# Early Detection of Latent Microstructure Regimes in Limit Order Books

arXiv: https://arxiv.org/abs/2604.20949 · HTML: https://mlsanity.com/paper/2604.20949/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 14 references that are in the map.
- First posted on arXiv 22 Apr 2026.

## Built on by (most cited first, 1 of 1)

- [When Does Order Flow Matter? State-Dependent L2 Liquidity-State Transitions in Crypto Futures](https://mlsanity.com/paper/2607.09230/) (2026)

## Abstract (arXiv)

Limit order books can transition rapidly from stable to stressed conditions, yet standard early-warning signals such as order flow imbalance and short-term volatility are inherently reactive. We formalise this limitation via a three-regime causal data-generating process (stable → latent build-up → stress) in which a latent deterioration phase creates a prediction window prior to observable stress. Under mild assumptions on temporal drift and regime persistence, we establish identifiability of the latent build-up regime and derive guarantees for strictly positive expected lead-time and non-trivial probability of early detection. We propose a trigger-based detector combining MAX aggregation of complementary signal channels, a rising-edge condition, and adaptive thresholding. Across 200 simulations, the method achieves mean lead-time +18.6 ± 3.2 timesteps with perfect precision and moderate coverage, outperforming classical change-point and microstructure baselines. A preliminary application to one week of BTC/USDT order book data shows consistent positive lead-times while baselines remain reactive. Results degrade in low signal-to-noise and short build-up regimes, consistent with theory.