New method finds better arbitrage opportunities in AMMs.
problem Finding optimal arbitrage trades in multi-token AMMs.
method Closed-form solutions using convex optimisation.
result Better arbitrage opportunities than traditional methods.
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48 results for “AMM arbitrage”
This paper studies how AMMs can minimize losses from arbitrage while retaining uninformed trading activity.
problem Minimizing losses from arbitrage in AMMs while retaining uninformed trading activity.
method Modeling arbitrage dynamics and sensitivity to fee choices, mapping to a random walk with a reward scheme.
result AMMs can maximize value retention by optimizing fee structures.
This study examines fees in AMMs to reduce losses from informed orderflow.
problem Minimizing losses from informed orderflow in AMMs.
method Modeling arbitrage dynamics and sensitivity to fee choices.
result Identified fees that mimic price directionality to reduce losses.
Unified routing and arbitrage with concave continuation.
problem Combining routing and arbitrage in financial markets.
method Extending AMM trade functions to negative inputs via concave continuation.
result Unified approach unifies routing and arbitrage.
Study shows AMM liquidity providers lose more than they earn, with varying profitability across pairs.
problem Arbitrage losses by liquidity providers on AMMs exceed fees earned.
method Empirical study of losses and profitability across different AMM pools and block times.
result Uniswap v2 pools are more profitable for passive LPs than Uniswap v3.
Blockchain-based exchanges adopt based on token pair volatility and personal use.
problem Token value loss and arbitrage issues in decentralized exchanges.
method Investigation of Automated Market Makers (AMMs) using transaction-level data.
result AMMs are adopted for high personal use or highly correlated token price movements.
This paper addresses AMMs for expiring assets, ensuring liquidity and risk management.
problem AMMs struggle with assets that expire, leading to liquidity issues and risk exposure.
method Combines AMM and limit-order book features, ensuring liveness and dynamic price adjustment.
result A DEX for expiring assets maintains liquidity and risk management.
Modeling fees impacts on arbitrage profits and LP losses in AMMs.
problem Impact of trading fees on arbitrage profits and LP losses in AMMs.
method Extended model of AMMs with fees and Poisson block generation times, computed instantaneous rate of arbitrage profit.
result Fees scale down arbitrage profits, reducing LP losses with faster block rates and lower gas fees.
Dynamic-weight AMMs outperform traditional CEX rebalancing in tokenized funds, especially on L2s.
problem Improving asset allocation efficiency in decentralized finance (DeFi) protocols.
method Block-level arbitrage analysis and long-term performance benchmarks on two live pools.
result Dynamic-weight AMMs can achieve performance comparable to or better than traditional CEX rebalancing, especially on Layer 2 (L2) networks.
Modeling price dynamics in AMMs with fees using geometric Brownian motion.
problem Understanding price dynamics in AMMs with transaction fees.
method Geometric Brownian motion, local times, excursion theory.
result Derivation of time-changed representation and limiting behavior of AMM prices.
New formula calculates loss from arbitrage in blockchain liquidity pools.
problem Calculating loss from arbitrage in Automated Market Makers (AMMs) under varying block times.
method Derived a closed-form approximation for expected loss using random walk theory.
result The formula approximates the loss from arbitrage with high accuracy and shows that constant block intervals minimize this loss.
A new AMM mechanism reduces losses and maximizes revenue from orderflows.
problem Reduces losses to informed orderflow and maximizes revenue from uninformed orderflow.
method Runs an onchain auction for pool manager role, allowing fee setting and price sensitivity.
result Proves higher liquidity in equilibrium compared to standard AMMs.
Optimal fees protect passive LPs in AMMs under varying market conditions.
problem Adverse selection losses in AMMs are not offset by static trading fees.
method Dynamic reduced-form model with parallel AMM and CEX, large-scale simulations, real market data analysis.
result Optimal AMM fees are stable under normal conditions but high in volatile periods to protect LPs.
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.
Marginal Price Optimizationq-fin.MF
Optimizes AMM markets with a new framework reducing complex optimization to simpler root finding.
problem Optimizing routing and arbitrage in AMM markets.
method Restricts search to boundary of optimal space using marginal prices, reducing high-dimensional optimization to lower-dimensional root finding.
result Significantly faster and more robust performance compared to the original convex optimization method.
Optimal dynamic fees found for AMMs to deter arbitrageurs and attract noise traders.
problem Optimizing fees in AMMs to balance against arbitrage and noise trading.
method Approximate closed-form solutions to control problem, study of fee structure.
result Two distinct fee regimes identified: high fees to deter arbitrage, low fees to attract noise traders.
