Shenzhen Genvict Technologies Co (002869) Fair Value & Analysis
Industrials · CN · Market cap 3.4B CNY
Analysis
Shenzhen Genvict Technologies Co (002869) currently trades at ¥18.86, while our model-based Fair Value estimate is ¥4.30 — implying the stock looks roughly 77.2% overvalued today. We read business quality at 95/100 (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: low).
About the company
Shenzhen Genvict Technologies Co., Ltd., together with its subsidiaries, engages in the research, development, and sale of smart transportation technologies in China. The company offers smart highway products, such as unmanned smart charging, mobile emergency charging, smart tunnel integration, smart maintenance construction, and smart service area solutions; and urban digital transportation products, including smart intersection holographic perception, smart transportation digital twin, RFID electric bicycle management, urban parking ETC recovery, and city-level smart parking solutions. It also provides vehicle-road collaboration products comprising intelligent connected bus, smart highway, intelligent connected test zone, and intelligent networking solutions; and automotive electronics consisting of V2X autonomous driving, car T-BOX, ETC car front-end, and body electronics solutions, as well as digital energy solutions. The company was incorporated in 2004 and is based in Shenzhen…
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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.