Jiangsu Daybright Intelligent Electric Co (300670) Fair Value & Analysis
Industrials · CN · Market cap 2.0B CNY
Fair value as of: Jun 24, 2026
Analysis
Jiangsu Daybright Intelligent Electric Co (300670) currently trades at ¥6.34, while our model-based Fair Value estimate is ¥6.15 — implying the stock looks roughly 3.0% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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
Jiangsu Daybright Intelligent Electric Co.,LTD. engages in the research, product development, production, sale, and service of distribution network equipment in China. It offers sensor transmission products covering electrical status, asset environment data collection and transmission, comprehensive energy data collection, and transmission; wireless communication products, such as low-power transmission and transformation Internet of Things wireless transmission modules, intelligent substation fusion terminals, station terminals, feeder terminals, fault indicators and ground fault analysis and auxiliary devices, energy Internet of Things gateways and other edge computing terminal products, Internet of Things-based pole switches, Internet of Things-based ring network boxes, etc. The company also provides energy storage systems under the YelonnESS brand name. In addition, it is involved in the provision of onshore wind power, photovoltaic and energy storage project investment and deve…
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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.