Rigol Technologies Co (688337) Fair Value & Analysis
Technology · CN · Market cap 12.5B CNY
Analysis
Rigol Technologies Co (688337) currently trades at ¥75.00, while our model-based Fair Value estimate is ¥10.78 — implying the stock looks roughly 85.6% 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
Rigol Technologies Co., Ltd., together with its subsidiaries, engages in the research, development, manufacturing, and sale of electronic testing and measuring instruments and accessories in China and internationally. The company offers digital oscilloscopes, function/arbitrary waveform generators, RF signal generators, DC power supplies, programmable DC electronic loads, digital multimeters, data acquisition and switch systems, spectrum analyzers, modular instruments, and probes. It also provides communication test solutions, including wireless communication and USB, ethernet, and MIPI D-PHY physical layer compliance tests; automotive electronics test solutions, such as smart cockpit, ADAS, and powertrain; and power electronics test solutions comprising power semiconductor dynamic performance testing and power supply design and testing. In addition, the company offers warranty extension, maintenance plan, license activation, factory calibration and certification, and calibration an…
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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.