Paper: arXiv 2610.35887

Authors: Veer Taylor

Abstract

To our knowledge, this paper provides the first systematic quantitative evaluation of the ICT Accumulation-Manipulation-Distribution (AMD) model on CME E-Mini NASDAQ-100 futures (NQ). The AMD model proposes that institutional participants structure intraday price delivery in three phases: overnight accumulation in the Asian session, a deliberate false breakout during London, and directional delivery to the opposing liquidity pool during the New York morning session. Using four years of real 15-minute OHLCV data from Databento (January 2022 to July 2026), we operationalize the AMD rules into a strict mechanical strategy and analyze the statistical properties of the resulting signal across N = 484 manipulation signal days using chi-square testing, Benjamini-Hochberg multiple comparisons correction, and regime-conditional analysis. Three principal findings emerge. First, the AMD manipulation signal fires on 44% of trading days. Second, 57% of valid signals see full target delivery before the 9:40 AM New York entry window opens, revealing a structural mismatch between the model’s timing assumptions and actual price delivery. Third, within this operationalization of the AMD model, no directional information beyond the daily trend regime was observed: when the signal aligns with the trend it is correct 62-71% of the time (Cohen’s h = 0.23-0.43); when it opposes the trend it is correct only 25-30% of the time (Cohen’s h = 0.42-0.53). All four trending-regime cells survive Benjamini-Hochberg correction. Key findings are robust to variation in the manipulation breach threshold (5-20 NQ points), Asia range filter percentile, and stop buffer. The regime-dependent signal pattern constitutes a specific, testable hypothesis for follow-on research.

Complexity vs Empirical Score

  • Math Complexity: 5.0/10
  • Empirical Rigor: 9.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: This paper demonstrates strong empirical rigor through its systematic backtesting, robust statistical analysis, and sensitivity testing. The novelty lies in being the first rigorous quantitative evaluation of a widely adopted retail trading model, addressing a significant gap in academic literature.

Research Flowchart

  flowchart TD
    A[Research Goal: Evaluate Predictive Validity of ICT AMD Model on NQ Futures] --> B{Key Methodology: Operationalize AMD into Mechanical Strategy};
    B --> C[Data/Inputs: 4 Years NQ 15-min OHLCV (Jan 2022 - Jul 2026)];
    C --> D{Computational Processes: Chi-square Test, Benjamini-Hochberg, Regime-Conditional Analysis};
    D --> E[Finding 1: AMD Signal Fires on 44% of Days];
    D --> F[Finding 2: 57% Signals See Target Delivery Before NY Entry Window];
    D --> G[Finding 3: No Directional Info Beyond Daily Trend; Signal Correct 62-71% with Trend, 25-30% Against Trend (Regime-Dependent)];
    E & F & G --> H[Outcome: Specific, Testable Hypothesis for Follow-on Research];