Guangdong Naruida Technology Co (688522) Fair Value & Analysis
Technology · CN · Market cap 8.5B CNY
Analysis
Guangdong Naruida Technology Co (688522) currently trades at ¥20.38, while our model-based Fair Value estimate is ¥5.42 — implying the stock looks roughly 73.4% 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
Guangdong Naruida Technology Co., Ltd. manufactures and sells polarized multifunctional active phased array radars in China. The company offers dual-polarization active phased array radars; radar meteorological product generation software, a software that processes and analyzes technology to generate radar meteorological products; WebGIS three-dimensional data visualization software, a meteorological application software; networked phased array weather radar control software system for status monitoring and control of multiple radar equipment; phased array weather radar control software system for controlling antenna array of phased array weather radar; and radar-based data analysis software that assists users in parsing, plotting, and analyzing dual-polarized phased array radar baseline data and meteorological product documents. It also provides hailstorm man-made weather automatic early warning system for achieving automatic hail warnings; short-term and nowcasting system for weat…
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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.