Kingenta Ecological Engineering Group (002470) Fair Value & Analysis
Basic Materials · CN · Market cap 7.4B CNY
Analysis
Kingenta Ecological Engineering Group (002470) currently trades at ¥2.17, while our model-based Fair Value estimate is ¥0.4400 — implying the stock looks roughly 79.7% overvalued today. We read business quality at 94/100 (high quality), in the Basic Materials 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
Kingenta Ecological Engineering Group Co., Ltd., together with its subsidiaries, research, develops, produces, and sells agricultural fertilizers and raw materials in China. The company offers various products, such as compound, phosphate, controlled-release, nitro, water soluble, and microbial fertilizers. It also trades, imports, and exports chemical fertilizers, raw materials, pesticides, herbicides, foliar fertilizers, and bio stimulants. In addition, the company engages in phosphogypsum products; technical services; investment consulting; phosphate mining; technology and technical development; agricultural and business investment; agricultural services; investment; technical training; food production and processing; planting; financing; soil remediation technology; sale of culture media and plant protection products; and lease activities. The company was formerly known as Shandong Kingenta Ecological Engineering Co.,Ltd. and changed its name to Kingenta Ecological Engineering G…
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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.