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300826 (300826) Fair Value & Analysis

Industrials · CN · Market cap 3.4B CNY

Price¥15.17
Fair Value¥5.79
Upside-61.8%
Quality91/100
Evidence: High Range ¥4.53 – ¥7.96

Analysis

300826 (300826) currently trades at ¥15.17, while our model-based Fair Value estimate is ¥5.79 — implying the stock looks roughly 61.8% overvalued today. We read business quality at 91/100 (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

NanJing Research Institute of Surveying, Mapping & Geotechnical Investigation,Co.Ltd. provides surveying and mapping services in the People's Republic of China. It offers surveying and mapping technology and consulting services for planning, natural resource management, and urban and rural construction projects; and engineering survey and geotechnical engineering services for engineering construction projects. The company also provides geographical information-based information system integration and related services in the fields of rail transit operation monitoring, urban map (atlas) compilation, remote sensing, geographic national conditions census and monitoring, pipeline detection, and garden intelligent management. In addition, it offers smart water and garden, underground space system, natural resource product, urban smart drainage monitoring and supervision, and intelligent monitoring and supervision of rail transit structure safety. The company was founded in 1991 and is ba…

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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.