Paper: arXiv 2603.24137

Authors: Patrick Noble, Mathieu Rosenbaum, Saad Souilmi

Abstract

We introduce a practical, interactive simulator of the limit order book for large-tick assets, designed to produce realistic execution, costs, and P&L. The book state is projected onto a tractable representation based on spread and volume imbalance, enabling robust estimation from market data. Event timing is calibrated to reproduce the fine-scale temporal structure of real markets, revealing a pronounced mode at exchange round-trip latency consistent with simultaneous reactions and latency races among participants. We further incorporate a feedback mechanism that accumulates signed trade flow through a power-law decay kernel, reproducing both concave market impact during execution and partial post-trade reversion. Across several stocks and strategy case studies, the simulator yields realistic behavior where profitability becomes highly sensitive to execution parameters. We present the approach as a practical recipe: project, estimate, validate, adapt, for building realistic limit order book simulations.

Complexity vs Empirical Score

  • Math Complexity: 5.5/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: This paper presents a highly practical, state-of-the-art Limit Order Book (LOB) simulator tailored for large-tick assets, addressing critical real-world friction like latency races and power-law decay market impact. Its empirical validation across multiple stocks and execution strategy case studies provides strong quantitative support, making it an exceptional contribution to market microstructure literature.

Research Flowchart

  flowchart TD
    A[Goal: Realistic LOB Simulation for Large-Tick Assets] --> B[Data Inputs: LOB Level 1 & 2 Market Data]
    B --> C[Project LOB State onto Spread & Volume Imbalance]
    C --> D[Calibrate Event Timing & Latency Race Dynamics]
    D --> E[Incorporate Feedback Kernel for Market Impact & Reversion]
    E --> F[Validation & Strategy Case Studies]
    F --> G[Outcome: Accurate Execution Costs & Latency-Sensitive P&L]

Cited References (16)

  1. A unified theory of order flow, market impact, and volatility — → 2601.23172
  2. A Novel Approach to Queue-Reactive Models: The Importance of Order Sizes — → 2405.18594
  3. The two square root laws of market impact and the role of sophisticated market participants — → 2311.18283
  4. Understanding the worst-kept secret of high-frequency trading — → 2307.15599
  5. Quantifying the High-Frequency Trading “Arms Race” (2021) — link
  6. The micro-price: a high-frequency estimator of future prices (2018) — link
  7. No‐arbitrage implies power‐law market impact and rough volatility (2018) — link
  8. Ergodicity and Diffusivity of Markovian Order Book Models: A General Framework (2015) — link
and 8 more
  1. Simulating and Analyzing Order Book Data: The Queue-Reactive Model (2013) — link
  2. Anomalous price impact and the critical nature of liquidity in financial markets (2011) — link
  3. Price Dynamics in a Markovian Limit Order Market (2011) — link
  4. The Price Impact of Order Book Events (2010) — link
  5. How Markets Slowly Digest Changes in Supply and Demand (2008) — link
  6. Statistical theory of the continuous double auction (2002) — link
  7. Without self-impact: the impact mechanism is active (other participants’ trades move prices via ϕ t ), but the strategy’s own fills are excluded, i.e. we set ε k = 0 for the strategy’s trades in
  8. 1.0 0.5 0.0 0.5 1.0 Imb Very low 0.0 0.2 0.4 0.6 0.8 1.0 Imb Very low Figure 22: Left: Observation count per imbalance bin, stratified by total queue level ℓ (PFE, n = 1 )

4 of 16 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.