Red Star Macalline Group (601828) Fair Value & Analysis
Real Estate · CN · Market cap 10.1B CNY
Analysis
Red Star Macalline Group (601828) currently trades at ¥2.21, while our model-based Fair Value estimate is ¥0.3900 — implying the stock looks roughly 82.4% overvalued today. We read business quality at 93/100 (high quality), in the Real Estate 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
Red Star Macalline Group Corporation Ltd. operates and manages home improvement and furnishing malls in the People's Republic of China. It operates through four segments: Owned/Leased Portfolio Shopping Malls; Managed Shopping Malls; Construction and decoration service; and Others. The company leases floor areas of shopping malls; operates as a construction contractor to develop and manage the shopping malls; and retails home furnishing merchandise, as well as offers related decorating services. It also provides initiation, consultation, and management services; and joint marketing, strategy consultation, home design consultation, construction service, internet home decoration, and internet retail services, as well as warehouse logistics services. The company was formerly known as Shanghai Red Star Macalline Home Living and Decorating Company Limited and changed its name to Red Star Macalline Group Corporation Ltd. in 2011. Red Star Macalline Group Corporation Ltd. was founded in 19…
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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.