Small trades show unexpected price impact after fee changes.
problem Anomaly in price impact for small transaction volumes post-fee restructuring.
method Reviewed existing master curve for price impact, re-estimated after fee reductions, found anomalies, and rescaled by liquidity proxy.
result Master curve for price impact can be approximated using a liquidity proxy, providing a practical method for practitioners.
Study finds managers' tenure and education influence their choice between in-court and out-of-court restructuring.
problem Exploring managers' characteristics and their impact on restructuring decisions.
method Empirical investigation using upper echelons theory and data from 342 managers of French firms.
result Managers with longer tenure and higher education levels prefer private restructuring over court involvement.
The paper analyzes XVA reduction strategies in financial crises using Mandatory Breaks, Restructuring, and Resets.
problem Challenges in client XVA management during crises when continuous collateralization is not feasible.
method Compares multiple trade strategies including Mandatory Breaks, Restructuring, and Resets.
result Resets can be twice as effective as Mandatory Breaks/Restructuring if there is no credit recovery. When recovery is at least 1/3, Mandatory Breaks/Restructuring can be more effective.
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.
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.
Study reveals dynamic causal relationships between Ethereum transaction fees and economic subsystems.
problem Historical gas fee volatility caused economic disequilibria and stakeholder challenges.
method Time-varying Granger causality analysis using data on active wallets and transaction volume.
result Dynamic bidirectional causal relationships between transaction fees and economic subsystems across Ethereum.
A simple formula approximates AUM fees' cumulative costs.
problem Estimating the total cost of AUM fees over time.
method Intuitive explanation and analytical derivation of a formula.
result Investments lose almost Nε% of their value over N years with an annual fee of ε%.
Study shows maker-taker fees improve market efficiency but increase costs.
problem Impact of maker-taker fees on total cost of taking orders.
method Agent-based simulation model for financial markets.
result Maker-taker fees increase total costs but improve market efficiency.
Improves parallel deep model performance by restructuring and pruning.
problem Latency in parallel deep model execution due to interdependency among sub-models.
method Layer-wise model restructuring and pruning, using ℓ0 optimization and Munkres assignment algorithm. result Significantly improves efficiency of distributed inference in terms of communication and computational complexity.
Study finds no significant short-term impact on liquidity supply after protocol fees were reduced.
problem Liquidity provider welfare is affected by protocol fees, but the impact on liquidity supply is unclear.
method Used a matched-overlap event-study difference-in-differences design to estimate the liquidity-supply response to take-rate cuts.
result No significant short-term impact on active liquidity or local depth; no change in LP participation or composition.
High-fee pools attract more liquidity but execute less volume; low-fee pools have more stable LPs.
problem Optimal liquidity supply and execution on decentralized exchanges with fixed gas costs.
method Analysis of Uniswap data to compare high- and low-fee pools.
result Fragmented liquidity leads to more LPs and competition, improving overall market efficiency.
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.
Study on optimal fees in hedge funds with first-loss compensation.
problem Determining the best fee structure for hedge funds with first-loss compensation.
method Solved the manager's non-concave utility maximization problem, calculated Pareto optimal first-loss schemes, and maximized a decision criterion on this set.
result Traditional fees are not Pareto optimal, and the preferred first-loss coverage guarantee varies with investor and market factors.
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
Study shows how management fees affect variable annuity guarantees pricing.
problem Impact of management fees on variable annuity guarantees pricing.
method Formulated and solved optimal withdrawal strategies from both policyholder and insurer perspectives using dynamic programming.
result Management fees lead to significant differences in guarantee insurance fees, explaining observed market prices.
We show how to restructure the counterparty risk faced by the originator of a securitization or covered bond arising from an interest rate hedging swap assisted by a "one-way" collateral agreement. This risk emerges when the swap is negotiated between the special purpose vehicle and a third party that covers itself thr…
ML system reduces overdraft fees for Mint users.
problem Overdraft fees burden Americans, leading to financial hardship.
method ML-driven overdraft early warning system (ODEWS).
result Saved $3 million in overdraft fees for Mint customers.
