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Forest Packaging Group (605500) Fair Value & Analysis

Consumer Cyclical · CN · Market cap 2.9B CNY

Price¥6.64
Fair Value¥3.10
Upside-53.3%
Quality90/100
Evidence: Medium Range ¥2.33 – ¥3.88

Fair value as of: Jun 24, 2026

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Analysis

Forest Packaging Group (605500) currently trades at ¥6.64, while our model-based Fair Value estimate is ¥3.10 — implying the stock looks roughly 53.3% overvalued today. We read business quality at 90/100 (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: medium).

About the company

Forest Packaging Group Co.,Ltd., together with its subsidiaries, engages in the manufacturing and selling of packaging papers products in China and internationally. It offers corrugated and gift box, as well as paper bag. The company was founded in 1997 and is based in Wenling, China.

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Frequently asked questions

Is Forest Packaging Group (605500) undervalued?
As of Jun 24, 2026, our model estimates a fair value of ¥3.10 versus a price of ¥6.64 — about −53% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 605500?
Our 21-model fair value for Forest Packaging Group is ¥3.10 (as of Jun 24, 2026), built from audited fundamentals. The current price is ¥6.64.
What is the quality score of 605500?
Forest Packaging Group has a Quality Score of 90/100, 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.