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Namhwa Industrial Co (111710) Fair Value & Analysis

Consumer Cyclical · KR · Market cap 70.9B KRW

Price4,775 KRW
Fair Value4,373 KRW
Upside-8.4%
Quality95/100
Evidence: High Range 3,478 KRW – 5,268 KRW

Fair value as of: Jun 24, 2026

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Analysis

Namhwa Industrial Co (111710) currently trades at 4,775 KRW, while our model-based Fair Value estimate is 4,373 KRW — implying the stock looks roughly 8.4% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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

Namhwa Industrial Co., Ltd. engages in the operation of golf course in South Korea. It operates a 54-hole public golf course. Namhwa Industrial Co., Ltd. was founded in 1990 and is headquartered in Muan-eup, South Korea.

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Frequently asked questions

Is Namhwa Industrial Co (111710) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 4,373 KRW versus a price of 4,775 KRW — about −8% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 111710?
Our 21-model fair value for Namhwa Industrial Co is 4,373 KRW (as of Jun 24, 2026), built from audited fundamentals. The current price is 4,775 KRW.
What is the quality score of 111710?
Namhwa Industrial 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.