, // 1: buy, 2: sell
    feeTokenAddress: '', // Fee token address (USDC or company token)
    
    // Signature fields
    sig: 'xxxxx', // Frontend signature of above data
    
    // Off-chain calculated transaction details
    exchangeNftAmount: 100 * 10**6, // NFT amount maker will receive
    paymentTokenAmount: 100 * 10**6, // USDC amount maker must pay
    paymentTokenAddress: '0xxxxx', // Payment token address (USDC)
    
    // Dual fee fields for multi-token fee support
    fee1Amount: 123, // Primary fee amount
    fee1TokenAddress: '0xxxxx', // Primary fee token (USDC/company token)
    fee2Amount: 456, // Secondary fee amount
    fee2TokenAddress: '0xxxxx' // Secondary fee token (USDC/company token)
}

const makerOrders = [{    salt: randomId(),    maker: user2,    tokenId: 2, // Token ID for A'
    tokenAmount: 100 * 10**6,
    tokenPriceInPaymentToken: 0.5 * 10**6,
    paymentTokenAddress: '0xxxxx',
    slippageBps: 100,
    deadline: 1672531200,
    side: 1,
    feeTokenAddress: '',
    sig: 'xxxxx',
    exchangeNftAmount: 100 * 10**6,
    paymentTokenAmount: 100 * 10**6,
    paymentTokenAddress: '0xxxxx',
    fee1Amount: 123,
    fee1TokenAddress: '0xxxxx',
    fee2Amount: 456,
    fee2TokenAddress: '0xxxxx'
}]

matchOrders(takerOrder, makerOrders)

Scenario 2 - Regular Transaction

  • user1 buys 100 A, transfers 50 C to exchange

  • user2 sells 100 A, receives 50 C from exchange

Scenario 3 - Merge Transaction

  • user1 sells 100 A

  • user2 sells 100 A'

  • Exchange merges 100 A + 100 A' into 100 C

  • Exchange transfers 50 C to user1

  • Exchange transfers 50 C to user2

Fee Mechanism

Fees are collected from output assets (proceeds). For complementary binary tokens (A + A' = C), fees must maintain symmetry to preserve market integrity. Symmetry means selling 100 A at $0.99 and buying 100 A' at $0.01 should incur equal fee value.

Rules:

  • Buy operations (receiving A/A') charge fees on output tokens

  • Sell operations (receiving C) charge fees on collateral tokens

Base fee rate (baseFeeRate) is written into order structure, corresponding to 2x fee rate when tokens are equally priced ($0.50/$0.50). Price deviations use formula:

USDC fee = baseFeeRate * min(price, 1-price) * token quantity

Example 1:

  • price = 0.2

  • feeBps = 100

  • fee = 0.01 * min(0.2, 0.8) * 100 = 0.2

Example 2:

  • Selling 100 A at $0.99:
    0.01 * min(0.99, 0.01) * 100 = 0.01 (deduct 0.01 C as fee)

  • Buying 100 A' at $0.01:
    0.01 * min(0.01, 0.99) * 100 = 0.01 (deduct 1 A' as fee)

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本次黑客松进展

Complete all basic functions and launch the MVP version on the testnet

技术栈

Solidity
Vue
Web3

融资状态

NO

队长TTuringM
Github

Github 关联

https://github.com/TuringM-Labs/jutopia2025
赛道
GamingDAOAI