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Results for “adverse selection” · papers 18 · wiki 1
Academic Papers · 18arXiv q-fin live 0 · desk corpus 138
arXiv · arXiv · 2026

Mitigating Adverse Selection in Concentrated Liquidity AMMs with Dynamic Fees: An Agent-Based Model Approach

Automated Market Makers based on concentrated liquidity, such as Uniswap v3, significantly improve capital efficiency but expose Liquidity Providers (LPs) to adverse selection costs, formalized as Loss-Versus-Rebalancing (LVR). While theoretical literature quantifies these costs, the interplay between realistic blockchain microstructure and endogenous pricing mechanisms remains under-explored. This paper develops a g

Daniele Maria Di Nosse, Fabrizio Lillo
arXiv · arXiv · 2026

Trading in the Sunshine or in the Shade: Market Impact and Adverse Selection on Hyperliquid

Sunshine trading theory predicts that publicly disclosing trading intentions can reduce adverse selection and attract liquidity provision, lowering execution costs. Evidence is scarce, because explicit preannouncement of large orders is rare in traditional markets. We study Hyperliquid, a fully on-chain limit order book for cryptocurrency perpetual futures, where protocol-native TWAP orders disclose their terms from

Davide Barone, Fabrizio Lillo
arXiv · arXiv · 2026

Market Informedness and Market-Maker Profitability: The Trade-Off Between Adverse Selection and Price Discovery

This paper studies how market informedness affects market makers' profitability in a computational market environment with heterogeneous learning agents. We develop an agent-based market model in which market makers differ in their information sets and inventory-risk aversion, prices form endogenously, fundamental values evolve exogenously, and market-taker order flow follows a state-dependent self-exciting process.

Konrad Ochędzan, Nino Antulov-Fantulin
arXiv · arXiv · 2025

When AI Trading Agents Compete: Adverse Selection of Meta-Orders by Reinforcement Learning-Based Market Making

We investigate the mechanisms by which medium-frequency trading agents are adversely selected by opportunistic high-frequency traders. We use reinforcement learning (RL) within a Hawkes Limit Order Book (LOB) model in order to replicate the behaviours of high-frequency market makers. In contrast to the classical models with exogenous price impact assumptions, the Hawkes model accounts for endogenous price impact and

Ali Raza Jafree, Konark Jain, Nick Firoozye
arXiv · arXiv · 2024

Market Simulation under Adverse Selection

In this paper, we study the effects of fill probabilities and adverse fills on the trading strategy simulation process. We specifically focus on a stochastic optimal control market-making problem and test the strategy on ES (E-mini S\&P 500), NQ (E-mini Nasdaq 100), CL (Crude Oil) and ZN (10-Year Treasury Note), which are some of the most liquid futures contracts listed on the CME (Chicago Mercantile Exchange). We pr

Luca Lalor, Anatoliy Swishchuk
arXiv · arXiv · 2026

Public Trader Identity: Adverse Selection and Return Predictability

Informed traders are supposed to need anonymity: they profit by hiding among the uninformed. A decentralized exchange now publishes the counterparty. Every committed order, cancellation, rejection, and fill carries a persistent pseudonymous wallet address. We reconstruct the full-depth limit order book from a record of 17.1 billion messages and 14.3 million aggressive orders by 147,113 wallets, covering $84.3 billion

Daojing Zhai
arXiv · arXiv · 2026

Quality-Adjusted Hit-Ratio Targeting in Corporate Bond Market Making

Hit ratio is a common service metric for electronic corporate bond market making, but raw hit-ratio targets can be economically misleading when client flow has heterogeneous adverse-selection content. This paper extends a stochastic-control framework for OTC bond RFQ market making with hit-ratio constraints by replacing raw hit ratio with a residual-quality-adjusted hit ratio. The key modelling distinction is that ad

Bouna Niang
arXiv · arXiv · 2025

Equilibrium Liquidity and Risk Offsetting in Decentralised Markets

We study the economic viability of liquidity provision in decentralised exchanges (DEXs) within a structural framework in which market outcomes are endogenous. We formulate strategic interactions as a sequential game: a risk-averse liquidity provider (LP) sets the supply of liquidity in the DEX and a costly dynamic replication strategy in a centralised exchange (CEX), price-sensitive traders determine trading volumes

Fayçal Drissi, Xuchen Wu, Sebastian Jaimungal
arXiv · arXiv · 2025

Optimal Fees for Liquidity Provision in Automated Market Makers

Passive liquidity providers (LPs) in automated market makers (AMMs) face losses due to adverse selection (LVR), which static trading fees often fail to offset in practice. We study the key determinants of LP profitability in a dynamic reduced-form model where an AMM operates in parallel with a centralized exchange (CEX), traders route their orders optimally to the venue offering the better price, and arbitrageurs exp

