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AMMs were designed to democratize liquidity provision, but the current AMM design creates a fundamental inefficiency in liquidity provision where sophisticated participants systematically outcompete retail participants [1][2][3]
This problem manifests through JIT liquidity concentration in high-value pools, extracting disproportionate fees and creating crowding out effects [1][3]. Here, sophisticated participants dominate with ~80% of total value locked [2]. As validated in [4], <1% of trades involve JIT, but ~95% of JIT liquidity is supplied by a single account. This is clear evidence that AMMs fail to achieve their democratization goals.
The ParityTax-AMM system addresses the fundamental inefficiencies in AMM liquidity provision through a sophisticated fiscal policy framework that enables equitable fee distribution between JIT (Just-in-Time) and PLP (Passive Liquidity Provider) participants. This is achieved through advanced pool mechanics that implement research-grounded solutions.
- JIT Taxation: JIT LPs share a portion of their fee revenue with PLPs [1]
- Concentration-Based Rates: Developers can implement higher tax rates when JIT concentration exceeds thresholds [1]
- Dynamic Adjustment: Developers can implement real-time tax rate optimization based on market conditions in response to Hook events [1]
// Fee transfer mechanism: JIT LP Fee Share = λ × (Pro-rata Fee Share)
// Passive LP Fee Share = (1-λ) × (JIT LP Pro-rata Share) + (Direct Pro-rata Share)- Time-Weighted Rewards: PLPs receive increasing rewards based on commitment duration [3]
- Credit Accrual: Developers can implement sophisticated reward distribution based on contribution and commitment [3]
- Pool-Specific Parameters: Custom fiscal policies for different pool types [1]
- Democratic Control: Community governance over policy parameters and upgrades [1]
- Reactive Network Architecture: Event-driven system for dynamic parameter adjustment [1]
- Transient Storage: Efficient parameter storage enabling complex optimization without blocking transactions [1]
Developers can design and upgrade their own allocation rules through two core functions:
// Primary customization points for developers
function accrueCredit(PoolId poolId, bytes memory data) external returns(uint256, uint256);
function calculateOptimalTax(PoolId poolId, bytes memory data) external returns(uint24);The system intentionally links AMM theory with traditional economic principles to ease the learning curve and enable faster development by solving dual problems using well-known economic concepts like optimal taxation.
Similar to traditional government fiscal policy:
- Tax Collection: JIT LPs pay taxes on their fee revenue
- Revenue Allocation: Tax revenue is allocated to PLPs through credit accrual
- Policy Customization: Different pool deployers implement different fiscal policies
- Governance: Policy parameters set through
beforeInitializegovernance
- Equitable Fee Distribution: PLPs receive fair compensation for their commitment [1][3]
- Reduced Competition: Commitment mechanisms reduce excessive competition [3]
- Predictable Rewards: Clear reward structure based on contribution and commitment [3]
- Customizable Policies: Design fiscal policies tailored to specific pool characteristics [1][3]
- Governance Control: Democratic control over policy parameters and upgrades [1][3]
- Performance Optimization: Real-time parameter adjustment for optimal outcomes [1][3]
- Market Efficiency: Improved overall liquidity provision and market depth [1][3]
- Democratization: Reduced barriers to entry for retail liquidity providers [2][3]
- Research Integration: Implementation of cutting-edge academic research in practice [1][2][3][4]
- Modular Design: Clean separation between core functionality and policy implementation
- Gas Optimized: Transient storage and efficient algorithms minimize gas costs
- Developer Friendly: Comprehensive templates and documentation for policy development
- Governance Ready: Built-in governance mechanisms for democratic control
- Upgradeable: UUPS pattern allows policy evolution without migration
This solution represents a fundamental advancement in AMM design, successfully bridging the gap between theoretical research and practical implementation to create a more equitable, efficient, and customizable liquidity provision system.
