Lihe Technology (Hunan) Co (300800) Fair Value & Analysis
Industrials · CN · Market cap 2.4B CNY
Fair value as of: Jun 24, 2026
Analysis
Lihe Technology (Hunan) Co (300800) currently trades at ¥9.91, while our model-based Fair Value estimate is ¥5.11 — implying the stock looks roughly 48.4% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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
Lihe Technology (Hunan) Co., Ltd. engages in the research and development, production, and sales of environmental monitoring systems in China. The company provides water quality monitoring systems, air/flue gas monitoring systems, and environmental monitoring information management systems; and environmental monitoring system operation services, third-party testing, and monitoring consulting services. Its products are used in environmental monitoring of ecological environment, water conservancy, municipal, and other government departments, as well as institutions and pollution source enterprises supervised by environmental protection departments. Lihe Technology (Hunan) Co., Ltd. was founded in 1997 and is based in Changsha, China.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is Lihe Technology (Hunan) Co (300800) undervalued?
What is the fair value of 300800?
What is the quality score of 300800?
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.