Steven Campbell, Philippe Bergault, Jason Milionis, Marcel Nutz
arXiv · arXiv · 2025

Liquidity Competition Between Brokers and an Informed Trader

We study a multi-agent setting in which brokers transact with an informed trader. Through a sequential Stackelberg-type game, brokers manage trading costs and adverse selection with an informed trader. In particular, supplying liquidity to the informed traders allows the brokers to speculate based on the flow information. They simultaneously attempt to minimize inventory risk and trading costs with the lit market bas

Ryan Donnelly, Zi Li
arXiv · arXiv · 2023

The Paradox Of Just-in-Time Liquidity in Decentralized Exchanges: More Providers Can Sometimes Mean Less Liquidity

We study Just-in-time (JIT) liquidity provision in blockchain-based decentralized exchanges. A JIT liquidity provider (LP) monitors pending swap orders in public mempools of blockchains to sandwich orders of their choice with liquidity, depositing right before and withdrawing right after the order. Our game-theoretic model with asymmetrically informed agents reveals that a JIT LP's presence does not always enhance li

Agostino Capponi, Ruizhe Jia, Brian Zhu
arXiv · arXiv · 2023

Fragmentation and optimal liquidity supply on decentralized exchanges

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, accep

Alfred Lehar, Christine Parlour, Marius Zoican
arXiv · arXiv · 2023

Blockchain scaling and liquidity concentration on decentralized exchanges

Liquidity providers (LPs) on decentralized exchanges (DEXs) can protect themselves from adverse selection risk by updating their positions more frequently. However, repositioning is costly, because LPs have to pay gas fees for each update. We analyze the causal relation between repositioning and liquidity concentration around the market price, using the entry of blockchain scaling solutions, Arbitrum and Polygon, as

Basile Caparros, Amit Chaudhary, Olga Klein
arXiv · arXiv · 2023

FLAIR: A Metric for Liquidity Provider Competitiveness in Automated Market Makers

This paper aims to enhance the understanding of liquidity provider (LP) returns in automated market makers (AMMs). LPs face market risk as well as adverse selection due to risky asset holdings in the pool that they provide liquidity to and the informational asymmetry between informed traders (arbitrageurs) and AMMs. Loss-versus-rebalancing (LVR) quantifies the adverse selection cost (Milionis et al., 2022a), and is a

Jason Milionis, Xin Wan, Austin Adams
arXiv · arXiv · 2023

A Myersonian Framework for Optimal Liquidity Provision in Automated Market Makers

In decentralized finance ("DeFi"), automated market makers (AMMs) enable traders to programmatically exchange one asset for another. Such trades are enabled by the assets deposited by liquidity providers (LPs). The goal of this paper is to characterize and interpret the optimal (i.e., profit-maximizing) strategy of a monopolist liquidity provider, as a function of that LP's beliefs about asset prices and trader behav

Jason Milionis, Ciamac C. Moallemi, Tim Roughgarden
arXiv · arXiv · 2015

Liquidity Effects of Trading Frequency

In this article, we present a discrete time modeling framework, in which the shape and dynamics of a Limit Order Book (LOB) arise endogenously from an equilibrium between multiple market participants (agents). We use the proposed modeling framework to analyze the effects of trading frequency on market liquidity in a very general setting. In particular, we demonstrate the dual effect of high trading frequency. On the

Roman Gayduk, Sergey Nadtochiy
arXiv · arXiv · 2026

Optimal Execution with Passive Market Impact

We derive a mesoscopic model for optimal execution with limit orders that incorporates microstructural features of passive price impact. Our framework is based on two empirical observables: the approximately exponential decay of limit-order fill probabilities with distance from the midprice, and the short-term linear response of price changes to order flow imbalance. Combining these ingredients, we obtain a reduced-f

Alexander Barzykin, Robert Boyce, Eyal Neuman, Sturmius Tuschmann
arXiv · arXiv · 2026

The Viability of Blockchain Markets under Discrete Clearing and Paid Priority

This paper develops a model to evaluate the viability of blockchain markets as the sole venue for price formation. Blockchains clear at discrete intervals called block time, and transactions are executed sequentially according to priority fees paid by traders who compete for queue position. We show that these features undermine the viability of markets. Paid-priority ordering induces endogenous selection, where only

Agostino Capponi, Álvaro Cartea, Fayçal Drissi
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