This study optimizes trading and arbitrage in decentralized finance's CPMs, revealing convexity costs and developing efficient strategies.
problem Optimizing trading and arbitrage in decentralized finance's constant product markets (CPMs).
method Developed models for CPMs in competing centralised exchanges, CPMs, and both venues. Derived computationally efficient strategies.
result Accurately estimated convexity costs in CPMs, which are linear in trade size and nonlinear in liquidity depth and exchange rate.
Optimal rebalancing strategy improves AMM pool performance by 25%.
problem Optimizing the sequence of weights in dynamic AMM pools to minimize rebalancing costs.
method Using optimal interpolation and a cheap-to-compute approximation to achieve nearly optimal rebalancing.
result Approximately-optimal weight changes lead to significant increases in pool performance (up to 25%) under various conditions.
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.
We introduce trading fees into AMM models and analyze their impact on swap rates and profits.
problem The impact of trading fees on AMM models and users' trading strategies.
method We extend a foundational AMM model by introducing a trading fee parameter and analyze the model using economic and mathematical rigor.
result Trading fees affect the additivity of swap rates and can lead to greater profits from larger trades.
All DeFi markets are essentially CFMMs with increasing invariants.
problem Ensuring DeFi markets are free of arbitrage opportunities.
method Formalizing DeFi markets as CFMMs and proving the existence of increasing invariants.
result A DeFi market is arbitrage-free if and only if it has an increasing invariant.
Study growth of LP wealth in G3Ms affected by trading fees and arbitrage.
problem Analyzing profitability of LPs in G3Ms under trading fees and arbitrage.
method Stochastic reflected diffusion processes to model G3M dynamics.
result Long-term expected logarithmic growth of LP wealth calculated.
FluxLayer solves cross-chain liquidity fragmentation for better MEV capture.
problem Cross-chain fragmented liquidity and MEV optimization.
method Three-layer framework integrating settlement, intent, and leverage mechanisms.
result FluxLayer enhances cross-chain MEV by capturing more arbitrage opportunities.
New dynamic curves improve cryptocurrency exchange liquidity.
problem Low liquidity and arbitrage opportunities in existing AMMs.
method Dynamic curves adjust AMM function based on market prices.
result Maintains liquidity and total LP value over wide market price ranges.
The paper explores IL and LVR in AMMs, identifying three regimes and the effect of fees.
problem The relationship between impermanent loss and loss-versus-rebalancing in AMMs.
method Statistical analysis, focus on fees, block times, and continuous time limit.
result Three regimes identified: identical, distinct distribution functions, and distinct averages.
This research categorizes AMM designs for secure token exchanges.
problem Designing AMMs for cryptoeconomic systems can lead to financial risks and inefficiencies.
method Developed an AMM taxonomy and proposed three archetypes.
result AMM archetypes meet key requirements for token issuance and exchange.
DQN outperforms static policies in a dynamic fee environment for automated market makers.
problem How automated market makers (AMMs) perform under dynamic fees is unknown.
method Constructed a closed-loop simulator with dynamic fees, noise flow, and arbitrage.
result A small DQN policy outperforms static policies in a dynamic fee environment.
This paper mixes constant sum and constant product market makers to improve their features.
problem Improving the balance between stable exchange rates and liquidity in automated market makers.
method Mixing and designing new methods for AMMs with specific features.
result Demonstrates new tools for creating markets with desired characteristics.
Optimizes liquidity withdrawal timing for AMM LPs to balance fees and impermanent loss.
problem Balancing fees and impermanent loss in automated market makers.
method Stochastic control problem with endogenous stopping time, numerical solutions via Euler scheme and Longstaff-Schwartz method.
result Optimal exit strategy depends on volatility, fees, and market dynamics.
This paper extends liquidity returns in geometric mean markets to time-varying weights.
problem Understanding returns and no-arbitrage prices in geometric mean markets with time-varying weights.
method Extending known results for constant-weight G3Ms to the general case of G3Ms with time-varying and potentially stochastic weights.
result LP shares can replicate the payoffs of financial derivatives and various trading strategies.
The paper examines how cheaper and faster chains affect Uniswap v3 liquidity and profitability.
problem Impact of cheaper and faster chains on Uniswap v3 liquidity and profitability.
method Comparative analysis of Uniswap v3 activity on different chains with varying gas prices and block times.
result Liquidity providers are more capital efficient and receive higher fee returns on cheaper and faster chains.
