Weiye Construction Group (300621) Fair Value & Analysis
Industrials · CN · Market cap 1.5B CNY
Fair value as of: Jun 24, 2026
Analysis
Weiye Construction Group (300621) currently trades at ¥6.86, while our model-based Fair Value estimate is ¥12.50 — implying the stock looks roughly 82.2% undervalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: low) — always confirm before acting.
About the company
Weiye Construction Group Co., Ltd. engages in the building decoration and civil construction businesses in China. It is involved in general construction contracting, door and window, curtain wall building, interior design, and cultural expo exhibition, electromechanical/intelligent, steel structure construction, and design and development activities. The company provides professional contracting for foundation engineering, post-construction decoration, and renovation and cleaning, as well as engages in technology development, transfer, consulting, and technology services for emerging materials in the field of architectural decoration. The company offers its services for government projects, star hotel, large-scale public construction, cultural architecture, office space, commercial complexes, building curtain walls, residences are well decorated sectors. The company was formerly known as ShenZhen WeiYe Decoration Group Co.,LTD and changed its name to Weiye Construction Group Co., Lt…
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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.