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SOS Lab Co (464080) Fair Value & Analysis

Technology · KR · Market cap 215B KRW

Price10,000 KRW
Fair Value8,976 KRW
Upside-10.2%
Quality95/100
Evidence: Low Range 6,732 KRW – 11,220 KRW

Fair value as of: Jun 24, 2026

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Analysis

SOS Lab Co (464080) currently trades at 10,000 KRW, while our model-based Fair Value estimate is 8,976 KRW — implying the stock looks roughly 10.2% 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

SOS Lab Co., Ltd. manufactures and sells optical sensors in South Korea. It offers mobility LiDAR sensor for automotive and autonomous driving; and GL sensor for industrial robots and factory automation. The company was founded in 2016 and is based in Gwangju-si, South Korea.

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Frequently asked questions

Is SOS Lab Co (464080) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 8,976 KRW versus a price of 10,000 KRW — about −10% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 464080?
Our 21-model fair value for SOS Lab Co is 8,976 KRW (as of Jun 24, 2026), built from audited fundamentals. The current price is 10,000 KRW.
What is the quality score of 464080?
SOS Lab Co 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.