Fujian Torch Electron Technology Co (603678) Fair Value & Analysis
Technology · CN · Market cap 27.7B CNY
Fair value as of: Jun 24, 2026
Analysis
Fujian Torch Electron Technology Co (603678) currently trades at ¥65.19, while our model-based Fair Value estimate is ¥11.79 — implying the stock looks roughly 81.9% overvalued today. We read business quality at 90/100 (high quality), in the Technology 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
Fujian Torch Electron Technology Co., Ltd. engages in the research, development, production, sale, and servicing of electronic components, new materials, and related products in China and internationally. The company is involved in the sales in the automotive and new energy sectors; production and sales of machined parts; research and development of thin film capacitors and their supporting equipment production and sales; research and development, manufacturing, and sales of thermal management system. It also provides electronic, microwave, and optoelectronic components; and ceramic precursor materials. In addition, the company is involved in technology promotion and application services; investment activities; electroplating processing; and design of integrated circuits. Its products are used in various fields, such as consumer electronics, industrial control equipment, medical electronics, security, and other civilian sectors, as well as in aerospace and weaponry. The company was …
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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.