Daebongls.Co.,Ltd. (078140) Fair Value & Analysis
Healthcare · KR · Market cap 94.9B KRW
Fair value as of: Jun 24, 2026
Analysis
Daebongls.Co.,Ltd. (078140) currently trades at 7,310 KRW, while our model-based Fair Value estimate is 13,809 KRW — implying the stock looks roughly 88.9% undervalued today. We read business quality at 80/100 (high quality), in the Healthcare 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
Daebongls.Co.,Ltd. engages in the research, development, and production of cosmetics, pharmaceutical raw materials, food and feed products in South Korea and internationally. The company's Cosmetic Ingredients division offers special cosmetic ingredients comprising fresh green tea, black ginseng water, jeju hatban extract, wormwood extract, jeju camellia oil, jeju dang oil extract, jeju basalt powder, jeju active complex, and ginseng flower extract; and natural and synthesis cosmetics like moisturizing, skin protection, whitening, anti- aging, skin care, and hair care products. The company's Pharmaceutical Raw Material division develops the API of respiratory, hypertension, digestive-system treatments, and medicines and supply excipients to domestic companies as an agent for global companies. The company's Food & Feed division manufactures and distributes functional additives, protein products, amino acids, and vitamins. Daebongls.Co.,Ltd. was founded in 1986 and is headquartered in…
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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.