Perpetual Demand Lending Pools
Tarun Chitra, Theo Diamandis, Nathan Sheng, Luke Sterle, Kamil Yusubov
TL;DR
The paper formalizes Perpetual Demand Lending Pools (PDLPs) as a class of decentralized lending mechanisms that finance perpetual futures by pooling assets, charging fees, and maintaining a target portfolio through arbitrage. It introduces a general Target Weight Mechanism (TWM) to align PDLP holdings with a desired composition and analyzes two main arbitrage channels: funding-rate arbitrage and PDLP share arbitrage, deriving conditions under which LPs and arbitrageurs profit. It also shows that TWMs reduce portfolio volatility and upper-bound delta exposure, enabling effective delta hedging, and develops a mean-variance framework for hedging PDLP risk, establishing clear criteria when hedging improves the Sharpe ratio. Collectively, the framework explains observed hedging-driven growth of PDLP vaults, highlights the balance between fees, liquidity, and price impact, and outlines directions for dynamic parameterization to enhance capital efficiency in decentralized perpetuals.
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.