Luminescence Technology Corp (6729) Fair Value & Analysis
Basic Materials · TW · Market cap 1.5B TWD
Fair value as of: Jun 24, 2026
Analysis
Luminescence Technology Corp (6729) currently trades at 54.50 TWD, while our model-based Fair Value estimate is 14.16 TWD — implying the stock looks roughly 74.0% overvalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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
Luminescence Technology Corp. manufactures and sells organic chemicals in North America, Europe, Asia, and Taiwan. It offers organic light emitting diode (OLED) materials, thermally activated delayed fluorescent (TADF), polymers, and small molecular and polymer solution processed OLED materials; organic photovoltaic (OPV) materials, including small small molecular and oligomer, polymer, hole transport and electron transport, self-assembled monolayers, perovskite solar cells, and dye-sensitized solar cell materials; organic photodiodes and perovskite-based photodiodes, including organic photodiodes (OPD) materials, and perovskite-based photodiodes (PPD) materials; organic thin-film transistor and organic field-effect transistor, comprising small molecular and oligomer materials, and polymer materials; flexible printed electronics, such as organic photovoltaic, OTFT and OFET, hole transport and hole injection layer, host layer, light-emitting layer, and electron transport hole blockin…
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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.