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A Validated Volatility-Volume-Gap Classifier for Regime Identification in MNQ Intraday Data

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  • Mathias Mesfin

Abstract

This paper builds and tests a day-classification system for MNQ (Micro E-Mini Nasdaq 100) futures based on three simultaneously elevated pre-market conditions: absolute overnight gap, absolute first-30-minute return, and first-bar volume relative to a 20-day rolling baseline. The Volatility-Volume-Gap (VVG) classifier is evaluated on 947 trading days of five-minute data from 2021-2025, with all thresholds computed on an expanding window to prevent lookahead bias. The classifier activates on roughly 4.4% of sessions (40 days). Those days exhibit measurably distinct behavior: 77.6% reverse from their intraday peak before the close, mean peak-to-close giveback of 11.73 points, and a 25.6 basis point next-day return spread versus non-classifier days. Year-by-year analysis reveals substantial path heterogeneity -- 2024 classifier days closed at mean +40.74 points while 2025 crashed to -42.48 -- which is the core obstacle for any directional strategy. Eight directional configurations were tested. None passed. Best result: T = 1.46, mean net +7.80 points, 127 OOS trades, reversal entry with OLS regression filter. 2024 broke year stability. Binding constraints are the 40-day sample (roughly 10 per year) and regime-dependent intraday behavior that no fixed rule survives across all test years. The classifier is preserved as a research asset: it identifies a real behavioral phenomenon but cannot generate a deployable directional signal under current constraints.

Suggested Citation

  • Mathias Mesfin, 2026. "A Validated Volatility-Volume-Gap Classifier for Regime Identification in MNQ Intraday Data," Papers 2605.11423, arXiv.org, revised Sep 2026.
    • Handle: RePEc:arx:papers:2605.11423
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