Dynamic Market Making via On-Chain Position Phases
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Solution Overview
Problem
Current automated market making systems and decentralized exchanges rely heavily on external data inputs and human intervention for dynamic liquidity management, which introduces complexity and potential points of failure due to latency, inaccuracies, or disruptions in external price feeds.
Innovation Solution
A system for autonomous digital asset position management using mathematically controlled liquidity pools that operate in distinct phases relative to defined price targets, allowing for automatic adjustments of position ratios based on market-derived price information without relying on external price feeds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If external price feeds and oracle services are used for dynamic liquidity management, then position adjustment capability is improved, but system reliability deteriorates due to latency, inaccuracies, or disruptions in external data sources
Solution Approach 1:
The patent extracts and removes the dependency on external price feeds and oracle services from the liquidity management system. Instead of relying on external data sources, the system uses internal on-chain data from the decentralized exchange to determine position adjustments, thereby eliminating the reliability issues associated with external feeds while maintaining adaptability to market conditions
Solution Approach 2:
The system becomes self-sufficient by using its own on-chain trading data to make liquidity management decisions. The smart contracts autonomously monitor price movements and execute position adjustments based on internal data, making the system self-service and independent of external oracle services, thus improving both reliability and maintaining adaptability
2Manufacturing precision
If manual oversight and active management processes are used to maintain balanced positions, then position control precision is improved, but device complexity deteriorates due to additional operational steps and human intervention requirements
Solution Approach 1:
The patent implements self-service through automated smart contracts that continuously monitor price movements and automatically execute position adjustments when predefined conditions are met. This eliminates the need for manual oversight while maintaining precise position control, thereby improving operational efficiency without adding complexity
Solution Approach 2:
The system incorporates continuous feedback loops where smart contracts monitor on-chain price data and automatically trigger rebalancing operations when positions deviate from target allocations. This automated feedback mechanism maintains position control precision while eliminating manual intervention, reducing operational complexity
3Device complexity
If fixed mathematical relationships are maintained between paired assets in liquidity pools, then system simplicity is improved, but adaptability to directional market movements deteriorates
Solution Approach 1:
The patent transforms the fixed mathematical relationships into dynamic ones by implementing smart contracts that automatically adjust position allocations based on directional price movements. The system maintains simplicity through automated rules that dynamically rebalance liquidity pool positions, enabling adaptation to market trends while preserving system simplicity through code-based logic
Data Source
AI summary
A target-based market making system that automatically manages asset pool positions through mathematically defined phases. The system determines position sizes using distribution functions relative to configured target prices, creating systematic sell pressure as prices approach those targets. Unlike traditional constant-product pools or derivative-based approaches, the system directly manages assets using phase transitions triggered by price-to-target ratios, maintaining full collateralization while enabling automated capture of value from price movements. The mathematical framework supports various distribution functions while preserving core position management mechanics.