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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 constructs and validates a composite day-classification system for Micro E-Mini Nasdaq 100 futures (MNQ) using three pre-market observable conditions: first-30-minute return magnitude, overnight gap magnitude, and abnormal opening-bar volume relative to a rolling baseline. Using 947 regular trading days of five-minute data from 2021-2025, we find that classifier-positive days exhibit statistically distinct intraday behavior, including directional morning drift followed by systematic late-session reversal. Despite these descriptive characteristics, all tested directional trading strategies fail institutional validation standards after transaction costs and multi-year consistency requirements are applied. The highest-performing configuration achieves T = 1.46 and mean net +7.80 points but fails year-stability criteria. The primary contribution is the validation of the Volatility-Volume-Gap (VVG) classifier as a descriptive regime-identification framework and the documentation of failed attempts to convert these statistical patterns into deployable trading signals under realistic execution constraints.

Suggested Citation

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