Focuslight Technologies Inc (688167) Fair Value & Analysis
Technology · CN · Market cap 43.2B CNY
Analysis
Focuslight Technologies Inc (688167) currently trades at ¥374.99, while our model-based Fair Value estimate is ¥51.19 — implying the stock looks roughly 86.3% overvalued today. We read business quality at 95/100 (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: low).
About the company
Focuslight Technologies Inc. engages in the research and development, production, sale and lease of semiconductor laser components and laser optics components in China and internationally. It offers diode laser materials, include AuSn Pre-Deposited AlN Ceramic Substrates and AuSn Pre-Deposited CuW Substrates; diode laser components, such as single emitter and bar components, micro-channel cooled stacks, conduction cooled stacks, pumped modules, fiber coupled modules, coated fibers, and patch cords; and micro-optical components, including single cylindrical lenses, microlens arrays and assemblies, v-groove arrays, etched mirco-optics, wafer-level-optics (WLO), wafer-level-stacking (WLS), precision molded optics, and high-damage-threshold coating and optics. The company also provides automotive application solutions includes flash and line beam lidar transmitters, VSCEL illuminators, beam shaping solutions, and lidar optical assembly; IC, display, glass, solar cell, and lithium batter…
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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.