The Adversarially Learned Mixture Model (AMM) is a generative model for unsupervised or semi-supervised data clustering. The AMM is the first adversarially optimized method to model the conditional dependence between inferred continuous and categorical latent variables. Experiments on the MNIST and SVHN datasets show t…
This paper introduces a new metric to improve the performance of AMMs over centralised exchanges.
problem Lack of a precise metric to compare AMM performance with centralised exchanges.
method Introduces Rebalancing-versus-Rebalancing (RVR) to measure AMM performance more accurately.
result AMMs can offer superior execution and rebalancing efficiency compared to centralised exchanges, even with low fees.
This research compiles knowledge on decentralized exchanges with AMM protocols.
problem Improving and developing AMM-based decentralized exchanges.
method Established a general AMM framework, compared mechanics, discussed security and privacy.
result Illustrated conservation and slippage functions of AMM protocols.
This paper examines the quantitative finance aspects of AMMs in decentralized finance.
problem Understanding the mathematical and financial underpinnings of AMMs.
method Review of existing literature and analysis of mathematical aspects.
result Interesting relationship between AMMs and derivatives pricing and hedging.
Adaptive market maker curves minimize arbitrage losses in DeFi.
problem Asset trading prices in AMMs trail behind centralized exchanges, causing LP losses.
method Adapts market maker bonding curves to trader behavior using a differential equation derived from the Glosten-Milgrom model.
result Optimal adaptive curves minimize arbitrage losses while remaining competitive.
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.
Walraswap solves batch auction pricing by finding optimal AMM swaps.
problem Executing all trade orders with optimal automated market makers (AMMs).
method Uses Brouwer's fixed-point theorem to find equilibrium prices.
result A solution to batch auction pricing problems in blockchain.
Enhances crypto-asset AMM with deep learning for better liquidity and efficiency.
problem Reduced slippage and improved liquidity in decentralized finance.
method Deep reinforcement learning for predicting market equilibrium and optimizing liquidity.
result Improved capital efficiency and reduced slippage for crypto-asset traders.
PA-AMM divides reserves into active and passive parts for better liquidity provider wealth.
problem Reducing adverse selection costs in AMMs.
method Divides reserves into active and passive parts, rebalancing top of each block.
result Improves LP wealth compared to CFMMs by reducing LVR.
We refine toxicity bounds for dynamic liquidation incentives in CP-AMM systems.
problem Ensuring stability in dynamic liquidation incentives in automated market makers.
method Derived state-dependent toxicity bounds for dynamic liquidation incentives, reconciling them with CP-AMM price dynamics.
result State-dependent bounds and liquidity-depth-only condition for dynamic liquidation incentives.
This thesis studies CPMMs with CL, developing strategies for LTs and LPs.
problem Trading mechanisms and strategies for CPMMs with CL.
method Formalizes CPMMs with CL, develops strategies using market data and models.
result Derives optimal strategies for LTs and LPs in CPMMs with CL.
We analyze impermanent loss in AMMs and show G3Ms are simplest.
problem Understanding impermanent loss in automated market makers.
method Developed a general framework and analyzed Geometric Mean Market Makers (G3Ms).
result G3Ms have the simplest impermanent loss characteristics.
Triangle Feesq-fin.MF
Triangle fees adjust fees based on trade size and price movement, improving price accuracy and revenue.
problem Price staleness and low fee revenue in AMMs.
method Decreasing marginal fees proportional to price movement, creating incentives for price accuracy.
result Triangle fees strictly improve the Pareto frontier of price accuracy versus losses.
This study interprets AMM fees as implied volatility, validating their relevance in digital asset markets.
problem Understanding the volatility of fees in decentralized exchange systems.
method Reinterpreting AMM fees as implied volatility and applying fixed-for-floating swaps to quote and validate these volatilities.
result The implied volatilities of digital assets can be accurately quoted using AMM fees, validating the approach.
Developed concentrated liquidity in n-dimensional AMM with polar coordinates in Rust.
problem Risk of stacking too many stablecoin pools.
method Building concentrated liquidity positions with ticks in polar coordinates in Rust.
result Hedging risk of stacking stablecoin pools.
Optimal dynamic fees for AMMs: A stochastic control approach
problem Fee policy of a liquidity provider in AMM
method Ergodic control problem
result Optimal fee is independent of wealth and constant relative risk aversion
Paper introduces CLVR to reduce price volatility in AMM exchanges.
problem Intra-block price volatility in AMM exchanges.
method CLVR constructs an ordering to minimize price volatility with low computation cost.
result CLVR minimizes price volatility with a small computation cost and can be externally verified.