Nature & Environment Co (043910) Fair Value & Analysis
Consumer Cyclical · KR · Market cap 35.0B KRW
Fair value as of: Jun 24, 2026
Analysis
Nature & Environment Co (043910) currently trades at 2,955 KRW, while our model-based Fair Value estimate is 10,976 KRW — implying the stock looks roughly 271.4% undervalued today. We read business quality at 90/100 (high quality), in the Consumer Cyclical 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: low) — always confirm before acting.
About the company
Nature & Environment Co.,Ltd. engages in the precast concrete, greening construction, and landscaping businesses in South Korea and internationally. The company is also engaged in ecological restoration, soil and groundwater remediation, soil environment assessment, landscaping, rainwater storage tank, environmental plant, green-tech construction, and other businesses. In addition, it provides water treatment, recycling, and civil work services; and environmental-friendly materials, air purification systems, and PC modulars. Further, the company offers afforestation, gardening, and environmental restoration product manufacturing services. Nature & Environment Co.,Ltd. was founded in 1991 and is headquartered in Gongju, South Korea.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is Nature & Environment Co (043910) undervalued?
What is the fair value of 043910?
What is the quality score of 043910?
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.