HeNan Splendor Science & Technology Co (002296) Fair Value & Analysis
Industrials · CN · Market cap 3.8B CNY
Analysis
HeNan Splendor Science & Technology Co (002296) currently trades at ¥9.37, while our model-based Fair Value estimate is ¥9.61 — implying the stock looks roughly 2.6% undervalued today. We read business quality at 94/100 (high quality), in the Industrials 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: high) — always confirm before acting.
About the company
HeNan Splendor Science & Technology Co., Ltd. engages in the research and development and promotion of rail transit measurement and control technologies for the rail transit industry in China. The company offers railway signal centralized monitoring systems, hump signal centralized monitoring systems, microcomputer monitoring intelligent analysis and fault diagnosis systems, railway turnout comprehensive monitoring systems, frequency shift track circuit outdoor monitoring systems, railway power environment monitoring systems, signal room UPS and battery online monitoring systems, railway communication tower monitoring systems, electric service comprehensive data analysis platform systems, high-speed railway natural disaster and foreign body intrusion monitoring systems, railway integrated video monitoring systems, high-speed railway perimeter intrusion alarm systems, decentralized autonomous dispatching centralized systems, train dispatching and command systems, wireless shunting lo…
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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.