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Jinli Group (8429) Fair Value & Analysis

Consumer Cyclical · TW · Market cap 1.2B TWD

Price6.34 TWD
Fair Value2.56 TWD
Upside-59.6%
Quality95/100
Evidence: High Range 1.92 TWD – 3.20 TWD

Fair value as of: Jun 24, 2026

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Analysis

Jinli Group (8429) currently trades at 6.34 TWD, while our model-based Fair Value estimate is 2.56 TWD — implying the stock looks roughly 59.6% 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

Jinli Group Holdings Limited, an investment holding company, manufacturing and sales of footwear and wholesale of clothing in China. It operates through Shoes and Garment; and Cosmetics segments. The company offers leisure sports, jeans, casual wear, casual shoes, face masks, accessories, and skin care products. It also sells its products through agents and footwear traders. The company provides its products under Gold Apple; e.t casual wear; and MegustaMe care beauty makeup brand names. Jinli Group Holdings Limited was incorporated in 2010 and is based in Kaohsiung, Taiwan.

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Frequently asked questions

Is Jinli Group (8429) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 2.56 TWD versus a price of 6.34 TWD — about −60% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 8429?
Our 21-model fair value for Jinli Group is 2.56 TWD (as of Jun 24, 2026), built from audited fundamentals. The current price is 6.34 TWD.
What is the quality score of 8429?
Jinli Group has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.