Hengdian Group (002056) Fair Value & Analysis
Technology · CN · Market cap 42.2B CNY
Fair value as of: Jun 25, 2026
Analysis
Hengdian Group (002056) currently trades at ¥29.24, while our model-based Fair Value estimate is ¥22.76 — implying the stock looks roughly 22.2% overvalued today. We read business quality at 92/100 (high quality), in the Technology 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
Hengdian Group DMEGC Magnetics Co., Ltd., together with its subsidiaries, provides magnetic materials, photovoltaic products, lithium batteries, and devices in China and internationally. The company offers tile-shaped, ring, microwave oven, square, dry pressing and irregularly shaped, and bonded composite permanent magnets; manganese-zinc power and high-conductivity ferrite, nickel-zinc ferrite, magnetic powder core, nanocrystals, magnetic sheet, and magnetic design tool; rubber magnetic sheet, extruded magnetic strip, motor magnetic strip and sensor magnetic ring, water pump rotor, glue-coated parts, and magnetic ring and rotor assembly; and permanent magnet ferrite sintering and binder powder. It also provides solar modules and cells; lithium battery cells and energy storage and pack modules; cemented carbide, including carbide top hammer, composite substrate, non-standard cemented carbide for molds, non-standard oil hard alloy, and high-density tungsten products; in-vehicle and c…
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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.