Nanjing Xinlian Electronics Co (002546) Fair Value & Analysis
Industrials · CN · Market cap 5.7B CNY
Analysis
Nanjing Xinlian Electronics Co (002546) currently trades at ¥7.37, while our model-based Fair Value estimate is ¥4.24 — implying the stock looks roughly 42.5% overvalued today. We read business quality at 94/100 (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: high).
About the company
Nanjing Xinlian Electronics Co., Ltd manufactures power consumption information collection systems for power grid enterprises and enterprise users in China. The company provides environmental protection supervision services and user-side system integration platform. It offers concentrators, dedicated transformer data acquisition terminals, electricity information collections main systems, collectors, and software systems; smart energy cloud platform, power distribution monitoring and management systems, central air-conditioning intelligent monitoring systems, park meter reading systems, intelligent maintenance systems, and demand response services; intelligent monitoring systems for environmental protection facilities, catering waste gas monitoring platform, and a collaborative governance data platform for ecological environment governance. In addition, the company provides high and low voltage switchgear, chassis series, new energy series, and console series products. Further, it o…
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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.