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oToBrite Electronics, Inc (2256) Fair Value & Analysis

Consumer Cyclical · TW · Market cap 2.9B TWD

Price73.30 TWD
Fair Value12.72 TWD
Upside-82.6%
Quality95/100
Evidence: Low Range 9.54 TWD – 15.90 TWD

Fair value as of: Jun 24, 2026

Analysis

oToBrite Electronics, Inc (2256) currently trades at 73.30 TWD, while our model-based Fair Value estimate is 12.72 TWD — implying the stock looks roughly 82.6% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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

oToBrite Electronics, Inc. engages in developing driver safety system products and artificial intelligence technologies in Taiwan. The company provides vehicle cameras and driver assistance systems. oToBrite Electronics, Inc. was founded in 2013 and is based in Hsinchu City, Taiwan.

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Frequently asked questions

Is oToBrite Electronics, Inc (2256) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 12.72 TWD versus a price of 73.30 TWD — about −83% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 2256?
Our 21-model fair value for oToBrite Electronics, Inc is 12.72 TWD (as of Jun 24, 2026), built from audited fundamentals. The current price is 73.30 TWD.
What is the quality score of 2256?
oToBrite Electronics, Inc has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.