RoadMainT Co (603860) Fair Value & Analysis
Industrials · CN · Market cap 1.8B CNY
Fair value as of: Jun 24, 2026
Analysis
RoadMainT Co (603860) currently trades at ¥25.72, while our model-based Fair Value estimate is ¥14.36 — implying the stock looks roughly 44.2% 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
RoadMainT Co.,Ltd. engages in the research and development, promotion, and application of highway maintenance technology in China. The company provides CRMS highway asset management system and analysis platform; and iroad highway full asset mobile information platform. It also offers national and provincial trunk lines; city, rural, and foreign roads; and inspection and specialized equipment. In addition, it offers decision consulting services, such as disease diagnosis, maintenance needs, and optimization of fund allocation analysis; road network level and project level maintenance planning; maintenance performance evaluation; and highway asset valuation. Further, it provides road condition detection and evaluation, material performance verification, production process validation, and detection of hidden structural defects services; and engineering application services, such as rural roads, construction technical, demonstration road creation consultation, maintenance engineering sc…
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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.