Lasertec Corporation (LSRCF) Fair Value & Analysis
Technology · US · Market cap $30.0B
Analysis
Lasertec Corporation (LSRCF) currently trades at $318.90, while our model-based Fair Value estimate is $117.11 — implying the stock looks roughly 63.3% 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: high).
About the company
Lasertec Corporation engages in the design, manufacture, and sale of inspection and measurement equipment in Japan, South Korea, Taiwan, Other Asia, the United States. The company offers semiconductor related products, including Actinic EUV patterned mask inspection system, EUV mask blanks inspection and review system, mask inspection system, mask blanks inspection and review system, EUV pellicle inspection system, EUV mask backside inspection and cleaning system, and mask edge inspection system; phase-shift and transmittance measurement system, phase-shift measurement system; SiC wafer inspection and review system, GaN wafer inspection and review system, high sensitivity under-layer defect inspection and review system, multi-wavelength wafer inspection system, high sensitivity wafer edge inspection system, wafer edge-dimension measurement system, via depth measurement system, TSV back grinding process measurement system, and fully automated wafer measurement system. It also provide…
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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.