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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.

168,657 papers · 148 categories

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23477093 · Jun 202019922001200920172026
48 results for Liquidity Rewards

Optimizes liquidity provision intervals for profitable AMM participation.

problem Financial losses from poor liquidity provision intervals and reallocation costs.
method Developed a tractable stochastic optimization problem.
result Computes optimal liquidity provision intervals for profitable liquidity concentration.

Backtesting framework for CLMMs on Uniswap V3 reduces reward estimation error.

problem Estimating rewards for CLMMs in Uniswap V3 liquidity pools.
method Parametric model for liquidity distribution, historical data analysis.
result Error in reward estimation less than 1% for each pool.

Optimizes liquidations in decentralized finance to manage credit risk.

problem Managing and liquidating positions in decentralized finance exchanges.
method Formulated as an ergodic optimal control problem, derived closed-form solutions for optimal liquidation strategies.
result Closed-form solutions balance immediate executions with price impacts and long-term rewards.

dYdX updates liquidity provider incentives to enhance trading efficiency.

problem Incentivizing liquidity providers to maintain efficient market structures.
method Analyzed various metrics (makerVolume, depths, spreads) and used historical trades to update the LP Incentives Programme.
result Updated the LP Incentives Programme to encourage more active and efficient liquidity.

PoEL protocol aims to efficiently create and secure liquidity for blockchain networks.

problem Lack of sustainable liquidity and network security in Proof of Stake blockchains.
method PoEL uses staking rewards to attract risk capital, structuring incentives for capital efficiency and security.
result PoEL protocol enhances blockchain network security and liquidity sustainability.

Study multi-agent RL in OTC markets, learning from agents' interactions.

problem Designing efficient RL solutions for OTC market interactions.
method Parameterized reward functions, shared policy learning, RL calibration.
result Agents learn to balance hedging and skewing in market simulations.

This paper explores leverage staking with stETH, revealing high returns but also significant risks.

problem Leverage staking introduces risks through intensified selling pressure and cascading liquidations.
method Formal framework for leverage staking, stress tests under extreme conditions of stETH devaluation.
result Leverage staking amplifies risks, leading to intensified selling pressure and price declines.

Paper presents a modular RL framework for Forex trading, addressing limitations of prior studies.

problem Challenges in applying RL to Forex trading, including unrealistic environments, simplified rewards, and restricted action spaces.
method Integrates three components: a friction-aware execution engine, a decomposable reward architecture, and a discrete action interface.
result Empirical evaluation shows strong non-monotonic reward interactions and optimal Sharpe ratio with the full reward configuration.

Market makers play an important role in providing liquidity to markets by continuously quoting prices at which they are willing to buy and sell, and managing inventory risk. In this paper, we build a multi-agent simulation of a dealer market and demonstrate that it can be used to understand the behavior of a reinforcem…

2019-11-14abs ↗pdf ↗
Deep Hedgingq-fin.CP

We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, market impact, liquidity constraints or risk limits using modern deep reinforcement machine learning methods. We discuss how standard reinforcement learning methods can be applied to non-linear r…

2018-02-08abs ↗pdf ↗

Study shows how crypto asset liquidity is affected by wash trading and proposes treatment to reduce liquidity diffusion.

problem Understanding and reducing crypto asset wash trading to improve liquidity.
method Proposed a two-component model for liquidity (jump and diffusion) and demonstrated the effectiveness of autoregressive models.
result Treatment on wash trading significantly reduces liquidity diffusion but not liquidity jump.

The study introduces new liquidity measures and models for assets with extreme liquidity.

problem Modeling assets with extreme liquidity, especially in crypto markets.
method Developed innovative liquidity premium measures, liquidity-adjusted return and volatility models, and used ARMA-GARCH/EGARCH models.
result The liquidity-adjusted models outperform traditional models in predicting asset performance at extreme liquidity.

A liquidity measure based on consideration and price range is proposed. Initially defined for daily data, Liquidity Index (LIX) can also be estimated via intraday data by using a time scaling mechanism. The link between LIX and the liquidity measure based on weighted average bid-ask spread is established. Using this li…

2014-12-16abs ↗pdf ↗

Research proposes a model to estimate transaction costs and assess asset liquidity risk.

problem Lack of standardized models for asset liquidity risk in asset management.
method Develops a market impact model and a two-regime model based on power-law property.
result Defines liquidity measures and applies model to stocks and bonds.

Improved ARMA-GARCH model for illiquid assets like cryptocurrencies.

problem Inadequate modeling of illiquid assets, especially cryptocurrencies, with traditional ARMA-GARCH models.
method Introducing liquidity-adjusted liquidity jump and diffusion metrics into ARMA-GARCH framework.
result The liquidity-adjusted model improves model fit and volatility sensitivity for cryptocurrencies.

Optimizes liquidity provision in decentralized exchanges with utility indifference market makers.

problem Impermanent loss in decentralized exchanges without transaction fees.
method Mathematical formulation of liquidity provision, focusing on utility indifference market makers.
result No-arbitrage conditions and optimal arbitrage strategies are established.

Third part of a study on liquidity risk in asset management, focusing on managing the asset-liability liquidity risk.

problem Managing the asset-liability liquidity risk in asset management.
method Develops a methodological and practical framework for liquidity stress testing programs.
result Proposes measurement, management, and monitoring tools for controlling the liquidity gap.

