Sichuan Crun Co (002272) Fair Value & Analysis
Industrials · CN · Market cap 10.3B CNY
Analysis
Sichuan Crun Co (002272) currently trades at ¥22.61, while our model-based Fair Value estimate is ¥2.40 — implying the stock looks roughly 89.4% 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: medium).
About the company
Sichuan Crun Co., Ltd manufactures and sells high-end equipment in the People's Republic of China. It offers liquid cooling products and temperature control energy-saving solutions; clean energy equipment, energy storage equipment, heat exchange equipment, power station boilers, and industrial boilers; and hydraulic lubrication system and integration, energy storage temperature control, liquid cooling system, and fluid control equipment. The company also provides digital supply chain manufacturing and sales; and hydraulic lubrication system technical, intelligent operation and maintenance, equipment predictive health management, equipment life cycle value-added, one-stop service platform, as well as technical, operation and maintenance, and equipment transformation services. In addition, it engages in the sale of lubricating hydraulic equipment, boilers, and pressure vessels; charging equipment sales and operation management services; road freight transportation; technology developm…
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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.