Shanghai Ganglian E-Commerce Holdings (300226) Fair Value & Analysis
Communication Services · CN · Market cap 6.6B CNY
Analysis
Shanghai Ganglian E-Commerce Holdings (300226) currently trades at ¥17.44, while our model-based Fair Value estimate is ¥11.68 — implying the stock looks roughly 33.0% overvalued today. We read business quality at 86/100 (high quality), in the Communication Services 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
Shanghai Ganglian E-Commerce Holdings Co., Ltd. provides data services for commodities and related industries in the People's Republic of China. The company offers big data and data processing, industrial internet data, software development and sale, enterprise management consulting, conference and exhibition, advertising design, and agency and publication services. It also offers consignment transaction and supply chain services; and steel products and related services. It operates banksteel.com, a steel and silver steel spot online trading platform; and Gangyin e-commerce that provides a package of e-commerce solutions for upstream and downstream users in the steel industry. In addition, the company's services cover various industries, such as ferrous and nonferrous metals, energy, chemical, building materials, agricultural products, extends to new energy, new materials, renewable resources, and other commodity fields. Shanghai Ganglian E-Commerce Holdings Co., Ltd. was founded in…
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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.