Fujian Tendering Co (301136) Fair Value & Analysis
Industrials · CN · Market cap 3.4B CNY
Analysis
Fujian Tendering Co (301136) currently trades at ¥12.07, while our model-based Fair Value estimate is ¥7.23 — implying the stock looks roughly 40.1% overvalued today. We read business quality at 92/100 (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: high).
About the company
Fujian Tendering Co., Ltd. provides engineering supervision, test and inspection, surveying and mapping, geographic information, survey and design, and other engineering consulting services in China. It offers engineering supervision services for highways, water transportation, housing construction, municipal administration, electromechanical installation, agriculture and forestry, and other projects; test and inspection services for construction, supervision, acceptance, maintenance, repair, and other links of the project; bidding agency services and pre-project consulting services; and topographic map surveying and mapping, cadastral house survey, natural resource survey, engineering survey, and other services. The company also provides geotechnical engineering survey, housing construction engineering design, urban and rural planning, landscape garden engineering design, ancient building, modern building protection engineering, protection planning and design, highway design, const…
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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.