Ecovacs Robotics Co (603486) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 31.7B CNY
Analysis
Ecovacs Robotics Co (603486) currently trades at ¥53.80, while our model-based Fair Value estimate is ¥62.48 — implying the stock looks roughly 16.1% undervalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Ecovacs Robotics Co., Ltd., together with its subsidiaries, engages in the research, design, development, manufacture, and sale of household and commercial service robot solutions in China and internationally. It offers DEEBOT, a home floor cleaning robot; WINBOT, a window cleaning robot; AIRBOT, a mobile air purifier; GOAT, a smart robotic lawnmower; FLOOR ONE, a smart floor washer; PURE ONE, a smart vacuum cleaner; CHIERE ONE, a smart cooking machine; HYDRATE ONE, a smart water purifier; MODA ONE, a smart hair dryer; STIYA ONE, a smart wireless brush; DEEBOT PRO K1 VAC, a commercial vacuum robot; and DEEBOT PRO M1, a commercial scrubber robot. The company also provides core components, such as high-precision DTOF LIDAR, KR S50, and KR S30 under the Kruisee Technology brand; lithium batteries under the TD Smart brand; and plastic products and components under the TF Technology brand for use in service robots, household appliances, medical equipment, vehicles, garden tools, and powe…
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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.