Hangzhou Zhongya Machinery Co (300512) Fair Value & Analysis
Industrials · CN · Market cap 3.1B CNY
Fair value as of: Jun 24, 2026
Analysis
Hangzhou Zhongya Machinery Co (300512) currently trades at ¥7.33, while our model-based Fair Value estimate is ¥1.59 — implying the stock looks roughly 78.3% 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
Hangzhou Zhongya Machinery Co., Ltd. develops, manufactures, and sells packaging equipment and unattended vending equipment in China and internationally. The company offers filling and sealing equipment comprising linear aseptic bottle and cup filling and sealing equipment, soft bag aseptic molding filling sealing and cutting equipment, cup aseptic forming filling and sealing equipment, linear type ultraclean filling and sealing equipment for prefabricated cup, rotary preformed cup filling and sealing equipment, linear plastic bottle ultraclean filling and capping equipment, ultraclean filling and capping equipment for rotating plastic bottles, rotary plastic bottle capping equipment, equipment of blowing, filling and sealing integrated machine, and cheese bar forming filling and sealing equipment. It also provides rear intelligent packaging equipment production line products, including automatic small pack edible oil bottle blowing filling case packing, home care product bottle uns…
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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.