Jiangsu Zhongshe Group (002883) Fair Value & Analysis
Industrials · CN · Market cap 1.4B CNY
Fair value as of: Jun 25, 2026
Analysis
Jiangsu Zhongshe Group (002883) currently trades at ¥8.92, while our model-based Fair Value estimate is ¥2.65 — implying the stock looks roughly 70.3% 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: medium).
About the company
Jiangsu Zhongshe Group Co., Ltd. provides engineering design consulting and general contracting services in the field of transportation, municipal administration, construction, and environment in China. The company engages in the comprehensive transportation planning for regions and cities; special transportation planning for highways, water transportation, passenger and freight hubs, ports, logistics, etc.; planning and design of transportation organization; and design, consultation, supervision, survey, test and inspection, project management, and general contracting of highways, bridges, tunnels, ports, waterways, traffic safety facilities, tracks, water supply, drainage, lighting, intelligent transportation, and other projects. It is also involved in the planning of urban express road network, public transportation, parking lots, and intelligent transportation; planning and design of urban furniture, transportation hubs, urban complexes, and urban renewal; and construction of sm…
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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.