Inspur Software Co (600756) Fair Value & Analysis
Technology · CN · Market cap 4.6B CNY
Analysis
Inspur Software Co (600756) currently trades at ¥13.60, while our model-based Fair Value estimate is ¥19.92 — implying the stock looks roughly 46.5% undervalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: low) — always confirm before acting.
About the company
Inspur Software Co., Ltd. provides cloud computing and big data services in China and internationally. The company offers computing equipment, such as storage, intelligent network, and cloud operating systems; government services and enterprise cloud; industrial internet products comprising industrial internet platforms, safety, communication, equipment, application, supply chain, and equipment health management; and data management. It also provides software products, including professional human resources cloud platform HCM cloud, and intelligent ERP for large enterprises GS cloud, as well as for small and middle sized enterprises inSuite; Inspur Haiyue low code platform inBuilder, Inspur Haiyue data middle platform in DataX, Inspur Haiyue intelligent IoT platfrom inIoT, and Inspur Haiyue big model inGPT; and databases and industry PaaS platforms. In addition, the company offers mobile private network, all-optical network, 5G router, IoT gateways, and edge desktop cloud; display, …
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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.