Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2208.06472

Perpetual Contract NFT as Collateral for DeFi Composability

HyoungSung Kim·Hyun-Sik Kim·Yong-Suk Park
View original source ↗Read source document ↗Export metadata ↓

Abstract

Ethereum and its standardized token interface have formed decentralized finance (DeFi), an open financial system based on blockchain smart contracts. The DeFi ecosystem has become richer with the introduction of DeFi composability projects, such as Lido finance and Curve finance. DeFi composability denotes the concatenation of DeFi services in which each DeFi service locks assets as collateral and gives another asset as liquidity of locked assets to providers. Providers use the tokens given for other concatenated DeFi services, such as lending, decentralized exchanges (DEXs), and derivatives. The DeFi ecosystem uses ERC-20 tokens which can represent the value of an asset. ERC-721 non-fungible tokens (NFTs) are not widely adopted in DeFi, since they represent rights to an asset and are not considered appropriate for valuation. In this paper, we propose a new concept, perpetual contract NFT, which exploits perpetual future contracts in the cryptocurrency derivatives market. Unlike futures contracts in a traditional derivatives market, in the cryptocurrency derivatives market, most futures contracts are perpetual. In addition, the value of futures contract is backed by collateral. Therefore, if we mint the rights to perpetual contracts as NFT, we can use the perpetual contract NFT as collateral for DeFi composability. To validate our proposal and its profitability, we experiment with the position NFT of Uniswap v3. Through validation, we show that our concept works in real-world scenarios.

Explore related subjects

cs.GT

Keep this discovery

BibTeXRIS

HyoungSung Kim, Hyun-Sik Kim, Yong-Suk Park. 2022-08-09. Perpetual Contract NFT as Collateral for DeFi Composability. https://doi.org/10.1109/access.2022.3225884

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

MMS Allocation for Chores with Online Agent Arrivals

We study the fair allocation of $m$ indivisible chores to $n$ agents with subadditive cost functions arriving online in an arbitrary order. Upon an agent's arrival, we are informed of her cost function and must irrevocably assign her a set of chores. We focus on the Maximin Share (MMS) fairness notion and aim to compute an allocation in which all items are assigned, and no agent incurs a cost more than $\alpha$ times her MMS. Without any prior information about the instance (other than $n$ and $m$), we design an algorithm with a competitive ratio of $O(\min\{n, k\log^{1+\epsilon}k, \log m\})$ for any constant $\epsilon > 0$, where $k$ denotes the number of cost function types. Our bound matches the best known offline approximation guarantees for MMS under subadditive costs and is nearly optimal with respect to all three parameters: we show that even for binary additive cost functions, no online algorithm can achieve a competitive ratio of $o(\min\{n, k\log k, \log m\})$. We then consider the setting in which the $k$ cost function types are known in advance (though the realized types of arriving agents are not). For additive cost functions, we provide an algorithm with a competitive ratio of $O(\min\{\log k, \log(kn)/\log\log(kn)\})$, and show that constant-competitive algorithms do not exist for general $k$, even for the binary additive setting. For binary additive functions when $k \le n$, we propose a $3$-competitive algorithm and establish a lower bound of $2$.

cs.GT↗
arXiv2026

Truncated Noisy Best-Response Algorithms: Toward Game Theoretic Learning with Safety Guarantees

We consider a game theoretic approach to solve multi-agent coordination problems with submodular maximization objectives. It is known for such problems that the Nash equilibria for the corresponding game are always within 50% of the optimal, but that the equilibria which achieve this worst-case bound are not stable. To exploit this instability, we propose a family of algorithms which we call Truncated Noisy Best-Response (TNBR) Algorithms. These algorithms are flexibly characterized by agents asynchronously and stochastically selecting actions from a neighbourhood of their best response payoffs. We compute bounds on the recurrent classes of TNBR algorithms' associated Markov chains. Our bounds fall into two categories: first, "Performance" bounds ensure that TNBR algorithms always have a high-value recurrent state; second, "Safety" bounds ensure that TNBR algorithms never have arbitrarily-bad recurrent states. Furthermore, these two types of bounds are linked by a waterbed-like effect: every game with a poor Safety guarantee necessarily has a favorable Performance guarantee.

cs.GT↗
arXiv2026

Existence of the Core in Approval-Based Committee Elections

We settle the main open question in the theory of approval-based multi-winner elections: we show that there always exists a committee in the core. The core is a stability and group fairness concept. The proof introduces a new voting rule that optimizes an entropy-like objective function over committees and payment systems. All local optima of this objective function lie in the core, which implies that a core committee can be found in polynomial time.

cs.GT↗