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3-D Matrix, Ltd (DMTRF) Fair Value & Analysis

Healthcare · US · Market cap $270M

Price$2.25
Fair Value$1.57
Upside-30.2%
Quality97/100
Evidence: High Range $1.18 – $2.03

Fair value as of: Jun 24, 2026

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Analysis

3-D Matrix, Ltd (DMTRF) currently trades at $2.25, while our model-based Fair Value estimate is $1.57 — implying the stock looks roughly 30.2% overvalued today. We read business quality at 97/100 (high quality), in the Healthcare sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).

About the company

3-D Matrix, Ltd. developing, manufacturing, and selling self-assembling peptide technology in Japan and internationally. It offers PuraMatrix, a self-assembling peptide hydrogel for use in the regenerative medicine, cell therapy, drug delivery systems, and other uses in various fields. The company was incorporated in 2004 and is based in Tokyo, Japan

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Frequently asked questions

Is 3-D Matrix, Ltd (DMTRF) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $1.57 versus a price of $2.25 — about −30% (overvalued). Model-based estimate, not financial advice.
What is the fair value of DMTRF?
Our 21-model fair value for 3-D Matrix, Ltd is $1.57 (as of Jun 24, 2026), built from audited fundamentals. The current price is $2.25.
What is the quality score of DMTRF?
3-D Matrix, Ltd has a Quality Score of 97/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

How we calculate Fair Value

Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.

Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.