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CleanTech Lithium Plc (CTLHF) Fair Value & Analysis

Basic Materials · US · Market cap $129M

Price$0.4200
Fair Value$0.2500
Upside-40.5%
Quality95/100
Evidence: Low Range $0.1900 – $0.3100

Fair value as of: Jun 24, 2026

Analysis

CleanTech Lithium Plc (CTLHF) currently trades at $0.4200, while our model-based Fair Value estimate is $0.2500 — implying the stock looks roughly 40.5% overvalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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

CleanTech Lithium Plc engages in the exploration, development, and production of lithium in Chile. The company's flagship project is Laguna Verde Project that comprises 127 licenses covering an area of approximately 217 square kilometers located in Chile. CleanTech Lithium Plc was founded in 2017 and is based in Saint Helier, Jersey.

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Frequently asked questions

Is CleanTech Lithium Plc (CTLHF) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $0.2500 versus a price of $0.4200 — about −40% (overvalued). Model-based estimate, not financial advice.
What is the fair value of CTLHF?
Our 21-model fair value for CleanTech Lithium Plc is $0.2500 (as of Jun 24, 2026), built from audited fundamentals. The current price is $0.4200.
What is the quality score of CTLHF?
CleanTech Lithium Plc has a Quality Score of 95/100, 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.