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.
Optimal fees for CFMMs prevent liquidity pools from competing to the bottom.
problem Maximizing liquidity provider returns in CFMMs with multiple pools.
method Theoretical and numerical analysis of Nash equilibria for optimal fees.
result Pure Nash equilibria of optimal fees exist for CFMMs using Uniswap's trade function.
New activation networks improve model efficiency and performance.
problem Creating hardware-efficient deep learning models.
method Restructurable Activation Networks (RANs) with RAN-explicit and RAN-implicit methods.
result RANs achieve state-of-the-art results with improved hardware efficiency.
Optimal fees for G3Ms align LP value with market accuracy.
problem Optimal fees for G3Ms to attract liquidity without sacrificing accuracy.
method Developed a framework for determining LP value with fees for G3Ms under diffusion.
result LPs prefer G3Ms over other strategies as fees approach zero.
A game-theoretic analysis of DEX competition through dynamic trading fees.
problem Competition between decentralized exchanges (DEXs) and their impact on trading fees and slippage.
method Characterization of an approximate Nash equilibrium via coupled system of partial differential equations and closed-form expressions for equilibrium fees.
result The equilibrium trading fees shift from the oracle price to a weighted average of the oracle and competitors' exchange rates under competition.
CFM fee income is insufficient to hedge market risk, study finds.
problem Inefficiency of CFM fee income in hedging market risk.
method Analysis through continuous-time financial mathematics and multi-agent simulations.
result Fee income is insufficient to compensate for market risk.
The study examines VIX-linked fees for GMWBs using explicit solution simulation methods.
problem Decreasing the sensitivity of insurer's liability to volatility risk in GMWBs.
method Explicit weak solution for VA account value and Monte Carlo simulations.
result VIX-linked fees decrease the sensitivity of the insurer's liability to volatility risk.
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.
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.
Simplified feature selection using a single agent with restructured choice strategy.
problem Efficiency and cost issues in multi-agent reinforced feature selection.
method Single-agent approach with restructured choice strategy, including scanning method, feature prioritization, state representation, and reward scheme.
result Improved efficiency and effectiveness of feature selection.
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.
Ethereum upgrades increased TPS and lowered fees, with L2s surpassing Solana in 2029.
problem Transaction speed and fees in Ethereum
method Comparing Ethereum Mainnet and Layer 2 networks, Solana, and Polygon
result Ethereum Mainnet and L2 networks surpassed Solana in terms of TPS and lowered fees
Optimizes routing in decentralized exchanges with gas fees.
problem Routing in decentralized exchanges with fixed gas fees.
method General optimization framework with mixed-integer model, incorporating gas fees.
result Explicit Karush-Kuhn-Tucker system linking prices, fees, and activation.
Study shows tuition fees in Germany reduce enrollment by up to 4.5%
problem Impact of German university tuition fees on enrollment rates
method Robust model selection and design-based inference in high-dimensions
result Significant negative impact of up to 4.5 percentage points on enrollment
This paper analyzes Ethereum's gas fees and their derivatives, providing a comprehensive model.
problem Understanding and predicting gas fees on the Ethereum blockchain.
method Analyzed Ethereum's gas fee structure and used a fractional Ornstein-Uhlenbeck process to model gas prices.
result A model for pricing and trading gas fee derivatives to hedge against volatility.
Study analyzes fees linked to VIX index in annuity contracts.
problem Impact of VIX-linked fees on annuity contract surrender strategies.
method Two-layer continuous-time Markov chain approximation for fund value process.
result Optimal surrender strategy is more robust to VIX-linked fees.
QLAMMP optimizes fees on AMMs using Q-Learning.
problem Static AMMs cannot adapt to market changes, leading to high slippage.
method Developed a Q-Learning Agent (QLAMMP) to learn optimal fee rates.
result QLAMMP consistently outperforms static AMMs under various market conditions.
