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SBSUNGBO Co (003080) Fair Value & Analysis

Basic Materials · KR · Market cap 43.7B KRW

Price2,110 KRW
Fair Value2,025 KRW
Upside-4.0%
Quality95/100
Evidence: Medium Range 1,502 KRW – 2,657 KRW

Fair value as of: Jun 25, 2026

Analysis

SBSUNGBO Co (003080) currently trades at 2,110 KRW, while our model-based Fair Value estimate is 2,025 KRW — implying the stock looks roughly 4.0% 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: medium).

About the company

SBSUNGBO Co., Ltd. provides crop protection products for the agricultural industry in South Korea. The company was formerly known as Sung Bo Chemicals Co., LTD and changed its name to SBSUNGBO Co., Ltd. in April 2025. SBSUNGBO Co., Ltd. was founded in 1961 and is headquartered in Seoul, South Korea.

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Frequently asked questions

Is SBSUNGBO Co (003080) undervalued?
As of Jun 25, 2026, our model estimates a fair value of 2,025 KRW versus a price of 2,110 KRW — about −4% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 003080?
Our 21-model fair value for SBSUNGBO Co is 2,025 KRW (as of Jun 25, 2026), built from audited fundamentals. The current price is 2,110 KRW.
What is the quality score of 003080?
SBSUNGBO 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.