A Gabor–Epps uncertainty principle for traders

Battle Count: 71

Directly addresses a fundamental practical problem in high-frequency and market-making trading: when is a cross-asset correlation signal mature enough to trade? The paper provides a clear theoretical framework connecting signal-processing resolution limits to the Epps effect, with six actionable rules of thumb. Highly relevant for algorithmic trading desks operating below human response times, pairs trading strategies, and risk management. The clock-dependence insight (calendar vs. trade vs. volume time) is practically important for execution and accounting. However, it remains a conceptual framework requiring empirical calibration before direct implementation.

The conceptual framework is relatively straightforward (Fourier uncertainty + Epps attenuation curves). However, practical implementation requires: (1) estimating shared-refresh rates λ, coupling-response rates κ, and imbalance-reversal frequencies ω from tick data; (2) choosing and maintaining multiple market clocks; (3) computing spectral estimates of order-flow imbalance; (4) implementing the reaction-diffusion order-book model for local response rates. The mathematical content is accessible to those with signal-processing background, but the data engineering for rate estimation is non-trivial.

The paper provides stylized dimensional examples (Tables 1 and 2) but explicitly states these are not calibrated empirical estimates. No code, data, or empirical validation is provided. The framework is conceptual and requires desk-specific estimates of λ, κ, and ω rates to be operationalized. The mathematical derivations are self-contained but the practical implementation requires proprietary market data and rate estimation.