Develops a new model to better estimate cryptocurrency and stock volatility.

problem Misrepresentation of volatility and co-movement in traditional models.
method Introduces liquidity-sensitive multivariate volatility framework with novel liquidity measures.
result Liquidity-adjusted models yield more stable and interpretable risk structures.

Market making is a fundamental trading problem in which an agent provides liquidity by continually offering to buy and sell a security. The problem is challenging due to inventory risk, the risk of accumulating an unfavourable position and ultimately losing money. In this paper, we develop a high-fidelity simulation of…

2018-04-11abs ↗pdf ↗

Optimal early liquidation strategy reduces financial losses during crises.

problem Substantial losses from simultaneous asset liquidation at depressed prices.
method Developed a worst-case approach for optimal early liquidation, considering uncertainty of other banks' decisions.
result Proposed robust optimal strategy maximizes liquid assets' value at clearing, even with uncertainty.

JIT liquidity providers can sometimes reduce overall market liquidity by crowding out passive LPs.

problem JIT liquidity providers can reduce overall market liquidity by crowding out passive LPs.
method Game-theoretic model with asymmetrically informed agents to analyze JIT liquidity provision in blockchain-based decentralized exchanges.
result JIT LPs only provide liquidity to uninformed orders and crowd out passive LPs when order volume is not sufficiently elastic to pool depth, potentially reducing overall market liquidity.

New framework detects crypto wash trading using liquidity measures.

problem Detecting and monitoring wash trading in crypto assets.
method Developed a new framework to detect wash trading through real-time liquidity fluctuation measures.
result Joint elevation in liquidity jump and diffusion indicates wash trading in crypto assets.

We review different approaches for measuring the impact of liquidity on CDS prices. We start with reduced form models incorporating liquidity as an additional discount rate. We review Chen, Fabozzi and Sverdlove (2008) and Buhler and Trapp (2006, 2008), adopting different assumptions on how liquidity rates enter the CD…

2010-03-03abs ↗pdf ↗

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.

Study finds Indian mutual funds adjust cash holdings based on inflows, impacting stock purchases.

problem Active liquidity management by mutual funds in India.
method Examined cash holdings and stock purchases of Indian equity mutual funds.
result Funds with active liquidity choices outperform, highlighting the importance of this strategy.

New metric to measure liquidity position PNL, delta hedging algorithm for automated market makers.

problem Vulnerability of liquidity positions to price changes in underlying assets.
method Proposes a new metric for measuring PNL, delta hedging algorithm for various AMMs.
result New metric more accurately measures net value change due to price movement.

The study examines when large trades are considered news or liquidity shocks in a market model.

problem Understanding when large trades are news or liquidity shocks in a market model.
method A sequential competitive limit order book model with asymmetric information and Student-t tails for liquidity demand.
result Heavy-tailed liquidity demand flattens and concavifies price impact, delaying price discovery.

Study calculates liquidity costs for delta hedging of European options.

problem Determining expected liquidity costs in delta hedging.
method Derives an integration formula for liquidity costs, including option prices and delta process.
result Expected liquidity costs can be calculated faster than Monte Carlo simulations.

We present a large-scale study of commonality in liquidity and resilience across assets in an ultra high-frequency (millisecond-timestamped) Limit Order Book (LOB) dataset from a pan-European electronic equity trading facility. We first show that extant work in quantifying liquidity commonality through the degree of ex…

2014-06-20abs ↗pdf ↗

We adopt Deep Reinforcement Learning algorithms to design trading strategies for continuous futures contracts. Both discrete and continuous action spaces are considered and volatility scaling is incorporated to create reward functions which scale trade positions based on market volatility. We test our algorithms on the…

2019-11-22abs ↗pdf ↗

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.

Study factors affecting liquidity on decentralized exchanges, introducing new metrics.

problem Understanding and predicting liquidity on decentralized exchanges (DEXs).
method Analyzes platform, blockchain, token pair, and liquidity pool factors; introduces new metrics.
result Identifies how various factors affect liquidity through concentration and total value locked.

Optimal strategy for liquidating portfolios under discrete time intervals.

problem Optimizing liquidation of portfolios with discrete time constraints and impact effects.
method Modeling portfolio liquidation with N risky assets, using VaR for cost measurement, and deriving an optimal liquidation time.
result The optimal liquidation time is only influenced by temporary price impacts, not permanent ones.

Study analyzes impact of concentrated liquidity on trading fees and provider returns.

problem Impact of concentrated liquidity on trading fees and provider returns.
method Comparison of average liquidity provider returns before and after concentrated liquidity introduction; quantification of fundamental strategies performance.
result Concentrated liquidity strategies outperform in certain trading pairs and market conditions.

Study liquidity provision in decentralized exchanges considering risk aversion and replication costs.

problem Economic viability of liquidity provision in decentralized exchanges (DEXs).
method Formulated strategic interactions as a sequential game with risk-averse LP, traders, and arbitrageurs.
result DEX liquidity depth is crucial for risk management, influenced by risk aversion and replication costs.

The effect of leverage on liquidity is a tool for analysing the level of liquidity for a given production process. It measures the sensitivity of the level of liquidity that results from changes in the volume of production and unit operating margin. A commercial activity is liquid at the moment when all costs are cover…

2010-04-05abs ↗pdf ↗