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Guangdong Jialong Food Co (002495) Fair Value & Analysis

Consumer Defensive · CN · Market cap 2.1B CNY

Price¥2.20
Fair Value¥0.5900
Upside-73.2%
Quality95/100
Evidence: High Range ¥0.5200 – ¥0.6600

Fair value as of: Jun 25, 2026

Analysis

Guangdong Jialong Food Co (002495) currently trades at ¥2.20, while our model-based Fair Value estimate is ¥0.5900 — implying the stock looks roughly 73.2% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Defensive 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

Guangdong Jialong Food Co., Ltd. researches, develops, produces, and sells condiments and related food products in China. The company offers chicken powder, essence, juice, and other chicken products, as well as tomato sauce, custard powder, green mustard sauce, and corn japonica. It offers its products under the Jialong, Fuwei, Gangchu, Taitaichu, Shiqiu, Jiafeng, and EAS brands. Guangdong Jialong Food Co., Ltd. was founded in 2002 and is based in Puning, China.

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Frequently asked questions

Is Guangdong Jialong Food Co (002495) undervalued?
As of Jun 25, 2026, our model estimates a fair value of ¥0.5900 versus a price of ¥2.20 — about −73% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 002495?
Our 21-model fair value for Guangdong Jialong Food Co is ¥0.5900 (as of Jun 25, 2026), built from audited fundamentals. The current price is ¥2.20.
What is the quality score of 002495?
Guangdong Jialong Food Co 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.