Sichuan Kexin Mechanical and Electrical Equipment Co (300092) Fair Value & Analysis
Industrials · CN · Market cap 3.6B CNY
Analysis
Sichuan Kexin Mechanical and Electrical Equipment Co (300092) currently trades at ¥12.64, while our model-based Fair Value estimate is ¥4.91 — implying the stock looks roughly 61.2% 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: high).
About the company
Sichuan Kexin Mechanical and Electrical Equipment Co.,Ltd., together with its subsidiaries, engages in the design, development, and manufacture of heavy-duty process equipment and system integration in China and internationally. It provides lifting equipment, material cutting and forming equipment, metal machining, welding and auxiliary equipment, NDT equipment and chemical laboratory, and heat and surface treatment equipment. The company also offers urea HP core equipment, heavy-duty pressure vessel, heat exchanger, furnace, column, nuclear equipment, vessel, and skidding equipment. In addition, it provides oil drilling equipment, oil production machinery and equipment, oilfield environmental protection equipment, and services. Further, the company offers technical consulting and engineering project contracting services. Sichuan Kexin Mechanical and Electrical Equipment Co.,Ltd was founded in 1997 and is based in Shifang, China.
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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.