Cubic Sensor and Instrument Co (688665) Fair Value & Analysis
Technology · CN · Market cap 5.5B CNY
Analysis
Cubic Sensor and Instrument Co (688665) currently trades at ¥59.84, while our model-based Fair Value estimate is ¥25.65 — implying the stock looks roughly 57.1% overvalued today. We read business quality at 92/100 (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
Cubic Sensor and Instrument Co.,Ltd. engages in the development, production, and sale of gas sensors and sensor solutions in China and internationally. It offers thermostats; air quality detectors; household infrared and laser methane, electrochemical formaldehyde, VOC gas, integrated air quality modules, infrared carbon dioxide, optical dust, infrared dust, CO2 gas transmitters, dust and dirt sensors; and fresh air controllers. It also provides automotive air quality, in-vehicle, smoke, thermal conductivity hydrogen, electrolyte leakage; oxygen, nitrogen, motorcycle oxygen, battery thermal runaway monitoring, automotive CO2 gas and integrated sensors; automotive fragrance and negative ion generator; and car seat ventilation fans and headlight cooling fans. In addition, it offers refrigerant leak monitoring, NMP gas, laser ammonia, and laser leak detectors; dust particle counters; high humidity CO2 transmitters; and laser methane, miniature infrared, energy storage thermal runaway, …
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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.