Harbin Boshi Automation Co (002698) Fair Value & Analysis
Industrials · CN · Market cap 11.9B CNY
Analysis
Harbin Boshi Automation Co (002698) currently trades at ¥11.33, while our model-based Fair Value estimate is ¥10.63 — implying the stock looks roughly 6.2% overvalued today. We read business quality at 92/100 (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
Harbin Boshi Automation Co., Ltd. engages in the research and development, production, sale, and service of intelligent manufacturing equipment and industrial robots in the People's Republic of China. It offers industrial robots, smelting robot equipment, weighing equipment, palletizing systems, conveying inspection equipment, intelligent logistics systems, rubber post-processing equipment, and energy-saving and environment protection equipment, as well as provides technical support and training, spare parts, maintenance and overhaul, operation-guaranteed, production and operation, and services network services. The company provides solutions for chemical, rubber, smelt, feed, foodstuff/beverage, medicine, building material, photovoltaics, steel, intelligent logistics, and energy saving and environmental protection sectors. It also exports its products to various countries in Europe, Asia, the United States, Africa, and other countries. The company was formerly known as Harbin BOSHI…
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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.