Bingshan Refrigeration & Heat Transfer Technologies Co (000530) Fair Value & Analysis
Industrials · CN · Market cap 4.8B CNY
Analysis
Bingshan Refrigeration & Heat Transfer Technologies Co (000530) currently trades at ¥5.21, while our model-based Fair Value estimate is ¥3.28 — implying the stock looks roughly 37.0% 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
Bingshan Refrigeration & Heat Transfer Technologies Co., Ltd., together with its subsidiaries, engages in the design, manufacturing, sale, installation, and maintenance of refrigeration, heating, and air conditioning equipment in China and internationally. The company offers piston type, screw type, vortex type, and lithium bromide absorption refrigeration machines/units, as well as pressure vessels, combination warehouses, controlled atmosphere fresh-keeping warehouses, refrigeration stations, quick freezing machines, and heat pumps. It provides maintenance services, including inspection and patrol, routine maintenance, emergency services, technical training, and overhaul workshop; and digital services. In addition, the company engages in the manufacturing and sale of gas compression machinery; building hardware; and plumbing equipment. It serves industrial refrigeration and heating, commercial freezing and refrigeration, air conditioning and environment, smart cold chain, industri…
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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.