Research Pulse Issue #80 08/29/2022

  1. Improving Proof of Stake Economic Security via MEV Redistribution
    Authors: Tarun Chitra and Kshitij Kulkarni

Maximal Extractable Value (MEV) has generally been viewed as a negative, parasitic aspect of economic transactions on blockchains that increases costs for nonstrategic users. Recent work has shown that MEV is not always bad for social welfare in crypto networks. In this note, we demonstrate that if rational validators in Proof of Stake (PoS) protocols are able to earn a portion of MEV revenue, by a process we call MEV redistribution, they are disincentivized to unstake and lower economic security. We construct a joint staking-lending dynamical system in which a fraction of MEV revenue is used to increase staking returns. We formally show that this MEV redistribution can avoid bad competitive equilibria between staking and lending in which no users stake under benign conditions on the reward inflation schedule of the protocol, and conduct numerical simulations that demonstrate this. This represents another potentially positive externality of MEV, provided that the mechanism for redistribution is well-designed.

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  • Maximal Extractable Value (MEV) has been shown to cause negative externalities to regular users, such as increased slippage rates in DEXs as well as increased transactional costs.
  • This paper evaluates MEV in a Proof-of-Stake context where developed lending markets for the staked asset exist. It provides interesting context and formalized mathematical models describing the competitive nature of lending and staking
  • The authors propose a fascinating schema to attempt to avoid bad competitive equilibria between staking and lending via a redistribution mechanism.
  • This mechanism effectively enables MEV revenue to be shared with PoS validators and further incentivizes staking.
  1. zk-PCN: A Privacy-Preserving Payment Channel Network Using zk-SNARKs
    Authors: Wenxuan Yu, Minghui Xu, Dongxiao Yu, Xiuzhen Cheng, Qin Hu, and Zehui Xiong

Payment channel network (PCN) is a layer-two scaling solution that enables fast off-chain transactions but does not involve on-chain transaction settlement. PCNs raise new privacy issues including balance secrecy, relationship anonymity and payment privacy. Moreover, protecting privacy causes low transaction success rates. To address this dilemma, we propose zk-PCN, a privacy-preserving payment channel network using zk-SNARKs. We prevent from exposing true balances by setting up public balances instead. Using public balances, zk-PCN can guarantee high transaction success rates and protect PCN privacy with zero-knowledge proofs. Additionally, zk-PCN is compatible with the existing routing algorithms of PCNs. To support such compatibility, we propose zk-IPCN to improve zk-PCN with a novel proof generation (RPG) algorithm. zk-IPCN reduces the overheads of storing channel information and lowers the frequency of generating zero-knowledge proofs. Finally, extensive simulations demonstrate the effectiveness and efficiency of zkPCN in various settings.

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  • Payment Channel Networks (PCNs), like Bitcoin’s Lightning Network, provide a scalable way to transfer funds between users.
  • However, there are concerns around their privacy guarantees and many proof-of-concept privacy attacks on Lightning have been published.
  • This paper provides a new approach to the construction of PCNs, leveraging Zero Knowledge Proofs to theoretically increase the privacy and efficiency of layer 2 payments.
  1. To EVM or Not to EVM: Blockchain Compatibility and Network Effects
    Authors: Ruizhe Jia and Steven Yin

We study the competition between blockchains in a multi-chain environment, where a dominant EVM-compatible blockchain (e.g., Ethereum) co-exists with an alternative EVMcompatible (e.g., Avalanche) and an EVM-incompatible (e.g., Algorand) blockchain. While EVM compatibility allows existing Ethereum users and developers to migrate more easily over to the alternative layer-1, EVM incompatibility might allow the firms to build more loyal and “sticky” user base, and in turn a more robust ecosystem. As such, the choice to be EVMcompatible is not merely a technological decision, but also an important strategic decision. In this paper, we develop a game theoretic model to study this competitive dynamic, and find that at equilibrium, new entrants/developers tend to adopt the dominant blockchain. To avoid adoption failure, the alternative blockchains have to either (1) directly subsidize the new entrant firms or (2) offer better features, which in practice can take form in lower transaction costs, faster finality, or larger network effects. We find that it is easier for EVMcompatible blockchains to attract users through direct subsidy, while it is more efficient for EVM-incompatible blockchains to attract users through offering better features/products.

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  • Smart contracts have been popularized by Ethereum, in part due to the high functionality enabled by its execution engine, the Ethereum Virtual Machine (EVM).
  • Competing layer 1s, such as Avalanche, have attempted to gain market share by enabling applications built on Ethereum to be executed on their platforms. This is predominantly done by copying the EVM and reusing all open-source software built for it.
  • This paper provides a fascinating analysis of this trend and features insights on why the EVM became an industry standard as well as the strategic significance of building EVM-compatible applications.
  1. Exploring Price Accuracy on Uniswap V3 in Times of Distress
    Authors: Lioba Heimbach, Eric Schertenleib, and Roger Wattenhofer

Financial markets have evolved over centuries, and exchanges have converged to rely on the order book mechanism for market making. Latency on the blockchain, however, has prevented decentralized exchanges (DEXes) from utilizing the order book mechanism and instead gave rise to the development of market designs that are better suited to a blockchain. Although the first widely popularized DEX, Uniswap V2, stood out through its astonishing simplicity, a recent design overhaul introduced with Uniswap V3 has introduced increasing levels of complexity aiming to increase capital efficiency.
In this work, we empirically study the ability of Unsiwap V3 to handle unexpected price shocks. Our analysis finds that the prices on Uniswap V3 were inaccurate during the recent abrupt price drops of two stablecoins: UST and USDT. We identify the lack of agility required of Unsiwap V3 liquidity providers as the root cause of these worrying price inaccuracies. Additionally, we outline that there are too few incentives for liquidity providers to enter liquidity pools, given the elevated volatility in such market conditions.

Link to Paper

  • Decentralized exchanges (DEXs), such as Uniswap, may at times settle more trades than the largest centralized exchanges. In order to better compete with them, Uniswap recently released the third iteration of its protocol, Uniswap v3, which attempts to further improve price efficiency in its markets.
  • This paper provides an empirical evaluation of efficiency in Uniswap v3 in times of price shocks and compares these markets to their centralized counterparts.
  • The authors find critical pricing inefficiencies in Uniswap v3 and highlight some of the structural problems that impact the liquidity providers of these markets.
  1. Analysis of Non-Fungible Token Pricing Factors with Machine Learning
    Authors: Kin-Hon Ho, Yun Hou, Tse-Tin Chan, and Haoyuan Pan

Rarity is known to be a factor in the price of nonfungible tokens (NFTs). Most investors make their purchasing decisions based on the rarity score or rarity rank of NFTs. However, not all rare NFTs are associated with a higher price, especially for play-to-earn gaming NFTs. In this paper, we studied the top-ranked play-to-earn gaming NFTs on Axie Infinity. We found that, in addition to rarity, utility is also a significant factor influencing the price. Furthermore, we use utility as a predictor to predict the price of Axies using the XGBoost regressor. Our results reveal that, compared to using rarity-based predictors only, leveraging utility-based predictors can improve the prediction accuracy, thus highlighting utility as a price determinant for play-to-earn gaming NFTs.

Link to Paper

  • The pricing of Non-fungible Tokens (NFTs) is susceptible to multiple factors. Generally speaking, the rarity of an NFT can be a major determinant of its price.
  • This paper evaluates the role that rarity plays in pricing NFTs, especially in the field of gaming, by looking at on-chain data from Axie Infinity.
  • They find that, although rarity plays a major role in valuation, the utility provided by the NFT can also drastically impact its value.
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