We study Privacy Pools, a novel smart contract-based privacy-enhancing protocol. The protocol introduces a mechanism for users to reveal certain properties of their transaction without having to reveal the transaction itself. The core concept involves allowing users to publish a zero-knowledge proof, demonstrating that their funds (do not) originate from known (un-)lawful sources, without publicly revealing their entire transaction history. This is achieved by proving membership in custom association sets, which are designed to demonstrate compliance with regulatory frameworks or social consensus. We illustrate how this mechanism can create a separating equilibrium between compliant and non-compliant withdrawals. Our work describes the technical underpinnings, incentives and broader implications of this mechanism, highlighting how Privacy Pools-like protocols can create more private yet compliant blockchain transactions.

In this paper we analyze constant product market makers (CPMMs). We formalize the liquidity providers' profitability conditions and introduce a concept we call the profitability frontier in xyk-space. We study the effect of mint and burn fees on the profitability frontier, consider various pool types, and compile a large data set from all Uniswap V2 transactions. We use this data to further study our theoretical framework and the profitability conditions. We show how the profitability of liquidity provision is severely affected by the costs of mint and burn calls relative to the portfolio size and the characteristics of the trading pair.

In this paper, we propose a fully decentralized and smart contract-based insurance protocol. We identify various issues in the Decentralized Finance (DeFi) insurance context and propose a solution to overcome these shortcomings. We introduce an economic model that allows for risk transfer without any external dependencies or centralized intermediaries. In particular, our proposal does not need any sort of subjective claim assessment, community voting or external data providers (oracles). Moreover, it solves the problem of over-insurance and proposes various ways to mitigate the capital inefficiencies usually seen with DeFi collateral. The work takes inspiration from peer-to-peer (P2P) insurance and collateralized debt obligations (CDO). We formally describe the protocol, assess its efficiency and key properties and present a reference implementation. Finally, we address limitations, extensions and ideas for further research.