Shenzhen V&T Technologies Co (300484) Fair Value & Analysis
Industrials · CN · Market cap 3.1B CNY
Fair value as of: Jun 24, 2026
Analysis
Shenzhen V&T Technologies Co (300484) currently trades at ¥14.52, while our model-based Fair Value estimate is ¥4.83 — implying the stock looks roughly 66.7% 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: high).
About the company
Shenzhen V&T Technologies Co., Ltd., together with its subsidiaries, engages in the research, development, manufacturing, sale, and service of industrial automation products and systems in China and internationally. It offers industrial automation products, including inverters, elevator control system, PLC, HMI, and servo drives; energy vehicles, such as electric vehicle motor controllers and low-voltage power controllers; and smart gateway, as well as V&T digital cloud, an enterprise digital cloud service platform for IoT, edge computing, data analysis, and product promotion. The company also provides medium and low-voltage frequency inverters, DCDC power supplies, elevator integration products, and other power electronic accessories; customized solutions; and software and tools. In addition, it offers pre and after-sales services; and maintenance services. The company was incorporated in 2006 and is headquartered in Shenzhen, China.
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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.