arXiv (All)
open access
LOB-Impact Benchmark: Emergent Market Impact in Generative Limit Order Book Models
Realistic market impact is essential for generative limit order book (LOB) models to serve as world models for trading agents. If a simulator misprices this mechanism, agents learn policies that are optimal in the simulator but wrong in the real market. Existing metrics assess generated streams pure
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Repurposing Deep Limit Order Book Forecasting for Scenario-Conditioned Market Impact Modeling#1123341
- Repurposing Deep Limit Order Book Forecasting for Scenario-Conditioned Market Impact Modeling#919420
- Probabilistic Limit Order Book Forecasting with Conditional Diffusion Models#1400321
- Why Risk it, When You Can {rix} it: A Tutorial for Computational Reproducibility Focused on Simulation Studies#348858
- StochLOB: Heavy-Tailed Score Matching for Robust Limit Order Book Trend Prediction#1356417
Record · ID 1402488
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive