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SC Cemacon SA (CEON) Fair Value & Analysis

Basic Materials · RO · Market cap 407M RON

Price0.4350 RON
Fair Value0.4200 RON
Upside-3.4%
Quality79/100
Evidence: Medium Range 0.3000 RON – 0.5500 RON

Fair value as of: Jun 24, 2026

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Analysis

SC Cemacon SA (CEON) currently trades at 0.4350 RON, while our model-based Fair Value estimate is 0.4200 RON — implying the stock looks roughly 3.4% overvalued today. We read business quality at 79/100 (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: medium).

About the company

SC Cemacon SA, together with its subsidiaries, manufactures and sells fired clay bricks, tiles and other construction products. The company was founded in 1969 and is headquartered in Cluj-Napoca, Romania. SC Cemacon SA is a subsidiary of Dedeman S.R.L.

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Frequently asked questions

Is SC Cemacon SA (CEON) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 0.4200 RON versus a price of 0.4350 RON — about −3% (overvalued). Model-based estimate, not financial advice.
What is the fair value of CEON?
Our 21-model fair value for SC Cemacon SA is 0.4200 RON (as of Jun 24, 2026), built from audited fundamentals. The current price is 0.4350 RON.
What is the quality score of CEON?
SC Cemacon SA has a Quality Score of 79/100, 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.