China Transinfo Technology Co (002373) Fair Value & Analysis
Technology · CN · Market cap 12.0B CNY
Analysis
China Transinfo Technology Co (002373) currently trades at ¥7.76, while our model-based Fair Value estimate is ¥3.81 — implying the stock looks roughly 50.9% overvalued today. We read business quality at 91/100 (high quality), in the Technology 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
China Transinfo Technology Co., Ltd. engages in the transportation, Internet of Things, big data, and artificial intelligence businesses. The company offers edge computing equipment, intelligent connected products (ICP), signal system, intelligent intersection, rural and national highway safety, dynamic weighing scales, highway monitoring equipment, traffic flow survey equipment, on-street parking intelligent devices, ETC, intelligent PIS playback control equipment, audio and video intelligent remote, transmission equipment, video processing equipment, intelligent parking lot, AI algorithm products, intelligent traffic camera, and traffic radar and LiDAR products. It also provides highway; airport digitalization; transportation; law enforcement; rail transit; urban traffic management; national and provincial highway and county and township road traffic comprehensive management; public security traffic management big data business think; and IoT solutions. China Transinfo Technology …
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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.