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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,694 papers · 148 categories

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0111 · Mar 202019922001200920172026
10 results for “Price-oracle”
UAMM: Price-oracle based Automated Market Makercs.LG

UAMM uses external market prices to improve AMM efficiency and reduce liquidity provider risk.

problem Traditional AMMs lack consideration of external markets and risk management.
method UAMM calculates prices by incorporating external market prices and impermanent loss, maintaining constant product curve properties.
result UAMM eliminates arbitrage opportunities when external market prices are efficient, reducing liquidity provider risk.
AMMDecentralized ExchangesPrice-oracleLiquidity ProviderImpermanent Loss
2023-08-11abs ↗pdf ↗
Axioms for Automated Market Makers: A Mathematical Framework in FinTech and Decentralized Financeq-fin.MF

The paper establishes axioms for AMMs to ensure fair pricing and fee structures.

problem Ensuring fair and efficient pricing in decentralized finance (DeFi) AMMs.
method Formulating axioms on utility functions to characterize swap sizes and pricing oracles.
result Most existing AMMs satisfy the proposed axioms, and a new AMM is proposed with desirable properties.
Automated Market MakersDecentralized FinanceAxiomatic FrameworkSmart ContractsPrice Oracles
2022-10-03abs ↗pdf ↗
Oracle Counterpoint: Relationships between On-chain and Off-chain Market Datacs.CR

Study finds on-chain data can proxy off-chain cryptocurrency pricing.

problem Develop methods to proxy off-chain cryptocurrency pricing using on-chain data.
method Graphical models, mutual information, and ensemble machine learning.
result A significant amount of pricing information is contained in on-chain data, but precise prices are hard to recover except on short time scales.
cryptocurrency pricingon-chain dataoff-chain marketsoracle counterpointblockchain price oracles
2023-03-28abs ↗pdf ↗
On the Partial Convexification for Low-Rank Spectral Optimization: Rank Bounds and Algorithmsmath.OC

Partial convexification improves tractability of low-rank spectral optimization problems.

problem Minimizing linear objectives subject to matrix inequalities and low-rank constraints.
method Partial convexification of the domain set, deriving rank bounds, and developing a column generation algorithm.
result The partial convexification LSOP-R is equivalent to the original LSOP under certain conditions and yields high-quality solutions.
Low-rank Spectral OptimizationPartial ConvexificationRank BoundsColumn GenerationVector-based Convex Pricing Oracle
2023-05-12abs ↗pdf ↗
Cost of Manipulation in AMM-Based Oraclescs.CE

Study on costs of manipulating AMM-based price oracles.

problem Cost of manipulation in AMM-based on-chain price oracles.
method Analyzes the robustness of AMM-based oracles to strategic manipulation, considering different aggregation methods and market conditions.
result Manipulation costs depend on the total quote depth and can be minimized by optimal liquidity weights.
AMMOracleManipulationCostRobustness
2026-06-02abs ↗pdf ↗
Decentralized Prediction Markets and Sports Booksq-fin.MF

Decentralized prediction markets use AMMs to pool and withdraw liquidity, improving financial properties.

problem Creating a fair and efficient decentralized prediction market.
method Developed a liquidity-based AMM structure for prediction markets, studied liquidity management, and proposed trading fees.
result The decentralized AMM structure satisfies financial properties and can be managed with liquidity withdrawal.
decentralized prediction marketsautomated market makersliquidity managementfeesfinancial properties
2023-07-17abs ↗pdf ↗
Automated Market Makers: Mean-Variance Analysis of LPs Payoffs and Design of Pricing Functionsq-fin.TR

This paper analyzes and compares different Automated Market Maker mechanisms.

problem Impermanent loss in Constant Function Market Makers.
method Mean-Variance analysis of liquidity providers' profit and loss, comparison of different mechanisms.
result Optimized oracle-based mechanisms outperform Constant Function Market Makers.
Automated Market MakersImpermanent LossMean-Variance AnalysisOracle-Based MechanismsLiquidity Providers
2022-12-01abs ↗pdf ↗
Auto.gov: Learning-based Governance for Decentralized Finance (DeFi)q-fin.RM

Auto..gov uses RL to automate DeFi governance, improving security and profitability.

problem Manual DeFi governance is prone to human bias and financial risks.
method Auto..gov employs a deep Q-network reinforcement learning strategy for semi-automated parameter adjustments.
result Auto..gov outperforms traditional governance methods by at least 14% in terms of protocol profitability.
reinforcement learningdecentralized financegovernanceautomatedsecurity
2023-02-19abs ↗pdf ↗