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WINBO-Dongjian Automotive Technology Co (300978) Fair Value & Analysis

Consumer Cyclical · CN · Market cap 3.9B CNY

Price¥8.74
Fair Value¥7.41
Upside-15.2%
Quality91/100
Evidence: High Range ¥5.56 – ¥9.27

Analysis

WINBO-Dongjian Automotive Technology Co (300978) currently trades at ¥8.74, while our model-based Fair Value estimate is ¥7.41 — implying the stock looks roughly 15.2% overvalued today. We read business quality at 91/100 (high quality), in the Consumer Cyclical 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

WINBO-Dongjian Automotive Technology Co., Ltd. produces and sells automotive smart cockpits and exterior parts in China. The company offers smart door, electric tailgate, electric pedal, electric folding rearview mirror, electronic child lock, electric closing door, and smart car air purifier products; and front and rear bar, side pedal, luggage rack/luggage box, and surround/tail products. It also provides pickup tail box cover, pickup trunk multi-function rack, and luggage rack luggage rack products; and pickup/wrangler pump handle, front bumper, U-shaped front bumper, off-road side anti-collision pedal, side bar/pedal, wheel eyebrow, car door, anti-roll frame, pickup truck tail compartment, and UTV series products. The company also exports its products. WINBO-Dongjian Automotive Technology Co., Ltd. was founded in 2003 and is based in Foshan, China.

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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.