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Beijing Yuanliu Hongyuan Electronic Technology Co (603267) Fair Value & Analysis

Technology · CN · Market cap 15.8B CNY

Price¥75.63
Fair Value¥21.63
Upside-71.4%
Quality95/100
Evidence: High Range ¥13.68 – ¥27.04

Analysis

Beijing Yuanliu Hongyuan Electronic Technology Co (603267) currently trades at ¥75.63, while our model-based Fair Value estimate is ¥21.63 — implying the stock looks roughly 71.4% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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

Beijing Yuanliu Hongyuan Electronic Technology Co., Ltd. engages in the research and development, production, and sale of electronic components in China and internationally. The company operates through Self-Produced Business and Agency Business segments. It offers ceramic capacitors and components, filters, microprocessors, microcontrollers, microwave modules, micro-nano system integrated ceramic shells, and supporting integrated circuits. In addition, the company provides resistors, inductors, RF devices, discrete devices, connectors, integrated circuits, and other products. It serves aerospace, aviation, electronic information, weapons, ships, automotive electronics, communications, rail transportation, medical electronics, industrial, consumer, and other reliability sectors. The company was founded in 2001 and is based in Beijing, China.

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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.