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CHAR Technologies Ltd (CTRNF) Fair Value & Analysis

Industrials · US · Market cap $30.1M

Price$0.2000
Fair Value$0.1000
Upside-50.0%
Quality89/100
Evidence: Low Range $0.0800 – $0.1300

Fair value as of: Jun 24, 2026

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Analysis

CHAR Technologies Ltd (CTRNF) currently trades at $0.2000, while our model-based Fair Value estimate is $0.1000 — implying the stock looks roughly 50.0% overvalued today. We read business quality at 89/100 (high quality), in the Industrials 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: low).

About the company

CHAR Technologies Ltd. engages in converting woody materials and organic waste into renewable gases and biocarbon. It offers renewable natural gas and green hydrogen; SulfaCHAR, an activated charcoal; and CleanFyre, a biochar product. CHAR Technologies Ltd. is headquartered in Toronto, Canada.

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Frequently asked questions

Is CHAR Technologies Ltd (CTRNF) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $0.1000 versus a price of $0.2000 — about −50% (overvalued). Model-based estimate, not financial advice.
What is the fair value of CTRNF?
Our 21-model fair value for CHAR Technologies Ltd is $0.1000 (as of Jun 24, 2026), built from audited fundamentals. The current price is $0.2000.
What is the quality score of CTRNF?
CHAR Technologies Ltd has a Quality Score of 89/100, 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.