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Nuvotec Co (060260) Fair Value & Analysis

Industrials · KR · Market cap 18.4B KRW

Price1,370 KRW
Fair Value1,520 KRW
Upside+10.9%
Quality95/100
Evidence: Medium Range 1,064 KRW – 1,976 KRW

Fair value as of: Jun 24, 2026

Analysis

Nuvotec Co (060260) currently trades at 1,370 KRW, while our model-based Fair Value estimate is 1,520 KRW — implying the stock looks roughly 10.9% undervalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: medium) — always confirm before acting.

About the company

Nuvotec Co. Ltd. manufactures and sells piping materials in South Korea. The company offers water and sewage pipe and repair; waste recycling; and eco-friendly snow removal business. Nuvotec Co. Ltd. was founded in 1990 and is based in Wonju-si, South Korea.

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Frequently asked questions

Is Nuvotec Co (060260) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 1,520 KRW versus a price of 1,370 KRW — about +11% (undervalued). Model-based estimate, not financial advice.
What is the fair value of 060260?
Our 21-model fair value for Nuvotec Co is 1,520 KRW (as of Jun 24, 2026), built from audited fundamentals. The current price is 1,370 KRW.
What is the quality score of 060260?
Nuvotec Co 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.