Shenzhen Colibri Technologies Co (002957) Fair Value & Analysis
Industrials · CN · Market cap 23.3B CNY
Fair value as of: Jun 25, 2026
Analysis
Shenzhen Colibri Technologies Co (002957) currently trades at ¥57.45, while our model-based Fair Value estimate is ¥13.65 — implying the stock looks roughly 76.2% overvalued today. We read business quality at 89/100 (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: medium).
About the company
Shenzhen Colibri Technologies Co., Ltd. engages in the research and development, design, production, sale, and technical service of industrial automation equipment and precision parts in China. The company offers camera module tests, camera tests, sensor tests, ar/vr tests, module tests, calibration tests, test sockets, and self and module assembly. It also provides stacking and pressing cells; matching, tab ultrasonic and adapter laser welding, mylar wrapping, shell insertion, top cover laser prewelding and full welding, sealing nail welding, as well as coating and dimension measuring equipment; tab-welding and packing, secondary degassing, double side sealing forming integration, and dimensional measurement; flattening, film wrapping, jr inserting, current collector welding, terminal pre-welding and full welding, and air leakage test; and cylindrical battery chemical separation system, automation formation and capacity grading line, and pouch cell formation and grading system. In …
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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.