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301289 (301289) Fair Value & Analysis

Industrials · CN · Market cap 3.9B CNY

Price¥49.32
Fair Value¥23.22
Upside-52.9%
Quality86/100
Evidence: Medium Range ¥17.41 – ¥29.02

Analysis

301289 (301289) currently trades at ¥49.32, while our model-based Fair Value estimate is ¥23.22 — implying the stock looks roughly 52.9% overvalued today. We read business quality at 86/100 (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

Shanghai National Center of Testing and Inspection for Electric Cable and Wire Co., Ltd provides inspection and testing services in China and internationally. The company offers inspection, testing, equipment measurement, capability verification, and certification services for wires and cables, optical fiber cables, and their components. It also provides professional training, inspection and supervision, standard setting, factory inspection, application evaluation, and other professional technical services. In addition, the company offers partial discharge test calibration, voltage divider ratio calibration, and voltage calibration; and factory inspection and supervision services. The company was founded in 1983 and is headquartered in Shanghai, China. Shanghai National Center of Testing and Inspection for Electric Cable and Wire Co., Ltd. operates as a subsidiary of Shanghai Electric Cable Research Institute Co., Ltd.

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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.