Decentralized Finance

Quantum and Classical Machine Learning in Decentralized Finance: Comparative Evidence from Multi-Asset Backtesting of Automated Market Makers ArXiv ID: 2510.15903 “View on arXiv” Authors: Chi-Sheng Chen, Aidan Hung-Wen Tsai Abstract This study presents a comprehensive empirical comparison between quantum machine learning (QML) and classical machine learning (CML) approaches in Automated Market Makers (AMM) and Decentralized Finance (DeFi) trading strategies through extensive backtesting on 10 models across multiple cryptocurrency assets. Our analysis encompasses classical ML models (Random Forest, Gradient Boosting, Logistic Regression), pure quantum models (VQE Classifier, QNN, QSVM), hybrid quantum-classical models (QASA Hybrid, QASA Sequence, QuantumRWKV), and transformer models. The results demonstrate that hybrid quantum models achieve superior overall performance with 11.2% average return and 1.42 average Sharpe ratio, while classical ML models show 9.8% average return and 1.47 average Sharpe ratio. The QASA Sequence hybrid model achieves the highest individual return of 13.99% with the best Sharpe ratio of 1.76, demonstrating the potential of quantum-classical hybrid approaches in AMM and DeFi trading strategies. ...

Concentrated Liquidity with Leverage ArXiv ID: 2409.12803 “View on arXiv” Authors: Unknown Abstract Concentrated liquidity (CL) provisioning is a way how to improve the capital efficiency of Automated Market Makers (AMM). Allowing liquidity providers to use leverage is a step towards even higher capital efficiency. A number of Decentralized Finance (DeFi) protocols implement this technique in conjunction with overcollateralized lending. However, the properties of leveraged CL positions have not been formalized and are poorly understood in practice. This article describes the principles of a leveraged CL provisioning protocol, formally models the notions of margin level, assets, and debt, and proves that within this model, leveraged LP positions possess several properties that make them safe to use. ...

Political Leanings in Web3 Betting: Decoding the Interplay of Political and Profitable Motives ArXiv ID: 2407.14844 “View on arXiv” Authors: Unknown Abstract Harnessing the transparent blockchain user behavior data, we construct the Political Betting Leaning Score (PBLS) to measure political leanings based on betting within Web3 prediction markets. Focusing on Polymarket and starting from the 2024 U.S. Presidential Election, we synthesize behaviors over 15,000 addresses across 4,500 events and 8,500 markets, capturing the intensity and direction of their political leanings by the PBLS. We validate the PBLS through internal consistency checks and external comparisons. We uncover relationships between our PBLS and betting behaviors through over 800 features capturing various behavioral aspects. A case study of the 2022 U.S. Senate election further demonstrates the ability of our measurement while decoding the dynamic interaction between political and profitable motives. Our findings contribute to understanding decision-making in decentralized markets, enhancing the analysis of behaviors within Web3 prediction environments. The insights of this study reveal the potential of blockchain in enabling innovative, multidisciplinary studies and could inform the development of more effective online prediction markets, improve the accuracy of forecast, and help the design and optimization of platform mechanisms. The data and code for the paper are accessible at the following link: https://github.com/anonymous. ...

The Democratization of Wealth Management: Hedged Mutual Fund Blockchain Protocol ArXiv ID: 2405.02302 “View on arXiv” Authors: Unknown Abstract We develop several innovations to bring the best practices of traditional investment funds to the blockchain landscape. Specifically, we illustrate how: 1) fund prices can be updated regularly like mutual funds; 2) performance fees can be charged like hedge funds; 3) mutually hedged blockchain investment funds can operate with investor protection schemes, such as high water marks; and 4) measures to offset trading related slippage costs when redemptions happen. Using our concepts - and blockchain technology - traditional funds can calculate performance fees in a simplified manner and alleviate several operational issues. Blockchain can solve many problems for traditional finance, while tried and tested wealth management techniques can benefit decentralization, speeding its adoption. We provide detailed steps - including mathematical formulations and instructive pointers - to implement these ideas and discuss how our designs overcome several blockchain bottlenecks, making smart contracts smarter. We provide numerical illustrations of several scenarios related to our mechanisms. ...

A new adaptive pricing framework for perpetual protocols using liquidity curves and on-chain oracles ArXiv ID: 2308.16256 “View on arXiv” Authors: Unknown Abstract This whitepaper introduces an innovative mechanism for pricing perpetual contracts and quoting fees to traders based on current market conditions. The approach employs liquidity curves and on-chain oracles to establish a new adaptive pricing framework that considers various factors, ensuring pricing stability and predictability. The framework utilizes parabolic and sigmoid functions to quote prices and fees, accounting for liquidity, active long and short positions, and utilization. This whitepaper provides a detailed explanation of how the adaptive pricing framework, in conjunction with liquidity curves, operates through mathematical modeling and compares it to existing solutions. Furthermore, we explore additional features that enhance the overall efficiency of the decentralized perpetual protocol. ...

Improving Capital Efficiency and Impermanent Loss: Multi-Token Proactive Market Maker ArXiv ID: 2309.00632 “View on arXiv” Authors: Unknown Abstract Current approaches to the cryptocurrency automated market makers result in poor impermanent loss and capital efficiency. We analyze the mechanics underlying DODO Exchange’s proactive market maker (PMM) to probe for solutions to these issues, leading to our key insight of multi-token trading pools. We explore this paradigm primarily through the construction of a generalization of PMM, the multi-token token proactive market maker (MPMM). We show via simulations that MPMM has better impermanent loss and capital efficiency than comparable market makers under a variety of market scenarios. We also test multi-token generalizations of other common 2-token pool market makers. Overall, this work demonstrates several advantages of multi-token pools and introduces a novel multi-token pool market maker. ...

Fragmentation and optimal liquidity supply on decentralized exchanges ArXiv ID: 2307.13772 “View on arXiv” Authors: Unknown Abstract We investigate how liquidity providers (LPs) choose between high- and low-fee trading venues, in the face of a fixed common gas cost. Analyzing Uniswap data, we find that high-fee pools attract 58% of liquidity supply yet execute only 21% of volume. Large LPs dominate low-fee pools, frequently adjusting out-of-range positions in response to informed order flow. In contrast, small LPs converge to high-fee pools, accepting lower execution probabilities to mitigate adverse selection and liquidity management costs. Fragmented liquidity dominates a single-fee market, as it encourages more liquidity providers to enter the market, while fostering LP competition on the low-fee pool. ...

Decentralized Prediction Markets and Sports Books ArXiv ID: 2307.08768 “View on arXiv” Authors: Unknown Abstract Prediction markets allow traders to bet on potential future outcomes. These markets exist for weather, political, sports, and economic forecasting. Within this work we consider a decentralized framework for prediction markets using automated market makers (AMMs). Specifically, we construct a liquidity-based AMM structure for prediction markets that, under reasonable axioms on the underlying utility function, satisfy meaningful financial properties on the cost of betting and the resulting pricing oracle. Importantly, we study how liquidity can be pooled or withdrawn from the AMM and the resulting implications to the market behavior. In considering this decentralized framework, we additionally propose financially meaningful fees that can be collected for trading to compensate the liquidity providers for their vital market function. ...