Anhui Estone Materials Technology Co (688733) Fair Value & Analysis
Basic Materials · CN · Market cap 7.8B CNY
Analysis
Anhui Estone Materials Technology Co (688733) currently trades at ¥46.20, while our model-based Fair Value estimate is ¥47.49 — implying the stock looks roughly 2.8% undervalued today. We read business quality at 95/100 (high quality), in the Basic Materials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: low) — always confirm before acting.
About the company
Anhui Estone Materials Technology Co.,Ltd, together with its subsidiaries, engages in the research, development, production, and sale of advanced inorganic non-metallic composites in China and internationally. The company offers coating materials for electrode plates and separators in lithium batteries; electronic communication functional filling materials, including chip packaging, 5G high-frequency and high-speed copper clad laminate functional filling materials, silicone rubber functional fillers, electronic ink functional filling materials, and thermal interface materials; low smoke halogen-free flame retardant materials comprising environmentally friendly flame retardant for low-smoke halogen-free B1 sheath materials, smoke suppression char-forming agents, ceramic flame retardants, and ceramic products; opening agent solutions that include soft silicon and spherical silicon dioxide; and ceramic parts, such as alumina, zirconia, and aluminum nitride structural components. It als…
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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.