Directional Liquidity and Geometric Shear in Pregeometric Order Books

Battle Count: 82

The paper provides a structural/geometric understanding of order book liquidity and bid-ask asymmetry, which is relevant for market microstructure research and order book modeling. However, the author explicitly states the framework does not aim to predict price trajectories or provide trading signals. The shear-drift separation finding (that liquidity imbalance is not a universal price-driving force) is relevant for practitioners who use order book imbalance as a signal. The gamma geometry could inform liquidity modeling in execution algorithms. Overall, it is more foundational/theoretical than directly actionable for quantitative trading strategies.

The theoretical framework (relational substrate, spectral projection, gauge decomposition) is conceptually sophisticated and draws from quantum gravity/statistical physics. However, the empirical implementation is relatively straightforward: computing cumulative liquidity profiles, fitting integrated-gamma vs. alternatives via AIC, and computing Spearman correlations. The main complexity lies in understanding the pregeometric conceptual framework rather than in coding the empirical tests. No specialized ML infrastructure is required.

The paper uses publicly accessible Level II data from Interactive Brokers via NASDAQ TotalView/OpenView feed. The methodology is fully described with explicit equations and parameters (K=50 ticks, ΔT=10s windows). However, no code repository is provided, and the pregeometric framework is primarily conceptual. The empirical validation is straightforward (cumulative liquidity fitting, AIC comparison, Spearman correlation), making reproduction feasible but requiring commercial data access.