Zhengzhou Tiamaes Technology Co (300807) Fair Value & Analysis
Technology · CN · Market cap 2.7B CNY
Fair value as of: Jun 24, 2026
Analysis
Zhengzhou Tiamaes Technology Co (300807) currently trades at ¥38.97, while our model-based Fair Value estimate is ¥6.49 — implying the stock looks roughly 83.3% overvalued today. We read business quality at 95/100 (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: medium).
About the company
Zhengzhou Tiamaes Technology Co., Ltd., together with its subsidiaries, engages in the production of solutions for urban public transportation operations, management, and services based on internet of vehicles technology in China. The company offers intelligent public transportation dispatching, remote monitoring, intelligent public transportation cashier, and charging operation management systems. It also provides bus terminal, bus smart cashier, and active safety products; electronic bus stop boards and road sign products; multimedia release, new energy charging, and taxi management products; products for vehicles engaging in regular-route passenger transport, tourist passenger transport, and hazardous chemicals transport; station management, BRT bus stop, and intelligent cabin products; and other products. In addition, the company offers software solutions, including smart bus, integrated transportation, smart charging, smart taxi, smart sanitation, and other application systems,…
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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.