Evaluating the Predictive Validity of ICT's Accumulation-Manipulation-Distribution (AMD) Model on CME E-Mini NASDAQ-100 Futures
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.
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BibTeX
@misc{taylor2026evaluating,
title = {{Evaluating the Predictive Validity of ICT's Accumulation-Manipulation-Distribution (AMD) Model on CME E-Mini NASDAQ-100 Futures}},
author = {Veer Taylor},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.35887},
eprint = {2610.35887},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.35887},
}
RIS
TY - UNPB
TI - Evaluating the Predictive Validity of ICT's Accumulation-Manipulation-Distribution (AMD) Model on CME E-Mini NASDAQ-100 Futures
AU - Veer Taylor
PY - 2026
DA - 2026/10/01
PB - arXiv
DO - 10.48550/arxiv.2610.35887
UR - https://arxiv.org/abs/2610.35887
AB - 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.
ER -