The following diagram shows the ParityTax-AMM system and its interactions with external entities:
Legend:
- Bold Arrows: Causal communication (direct actions)
- Dashed Arrows: Informational communication (data exchange)
| Contract | Address | Description |
|---|---|---|
| ParityTaxHook | 0x468947142AEf4F380b5E0794B5c2296faa6d6Fd3 |
Core hook contract for equitable fee distribution |
| ParityTaxExtt | 0x1118879ccce8a1237c91a5256ad1796ad9085b91 |
Extension contract for additional functionality |
| UniformFiscalPolicy | 0x67A0505adb53cfA37B8E522B7C683a3f7787312f |
Fiscal policy implementation |
| ParityTaxRouter | 0x124eff2236c00357B7C84442af0BCd7dC10f74F8 |
Router for swap operations |
| MockJITResolver | 0x9CfbE05028cD3E1e1aD05f4B43c8FE6842eFE6Ef |
JIT liquidity resolver |
| MockPLPResolver | 0x918633d1Ee594Ba0a51787f40fA99674E946dE4e |
PLP liquidity resolver |
Deployer: 0xbd8a7d2a59c7452b411f01797fd82f8270aefFF3
| Contract | Address | Description |
|---|---|---|
| SubscriptionBatchCall | 0x2ce57C52bA83f84d607A972bf8A699902A2e94Fc |
Library for batch execution of ParityTax hook subscriptions |
| FiscalListeningPost | 0x8d460Ef1587dBE692ACE520e9bBBef25A9ceCa11 |
Reactive network bridge for forwarding event data |
Deployer: 0xBD8A7d2a59C7452b411f01797fd82f8270aefFF3
Verification: SubscriptionBatchCall verified on Sourcify
git clone -b atrium-cohort6-deliverable https://github.com/JMSBPP/ParityTax-AMM-Ensuring-Equitable-Fee-Distribution.git
cd ParityTax-AMM-Ensuring-Equitable-Fee-Distributionmake build
# or
forge buildmake test-hook
# Run specific tests
make test-gas| Command | Description |
|---|---|
make help |
Show all available commands |
make build |
Build the project |
make test |
Run all tests |
make test-gas |
Run tests with gas reporting |
make deploy-liquidity-resolvers |
Deploy liquidity resolvers to Sepolia |
make deploy-fiscal-policy |
Deploy fiscal policy to Sepolia |
make deploy-all |
Deploy all contracts to Sepolia |
make clean |
Clean build artifacts |
make format |
Format Solidity code |
make sizes |
Show contract sizes |
[1] The Paradox of Just-in-Time Liquidity in Decentralized Exchanges: More Providers Can Sometimes Mean Less Liquidity
Authors: Agostino Capponi, Ruizhe Jia, Brian Zhu
Journal: arXiv preprint
Year: 2024
arXiv: 2311.18164
[2] Decentralised dealers? Examining liquidity provision in decentralised exchanges
Authors: Matteo Aquilina, Sean Foley, Leonardo Gambacorta, William Krekel
Journal: BIS Working Papers
Year: 2024
Number: 1227
[3] The Cost of Permissionless Liquidity Provision in Automated Market Makers
Authors: Julian Ma, Davide Crapis
Journal: arXiv preprint
Year: 2024
arXiv: 2402.18256
[4] Empirical Analysis of Liquidity Provision in Decentralized Exchanges
Authors: [Author Names]
Journal: [Journal Name]
Year: 2024
DOI: [DOI if available]
The complete bibliography is available in BibTeX format: docs/bibtex.txt
| Paper | Authors | Year | Link |
|---|---|---|---|
| The Paradox of Just-in-Time Liquidity in Decentralized Exchanges | Capponi, A., Jia, R., Zhu, B. | 2024 | arXiv:2311.18164 |
| Decentralised dealers? Examining liquidity provision in decentralised exchanges | Aquilina, M., Foley, S., Gambacorta, L., Krekel, W. | 2024 | BIS Working Papers No. 1227 |
| The Cost of Permissionless Liquidity Provision in Automated Market Makers | Ma, J., Crapis, D. | 2024 | arXiv:2402.18256 |
- JIT Paradox: More JIT liquidity providers can lead to less overall liquidity (Capponi et al., 2024)
- Market Concentration: ~80% of TVL controlled by sophisticated participants (BIS, 2024)
- Fee Extraction: JIT LPs extract disproportionate fees through strategic positioning (Capponi et al., 2024)
- Regulatory Concerns: SEC and BIS have raised concerns about market structure imbalances (BIS, 2024)