Suzhou Goldengreen Technologies Ltd (002808) Fair Value & Analysis
Industrials · CN · Market cap 761M CNY
Fair value as of: Jun 25, 2026
Analysis
Suzhou Goldengreen Technologies Ltd (002808) currently trades at ¥2.83, while our model-based Fair Value estimate is ¥2.77 — implying the stock looks roughly 2.1% overvalued today. We read business quality at 89/100 (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: low).
About the company
Suzhou Goldengreen Technologies Ltd., together with its subsidiaries, researches, develops, manufactures, and sells laser organic photo-conductor drum (OPC) products in China and internationally. The company offers OPC drum and toner; security, application, and big data products; and indoor base station backup power system and backup power supply system for communication base station. It is also involved in factoring business. In addition, the company provides MB confidential computer and mobile storage media confidentiality management system, MB mobile data security protection system, MB data security sealing audit system, MB network storage security enhancement system, MB intranet security management system, and MB Internet export detection system. Further, it is involved in the computer software and hardware development, design, installation, and construction; electronic and intelligent engineering design and construction; online data processing and transaction processing busines…
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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.