Shanghai Hi-Tech Control System Co (002184) Fair Value & Analysis
Technology · CN · Market cap 3.8B CNY
Analysis
Shanghai Hi-Tech Control System Co (002184) currently trades at ¥10.25, while our model-based Fair Value estimate is ¥1.73 — implying the stock looks roughly 83.1% overvalued today. We read business quality at 80/100 (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
Shanghai Hi-Tech Control System Co., Ltd, together with its subsidiaries, engages in the manufacturing and system integration of industrial automation products in China and internationally. The company operates in three segments: Industrial Electrical Automation Business, Industrial Information Technology Business, and New Energy Business. It is involved in electrical automation; wholesale distribution and technical services on industrial automation and electronic and electric products; and supply chain services. The company also offers intelligent manufacturing products, solutions, and services; and industrial network, software, computing, and other related products, as well as automation and information integration solutions and services. In addition, it engages in research, development, and production of technology products in new energy source industries, such as wind power, solar power, and others. The company was founded in 1994 and is headquartered in Shanghai, China.
Open the full interactive analysis →
Similar stocks
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.