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Bichamp Cutting Technology (Hunan) Co (002843) Fair Value & Analysis

Industrials · CN · Market cap 5.6B CNY

Price¥21.58
Fair Value¥8.28
Upside-61.6%
Quality95/100
Evidence: Medium Range ¥6.17 – ¥10.40

Analysis

Bichamp Cutting Technology (Hunan) Co (002843) currently trades at ¥21.58, while our model-based Fair Value estimate is ¥8.28 — implying the stock looks roughly 61.6% overvalued today. We read business quality at 95/100 (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: medium).

About the company

Bichamp Cutting Technology (Hunan) Co., Ltd. engages in the sawing and energy businesses in China. The company offers sawing tools, such as bimetal and carbide band saw blades that are used in automobile manufacturing, forging, aerospace, steel metallurgy, wind and nuclear power, rail transit, and machinery manufacturing applications. It also provides power solutions used in electric vehicle charging piles, smart photovoltaic power generation, energy storage, OBC, and other fields; open frame, enclosed, and configurable modules used in industrial robots, displays, and lighting equipment, as well as imaging, analysis laboratory, clinical, and other medical fields; power supply products used in communication equipment, data centers, computer systems, and other fields; and wireless charging solutions used in the consumer electronics industry. The company was founded in 2003 and is headquartered in Changsha, China.

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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.