What is Del Monte Corporation Ordinary Shares (DMC)'s Q-Score?

StoQuant's Q-Score for DMC is 48.0. The Q-Score is a composite rating from 0–100 that combines DCF valuation, earnings quality, competitive moat, analyst consensus, ML forecasts, and market sentiment.

Is DMC stock undervalued according to StoQuant?

See the full StoQuant analysis to check whether DMC is currently undervalued according to Graham intrinsic value estimates.

What is the DMC stock forecast?

StoQuant's ML model generates a forecast for DMC predicting the probability of outperformance vs. the S&P 500, updated daily. See the detailed forecast page for confidence intervals and named drivers.

Del Monte Corporation Ordinary Shares (DMC) — AI-Powered Stock Analysis & Research

Quantitative analysis for Del Monte Corporation Ordinary Shares (DMC): AI-powered alpha score, Benjamin Graham intrinsic value, ML-based forecast, technical and fundamental signals, and insider activity.

Key Quantitative Facts

At-a-Glance Metrics

Market Cap: $1.48B
Current Price: $31.34
52-Week Range: $27.44 – $42.60
Q-Score Verdict: Hold (48.0) grade C
Signal Coverage: 29 signals (25 alt-data)

Current Q-Score verdict: Hold (48.0) (grade C). 29 signals analyzed (25 differentiated alt-data).

Recent Price Action & History

Trading Data & Technical Analysis

DMC stock price is tracked daily for technical and fundamental analysis. The data below shows recent trading activity used in trend analysis, momentum calculation, and entry/exit signals.

Date	High	Low	Close
2026-05-06	$38.72	$36.69	$37.50
2026-05-18	$33.20	$32.38	$32.72
2026-05-29	$33.10	$31.70	$32.14
2026-06-10	$29.48	$28.85	$29.08
2026-06-23	$27.90	$27.11	$27.86
2026-07-06	$28.21	$27.59	$27.98
2026-07-16	$29.77	$28.98	$29.35
2026-07-28	$29.82	$28.57	$28.73
2026-08-07	$31.32	$30.08	$30.75
2026-08-19	$31.65	$30.59	$31.28
2026-08-31	$31.86	$31.31	$31.68
2026-09-11	$32.09	$31.31	$31.34

Key Analysis Points for Del Monte Corporation Ordinary Shares

What Drove DMC's Score

Del Monte Corporation Ordinary Shares (DMC) scores Hold (48.0), with every measured dimension at or below 58. The weakest are technicals at 9, across 3 measured dimensions. See Q-Score methodology for how these dimensions are weighted and combined.

Q-Score dimensions, normalized 0-100
Dimension	Score
ML forecast	58
competitive moat	47
technicals	9

Signal Diversity

StoQuant analyzes 29 signals (25 alt-data). Alternative data sources (FDA approvals, GitHub activity, SEC filings, App Store ratings) complement traditional financial metrics.

What StoQuant Measures for DMC

Core Signals & Metrics

AI Alpha (Gem) Score: Combines 15+ technical signals (momentum, RSI, moving averages) with fundamentals (earnings surprise, growth consistency) and sentiment. 0–100 scale, residualized by sector so peer-relative strength is visible.
Benjamin Graham Intrinsic Value: DCF-based valuation using conservative earnings assumptions and sector-median discount rates. Margin of safety measures distance from intrinsic value to current price.
Composite Q-Score: Blends DCF upside potential, earnings quality (Piotroski F-Score, Altman Z-Score for distress risk), competitive moat score, analyst consensus, and social/news sentiment into one 0–100 verdict.
ML Price Forecasts: Probability estimates using historical price/volume patterns.
Insider & Institutional Flow: Officer and large shareholder transactions from SEC filings (10-K, Form 4), concentration analysis, and transaction patterns over 14/90-day windows. See insider activity methodology.
Sector & Macro Context: Market regime classification (bull/bear/correction), sector rotation, and portfolio context. Same stock signal reads differently across market environments.

Learn StoQuant's Signals & Scoring

Knowledge Base & Methodology

All StoQuant signals are explained in our knowledge base:

Q-Score Methodology — How StoQuant combines dimensions: DCF, earnings quality, moat, analyst consensus, ML, sentiment
Portfolio Construction — Building balanced portfolios with StoQuant signals
Diversification & Correlation — Cross-sector allocation and risk-adjusted returns

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Platform Overview

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Disclaimer & Methodology

How StoQuant Works

StoQuant research is generated algorithmically using public market data, SEC filings, news feeds, and proprietary ML models. Not investment advice. Past performance does not guarantee future results.

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