Rainbow Digital Commercial Co (002419) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 5.3B CNY
Fair value as of: Jun 25, 2026
Analysis
Rainbow Digital Commercial Co (002419) currently trades at ¥4.68, while our model-based Fair Value estimate is ¥1.57 — implying the stock looks roughly 66.5% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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
Rainbow Digital Commercial Co., Ltd. operates a chain of department stores, shopping centers, and supermarkets in China. The company offers fresh and cooked food, including fruits, vegetables, meat, poultry, eggs, seafood, dried goods, wholesale grains, cooked food, baked goods, staple food, frozen and refrigerated food, grains, and grain products; packaged food, such as non-staple food, edible oils, beverages, biscuits, and pastries; and daily necessities, comprising toiletries, cleaning products, and kitchenware, etc. It also provides department store retail, consists of clothing, cosmetics, gold and jewelry, leather shoes and goods, baby products, bedding, home furnishings, and electrical appliances; and catering and entertainment/educational services. It offers its services under Tianhong, Jun Shang, and sp@ce brand names. The company was formerly known as Rainbow Department Store Co., Ltd. and changed its name to Rainbow Digital Commercial Co., Ltd. in 2020. Rainbow Digital Com…
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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.