Lushang Freda Pharmaceutical Co (600223) Fair Value & Analysis
Real Estate · CN · Market cap 5.8B CNY
Analysis
Lushang Freda Pharmaceutical Co (600223) currently trades at ¥5.26, while our model-based Fair Value estimate is ¥5.30 — implying the stock looks roughly 0.8% undervalued today. We read business quality at 80/100 (high quality), in the Real Estate 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: medium) — always confirm before acting.
About the company
Lushang Freda Pharmaceutical Co.,Ltd. engages in the research, development, production, and sales of cosmetics, pharmaceuticals, raw materials, and additives in China. It is involved in property management services. The company provides facial cleansers, lotions, creams, sprays, masks, and other products. It also offers products in the field of dermatology, orthopedics, ophthalmology, gynecology, and pediatrics, respiratory, endocrinology, andrology, tonic, and plasters, as well as hyaluronic acid and its derivatives, bio-fermentation, plant extracts, chemical synthesis, tablets, capsules, drinks, injections, granules, and other products. The company offers its products through online and offline channels. It exports its products to North America, the European Union, Japan, South Korea, and Southeast Asia. The company was formerly known as Lushang Health Industry Development Co.,Ltd. and changed its name to Lushang Freda Pharmaceutical Co.,Ltd. in April 2023. The company was founded…
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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.