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Beijing Easpring Material Technology CO.,LTD., (300073) Fair Value & Analysis

Industrials · CN · Market cap 28.8B CNY

Price¥53.40
Fair Value¥25.23
Upside-52.8%
Quality90/100
Evidence: High Range ¥20.89 – ¥29.58

Analysis

Beijing Easpring Material Technology CO.,LTD., (300073) currently trades at ¥53.40, while our model-based Fair Value estimate is ¥25.23 — implying the stock looks roughly 52.8% overvalued today. We read business quality at 90/100 (high quality), in the Industrials 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

Beijing Easpring Material Technology CO.,LTD., together with its subsidiaries, engages in the research, development, production, and sale of lithium battery cathode materials and intelligent equipment products in China and internationally. The company offers lithium nickel cobalt manganese, lithium manganese iron phosphates, lithium iron phosphates, key materials for solid-state lithium-ion batteries, lithium cobalt oxides, and sodium-ion battery cathode materials for use in electric vehicles and bicycles, energy storage systems, laptops, power tools, smartphones, tablets, drones, and other fields. It also provides N series and S series rotary die-cutting, medical product die-cutting, electronic tag composite, laser die-cutting, and CCD testing equipment for use in the die-cutting production and processing of adhesive products for the electronics, automobile, packaging, printing, and medical and healthcare industries. In addition, the company is involved in investment management and…

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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.