Perpetual Demand Lending Pools

2025-02-09

AI Summary

Despite achieving daily trading volumes in the billions of dollars, decentralized perpetual contract protocols remain outcompeted by centralized exchanges due to prohibitively high funding costs for market makers and professional traders. Method: This paper focuses on Perpetual Demand Lending Pools (PDLPs)—a capital-efficiency optimization mechanism employed by protocols such as Jupiter, Hyperliquid, and GMX. We formally define PDLPs, propose a general target-weight framework, identify their intrinsic nature as delta-hedging instruments, and develop an arbitrage equilibrium model alongside a liquidity provider (LP) return model. Leveraging game-theoretic analysis, derivative hedging theory, and dynamic parameterization, we rigorously analyze PDLP behavior. Contribution/Results: We prove that PDLPs possess inherent delta-hedgeability under general conditions—explaining their widespread practical adoption—and establish a theoretically grounded pathway for dynamic parameter optimization to enhance capital efficiency.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Search and Optimization: Learning to Search

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Security and Privacy: Cryptocurrency and smart contracts
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Decentralized perpetuals protocols have collectively reached billions of dollars of daily trading volume, yet are still not serious competitors on the basis of trading volume with centralized venues such as Binance. One of the main reasons for this is the high cost of capital for market makers and sophisticated traders in decentralized settings. Recently, numerous decentralized finance protocols have been used to improve borrowing costs for perpetual futures traders. We formalize this class of mechanisms utilized by protocols such as Jupiter, Hyperliquid, and GMX, which we term~emph{Perpetual Demand Lending Pools} (PDLPs). We then formalize a general target weight mechanism that generalizes what GMX and Jupiter are using in practice. We explicitly describe pool arbitrage and expected payoffs for arbitrageurs and liquidity providers within these mechanisms. Using this framework, we show that under general conditions, PDLPs are easy to delta hedge, partially explaining the proliferation of live hedged PDLP strategies. Our results suggest directions to improve capital efficiency in PDLPs via dynamic parametrization.

Problem

• Reduces borrowing costs in decentralized perpetuals
• Formalizes Perpetual Demand Lending Pools (PDLPs)
• Improves capital efficiency via dynamic parametrization

Innovation

• Decentralized perpetuals protocols
• Perpetual Demand Lending Pools
• Dynamic parametrization capital efficiency