Allied Machinery Co (605060) Fair Value & Analysis
Industrials · CN · Market cap 11.6B CNY
Analysis
Allied Machinery Co (605060) currently trades at ¥53.50, while our model-based Fair Value estimate is ¥19.87 — implying the stock looks roughly 62.9% 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
Allied Machinery Co., Ltd. designs, researches and develops, produces, and sells high-precision mechanical parts and precision cavity mold products in China and the United States. It provides gearbox and rear gearbox, engine block, flywheel housing, reducer and reducer housing, torque arm, and power frame; valve case and body, reducer rear cover, housing and motor housing, regulator, and pump rear cover; compressor, interstage and rotor housing, volute casing, suction cover, and motor housings products. The company also offers rear wheel hub, axle housing, turbine support, CASE, housing frame, end housing, left cam, bracket, left mounting frame, main reducer housing, crankcase housing, pump flange, slider, connecting rod, dual-end base, power frame, drive housing, base, main baffle, spindle disk, and right rear base products. It offers its products for power and energy, hydraulics, HVAC, construction, air compressor, agriculture, automation, and food process industry. Allied Machine…
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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.