Tiandi Science & Technology Co. (600582) Fair Value & Analysis
Industrials · CN · Market cap 21.6B CNY
Analysis
Tiandi Science & Technology Co. (600582) currently trades at ¥4.83, while our model-based Fair Value estimate is ¥10.05 — implying the stock looks roughly 108.1% undervalued today. We read business quality at 80/100 (high quality), in the Industrials 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
Tiandi Science & Technology Co.Ltd engages in the research, technology development, equipment manufacturing, engineering demonstration, testing, and inspection activities for the coal industry in China. It supplies intelligent technologies and equipment for coal mines, including intelligent mining, tunneling, and transportation, as well as mining equipment and washing equipment. The company also offers safety products, technical services, disaster management and other services for coal mine safety technology sector. In addition, it is involved in clean utilization, low-carbon and carbon reduction, and new energy activities; survey and design, engineering general contracting and supervision consulting; demonstration mines, professional operations and ecological governance; and urban construction, new materials, and cross-border extension businesses. The company was founded in 2000 and is based in Beijing, China. Tiandi Science & Technology Co.Ltd is a subsidiary of China Coal Technol…
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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.