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Zhejiang Cayi Vacuum Container Co (301004) Fair Value & Analysis

Consumer Cyclical · CN · Market cap 5.0B CNY

Price¥34.34
Fair Value¥41.62
Upside+21.2%
Quality95/100
Evidence: High Range ¥31.70 – ¥166.48

Analysis

Zhejiang Cayi Vacuum Container Co (301004) currently trades at ¥34.34, while our model-based Fair Value estimate is ¥41.62 — implying the stock looks roughly 21.2% 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

Zhejiang Cayi Vacuum Container Co., Ltd. engages in the research, development, design, production, and sale of beverage and food containers of various materials in China and internationally. The company offers stainless steel water bottle, tumbler and mug, wine cup, vacuum flask, and kids bottle; travel mug and bottle, straw tumbler, and stainless-steel jug; and stainless-steel vacuum insulation utensils, such as vacuum bottle, food jar, sports bottle, digital bottle; stainless steel utensils, plastic utensils, glassware, and other new materials for daily beverages and food containers. It also exports its products to various countries, such as the United States, South Korea, Brazil, Norway, the Netherlands, Japan, and Canada, as well as other European, American, and East Asian countries. Zhejiang Cayi Vacuum Container Co., Ltd. was incorporated in 2004 and is based in Jinhua, 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.