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Jiangsu Leadmicro Nano-Equipment Technology Ltd (688147) Fair Value & Analysis

Technology · CN · Market cap 43.9B CNY

Price¥109.11
Fair Value¥13.58
Upside-87.6%
Quality95/100
Evidence: High Range ¥10.02 – ¥16.64

Analysis

Jiangsu Leadmicro Nano-Equipment Technology Ltd (688147) currently trades at ¥109.11, while our model-based Fair Value estimate is ¥13.58 — implying the stock looks roughly 87.6% 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

Jiangsu Leadmicro Nano-Equipment Technology Ltd engages in manufacturing high-end micro-nano equipment for semiconductor and pan-semiconductor. It focuses on the research, development, production, and application of advanced micron-level and nanoscale thin film equipment. The company's business covers integrated circuits, photovoltaics, LEDs, and MEMS, as well as new energy and flexible electronics fields. Its products include specialized equipment and complete technology packages for semiconductors and pan-semiconductors, such as logic chips, memory chips, photovoltaic cells, silicon-based micro-displays, compound semiconductors, and 3D packaging, as well as mass production solutions for flexible electronics and a range of high-efficiency solar cells. Jiangsu Leadmicro Nano-Equipment Technology Ltd was founded in 2015 and is based in Wuxi, 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.