Tianshan Material Co (000877) Fair Value & Analysis
Basic Materials · CN · Market cap 28.8B CNY
Analysis
Tianshan Material Co (000877) currently trades at ¥3.94, while our model-based Fair Value estimate is ¥2.86 — implying the stock looks roughly 27.5% overvalued today. We read business quality at 86/100 (high quality), in the Basic Materials 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
Tianshan Material Co., Ltd. engages in the production and sale of cement, clinker, ready-mixed concrete, and aggregates in China and internationally. It offers ordinary cement, including silicate cement and common silicate cement; and special cements, such as sulfoaluminate cement, oil well cement, hydraulic cement, high-temperature heavy oil cement, sulfate-resistant silicate cement, ultrafine silicate cement, road silicate cement, silicate cement for nuclear power engineering, marine cement, fast-setting and fast-hardening sulfoaluminate cement, and medium-heat and low-heat silicate cement. The company also provides ordinary mortars consisting of leveling and plastering mortars, as well as tile adhesive specialty mortars; conventional commercial concrete and high-strength concrete; air entrained concrete, radiation proof concrete, permeable concrete, plain concrete, lightweight aggregate concrete, ultra-high strength and high-performance concrete, soil and low heat concrete, self-…
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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.