Longxing Technology Group (002442) Fair Value & Analysis
Basic Materials · CN · Market cap 2.6B CNY
Fair value as of: Jun 25, 2026
Analysis
Longxing Technology Group (002442) currently trades at ¥5.64, while our model-based Fair Value estimate is ¥1.34 — implying the stock looks roughly 76.2% overvalued today. We read business quality at 95/100 (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
Longxing Technology Group Co., Ltd. produces and sells carbon black products under the Longxing brand in China. The company offers carbon black, silica, and coal tar products. Its carbon black is used for the production of steel and semi-steel radial tires and inner tubes; and used in door and window sealing strips, oil pipes, shock absorbers, brake pads, and other auto parts, as well as rubbers, building materials, electronics, paper, plastics, color master batches, paint, fuel, chemical fibers, coloring of fiber, ink, wash painting, and papermaking. The company's white carbon black is used in tires and product industries for reinforcement and filling; and feed-grade silica is used in the feed additive industry to act as a carrier, glidant, and anti-caking. It also engages in the energy business. The company was formerly known as Longxing Chemical Stock Co., Ltd. and changed its name to Longxing Technology Group Co., Ltd. in January 2025. Longxing Technology Group Co., Ltd. was fou…
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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.