YCIC Eco-Technology Co (002200) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 85.3B KRW
Fair value as of: Jun 25, 2026
Analysis
YCIC Eco-Technology Co (002200) currently trades at 2,365 KRW, while our model-based Fair Value estimate is 2,168 KRW — implying the stock looks roughly 8.3% 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: medium).
About the company
YCIC Eco-Technology Co.,Ltd., together with its subsidiaries, engages in ecological landscape, ecological and environmental protection, and flower and eco-friendly businesses in China. The company offers landscaping, cultural tourism, water pollution treatment, and engineering construction services. In addition, it provides environmental consulting services comprising environmental planning, environmental investigation and assessment, project planning, engineering feasibility studies, and engineering design for solid waste and water pollution; soil remediation, heavy metal treatment, and waste disposal services; and sewage treatment and watershed management services, as well as agricultural products, such as flowers. The company was formerly known as Yunnan Yuntou Ecology and Environment Technology Co.,Ltd. and changed its name to YCIC Eco-Technology Co.,Ltd. in July 2022. YCIC Eco-Technology Co.,Ltd. was incorporated in 1996 and is headquartered in Kunming, the People's Republic of…
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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.