Beijing Philisense Technology Co (300287) Fair Value & Analysis
Technology · CN · Market cap 5.2B CNY
Analysis
Beijing Philisense Technology Co (300287) currently trades at ¥3.57, while our model-based Fair Value estimate is ¥2.13 — implying the stock looks roughly 40.3% 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: low).
About the company
Beijing Philisense Technology Co., Ltd., together with its subsidiaries, provides government informatization solutions in China. The company offers meeting products comprising wired digital conference and wireless digital conference products; matrix switching and processing equipment; multimedia information display devices; simultaneous interpretation system equipment; meeting check-in equipment; electronic ticket box equipment; digital sound reinforcement equipment; system host products; and system software products. It also provides software products comprising intelligent meeting management software, electronic records management systems, content management platforms, staff attendance systems, human resources information management systems, salary and payroll management systems, civil servant information management systems, public institution information management systems, information management systems, CPPCC information systems, petition information management systems, governm…
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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.