MGPraxis42,984 papers mapped

Robust Market Making: To Quote, or not To Quote

Ziyi Wang, Carmine Ventre, Maria Polukarov·2025

Market making, studied by Wang, Ventre and Polukarov in 2025 with reinforcement learning. The abstract mentions a Sharpe ratio and profits but not a benchmark, an out-of-sample test, transaction costs, multiple testing or the size of the universe.

“We demonstrate how occasional refusal to provide bid-ask quotes improves returns and/or Sharpe ratios.”

StrategyMarket makingliquidity premium
TechniqueReinforcement learning
ClaimSharpe ratioprofit

Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe

Institutional-grade audit of this strategy.
£5 — Request the audit
  • Audit of the paper claims accounting for costs, luck, crises, originality, geography, etc.
  • Reproduction code integratable into Bloomberg, IBKR, etc.
  • Bias-free datasets for backtesting included
  • Delivered in 2 working days
The paper's neighbourhoodMarket making by year
■ volatility and options■ crypto■ equities■ other assets201032015220204This paper2025■ volatility and options■ crypto■ equities■ other assets201032015220204This paper2025
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
Similar paperscitationsame methodsame assetsame authors
Chapter 3: AI in Trading & Market Making by Gandhi2026
Option Pricing on Automated Market Maker Tokens by Maymin2026
Deep Reputation Scoring in DeFi: zScore-Based Wallet Ranking from Liquidity and Trading Signals by Kandaswamy et al.2025
Implicit Numerical Scheme for the Hamilton-Jacobi-Bellman Quasi-Variational Inequality in the Optimal Market-Making Problem with Alpha Signal by Meteykin2025
Quantum and Classical Machine Learning in Decentralized Finance: Comparative Evidence from Multi-Asset Backtesting of Automated Market Makers by Chen and Tsai2025
Not yet audited by MarketGraphs Praxis. Tags from the abstract. Counts from the universe.
RSS · Contacts