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Competitive equilibria between staking and on-chain lending

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arxiv 2001.00919 v2 pith:LUE7ZIRF submitted 2019-11-28 q-fin.GN cs.DC

classification q-fin.GNcs.DC
keywords lendingsecuritymodelnetworkon-chainproofstakedstaking
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Proof of Stake (PoS) is a burgeoning Sybil resistance mechanism that aims to have a digital asset ("token") serve as security collateral in crypto networks. However, PoS has so far eluded a comprehensive threat model that encompasses both Byzantine attacks from distributed systems and financial attacks that arise from the dual usage of the token as a means of payment and a Sybil resistance mechanism. In particular, the existence of derivatives markets makes malicious coordination among validators easier to execute than in Proof of Work systems. We demonstrate that it is also possible for on-chain lending smart contracts to cannibalize network security in PoS systems. When the yield provided by these contracts is more attractive than the inflation rate provided from staking, stakers will tend to remove their staked tokens and lend them out, thus reducing network security. In this paper, we provide a simple stochastic model that describes how rational validators with varying risk preferences react to changes in staking and lending returns. For a particular configuration of this model, we provide a formal proof of a phase transition between equilibria in which tokens are predominantly staked and those in which they are predominantly lent. We further validate this emergent adversarial behavior (e.g. reduced staked token supply) with agent-based simulations that sample transitions under more realistic conditions. Our results illustrate that rational, non-adversarial actors can dramatically reduce PoS network security if block rewards are not calibrated appropriately above the expected yields of on-chain lending.

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  1. A theory of Lending Protocols in DeFi

    cs.GT 2025-06 conditional novelty 6.0 of 10

    An operational model of DeFi lending protocols with proved invariants, strategic front-running theorems, and formalized price and utilization manipulation attacks.

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