Infore Environment Technology Group (000967) Fair Value & Analysis
Industrials · CN · Market cap 34.7B CNY
Analysis
Infore Environment Technology Group (000967) currently trades at ¥10.45, while our model-based Fair Value estimate is ¥4.72 — implying the stock looks roughly 54.8% overvalued today. We read business quality at 94/100 (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: high).
About the company
Infore Environment Technology Group Co., Ltd. engages in the research and development, sales, maintenance, and operation services of environmental protection equipment in China and internationally. It offers intelligent environmental protection equipment, such as cleaning and maintenance equipment, waste collection and transportation equipment, waste compression station equipment, kitchen food waste recycling equipment, and municipal and landscaping equipment, as well as diversified product lines, such as aerial work equipment and emergency fire-fighting equipment. The company also provides intelligent cloud computing, such as smart sanitation cloud platform and smart environmental management; smart services, including integrated sanitation, solid waste treatment, and food waste disposal; and intelligent equipment that include sanitation equipment, sanitation robots, environmental equipment, and scientific instrument. In addition, it operates Qiyuan, a full-scenario intelligent oper…
Open the full interactive analysis →
Similar stocks
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.