Beijing Oriental Jicheng Co (002819) Fair Value & Analysis
Technology · CN · Market cap 6.5B CNY
Analysis
Beijing Oriental Jicheng Co (002819) currently trades at ¥21.44, while our model-based Fair Value estimate is ¥9.31 — implying the stock looks roughly 56.6% overvalued today. We read business quality at 86/100 (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: medium).
About the company
Beijing Oriental Jicheng Co., Ltd. engages in the testing technology and service-related businesses in China. The company offers general electronic testing products, such as oscilloscope and accessories, digital multimeter, signal generator, power supply, electronic load, infrared temperature measurement, data loggers and switches, frequency counter, power analysis, logic analyzer, safety test, power quality analysis, component parameter test, and small signal measurement, metrology and calibration, data logger, audio and video test, dedicated analyzer, general electronics testing, and battery test. It also provides RF test equipment, including spectrum analyzer, RF signal source, network analyzer, wireless comprehensive tester, RF power meters and power sensors, and other RF test equipment; EMS test equipment, EMI test equipment, EMC test related accessories, and EMC test software; solar cell testing and solar radiation; semiconductor material and chip testing; and optical and colo…
Open the full interactive analysis →
Similar stocks
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.