Tianjin Keyvia Electric Co (300407) Fair Value & Analysis
Industrials · CN · Market cap 4.1B CNY
Analysis
Tianjin Keyvia Electric Co (300407) currently trades at ¥11.89, while our model-based Fair Value estimate is ¥7.25 — implying the stock looks roughly 39.0% overvalued today. We read business quality at 95/100 (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
Tianjin Keyvia Electric Co.,Ltd engages in the research and development, production, and sales of electrified railway and urban rail transit traction power supply systems in China. The company offers power supply dispatching, substation and distribution integrated automation, telecontrol terminal control, wide area protection measurement and control, intelligent auxiliary monitoring, railway tunnel monitoring, electrical detection vehicle, and simulation teaching and training systems for electrified railway power supply automation. It also provides integrated monitoring system, integrated automation system of substation, rigid suspension catenary system, dc switch cabinet, environment and equipment monitoring system, energy management system, comprehensive intelligent security monitoring system, integrated intelligent power supply operation management system, power supply protection measurement and control system, visual grounding system, LTE and dedicated wireless system, vehicles …
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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.