The paper analyzes transaction fees on blockchains using a priority queue model.
problem Understanding and optimizing transaction fees on blockchain networks.
method An M/G^K/1 priority queue model is used to analyze transaction fees and user behavior.
result New insights into the dynamics of transaction fees and their impact on user behavior are provided.
Optimal trading strategy between CEXs and DEXs with priority fees and stochastic delays.
problem Managing latency risk in trading between centralized and decentralized exchanges.
method Developed a mixed control framework combining absolutely continuous controls with impulse interventions, allowing for stochastic execution delays and multiple pending orders.
result Optimal priority fee selection significantly outperforms non-strategic fee selection.
DyFEn simulates blockchain for fee setting in payment channels.
problem Dynamic fee setting in off-chain payment channels.
method Agent-based reinforcement learning in a blockchain simulation.
result Empirical results of reinforcement learning methods on dynamic fee setting.
Modeling gas fee competition in decentralized exchanges to optimize arbitrage profits.
problem Gas fees and transaction ordering in decentralized exchanges create arbitrage opportunities.
method Developed a first equilibrium model of gas fee competition between two arbitrageurs under three transaction reversion settings.
result Mixed equilibria exist, and their characteristics depend on inventory risk and transaction settings.
Maker-taker fees can prevent algorithmic cooperation in market making, but not always.
problem Unexpected cooperation among independent algorithms in market making.
method Modeling market making as a repeated game, experimental analysis of transaction costs and rebates.
result Maker-taker fee models can destabilize cooperation, but not always with a specific relationship between costs and rebates.
One of the main issues affecting the Italian NHS is the healthcare deficit: according to current agreements between the Italian State and its Regions, public funding of regional NHS is now limited to the amount of regional deficit and is subject to previous assessment of strict adherence to constraint on regional healt…
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.
Machine learning refactors knowledge to improve learning efficiency.
problem Inductive program synthesis efficiency through knowledge restructuring.
method Introduces Knorf, a system that refactors knowledge bases using constraint optimization.
result Learning from refactored knowledge improves predictive accuracy fourfold and reduces learning time by half.
Uniswap v3 LPs suffer significant Impermanent Loss despite higher fees.
problem Impermanent Loss in leveraged liquidity provision on Uniswap v3.
method Analysis of 17 pools covering 43% of TVL, calculating fees and IL.
result LPs would have been better off by $60.8m had they HODLd.
Paper uses relaxation techniques to find optimal brokerage fees with private signals.
problem Finding optimal brokerage fees for clients with private trading signals.
method Relaxation techniques to establish contract existence in asymmetric information settings.
result Existence of optimal brokerage fees established in a market model with private signals.
The growth-optimal portfolio optimization strategy pioneered by Kelly is based on constant portfolio rebalancing which makes it sensitive to transaction fees. We examine the effect of fees on an example of a risky asset with a binary return distribution and show that the fees may give rise to an optimal period of portf…
Blockchain scaling reduces gas fees, allowing more frequent liquidity updates and concentration.
problem Adverse selection risk and high gas fees on decentralized exchanges.
method Instrumental variables analysis using blockchain scaling solutions (Arbitrum, Polygon) as instruments.
result Higher repositioning intensity and precision lead to greater liquidity concentration, benefiting small trades.
A fund manager invests both the fund's assets and own private wealth in separate but potentially correlated risky assets, aiming to maximize expected utility from private wealth in the long run. If relative risk aversion and investment opportunities are constant, we find that the fund's portfolio depends only on the fu…
Investors optimize liquid staking decisions in LSP and AMM protocols.
problem Optimal timing and allocation in liquid staking protocols.
method Derive optimal allocation strategy and model optimal exit timing using Laplace transforms and free-boundary techniques.
result Optimal stop-loss strategy maximizes expected payoff, influenced by fees and opportunity gains.