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Sewha P&C INC. (252500) Fair Value & Analysis

Consumer Defensive · KR · Market cap 28.8B KRW

Price578.00 KRW
Fair Value567.56 KRW
Upside-1.8%
Quality95/100
Evidence: High Range 439.22 KRW – 695.90 KRW

Fair value as of: Jun 24, 2026

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Analysis

Sewha P&C INC. (252500) currently trades at 578.00 KRW, while our model-based Fair Value estimate is 567.56 KRW — implying the stock looks roughly 1.8% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Defensive 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

Sewha P&C INC. engages in the development, production, and sale of hair dyes, hair care products, and cosmetics in South Korea. It also exports its products to approximately fifty countries. The company was founded in 1976 and is headquartered in Jincheon-eup, South Korea.

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Frequently asked questions

Is Sewha P&C INC. (252500) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 567.56 KRW versus a price of 578.00 KRW — about −2% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 252500?
Our 21-model fair value for Sewha P&C INC. is 567.56 KRW (as of Jun 24, 2026), built from audited fundamentals. The current price is 578.00 KRW.
What is the quality score of 252500?
Sewha P&C INC. 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.