AnHui Wanyi Science and Technology Co (688600) Fair Value & Analysis
Technology · CN · Market cap 3.5B CNY
Fair value as of: Jun 24, 2026
Analysis
AnHui Wanyi Science and Technology Co (688600) currently trades at ¥31.14, while our model-based Fair Value estimate is ¥8.35 — implying the stock looks roughly 73.2% 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
AnHui Wanyi Science and Technology Co.,Ltd. provides precision scientific instruments and solutions in China and internationally. It offers industrial testing instruments, including helium leak detector, pressure decay leak detector, and vacuum chamber leak detection system; online monitoring instruments, such as water quality, air, online pollution source, and industrial process monitoring products; and laboratory analytical instruments comprising chromatography, mass spectrometry, and spectrometry. The company also provides chromatography consumables, which include ion, liquid, and other chromatography consumables; and medical instruments, such as minimally invasive tools. In addition, it offers various solutions for medicine, environment, energy and chemical, auto, semiconductor, public security and justice, scientific research, home appliance refrigeration, electric power, geology and metallurgy, cosmetics, and food, as well as smart industry, environment, and laboratories indus…
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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.