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T-Robotics.Co., Ltd (117730) Fair Value & Analysis

Technology · KR · Market cap 315B KRW

Price13,690 KRW
Fair Value4,820 KRW
Upside-64.8%
Quality93/100
Evidence: Medium Range 3,615 KRW – 6,025 KRW

Fair value as of: Jun 24, 2026

Analysis

T-Robotics.Co., Ltd (117730) currently trades at 13,690 KRW, while our model-based Fair Value estimate is 4,820 KRW — implying the stock looks roughly 64.8% overvalued today. We read business quality at 93/100 (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: medium).

About the company

T-Robotics.Co., Ltd. engages in the development, production, and sale of robots in South Korea, China, the United States, and internationally. It offers vacuum transport robots, autonomous driving robots, and human support robots. The company was founded in 2004 and is headquartered in Osan-si, South Korea.

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Frequently asked questions

Is T-Robotics.Co., Ltd (117730) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 4,820 KRW versus a price of 13,690 KRW — about −65% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 117730?
Our 21-model fair value for T-Robotics.Co., Ltd is 4,820 KRW (as of Jun 24, 2026), built from audited fundamentals. The current price is 13,690 KRW.
What is the quality score of 117730?
T-Robotics.Co., Ltd has a Quality Score of 93/100, 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.