Korea Movenex Co (010100) Fair Value & Analysis
Consumer Cyclical · KR · Market cap 118B KRW
Fair value as of: Jun 25, 2026
Analysis
Korea Movenex Co (010100) currently trades at 3,570 KRW, while our model-based Fair Value estimate is 10,275 KRW — implying the stock looks roughly 187.8% undervalued today. We read business quality at 90/100 (high quality), in the Consumer Cyclical sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Korea Movenex Co., Ltd., together with its subsidiaries, manufactures and sells automobile parts, flanges, and industrial machinery worldwide. It offers automobile drive parts, such as half shafts and front axle assemblies for passenger cars; and front axle and brake assemblies for buses and trucks. The company also provides front/rear axle and brake complete ass'y, rear axles, inner shafts, crank shafts, and connecting rods for commercial vehicles and ships; and various types of flanges, including carbon steel, non-ferrous, ANSI, AWWA, AOI, MSS, and others. In addition, it offers power plants, ship structures, chemical plant steel structures, pressure vessels, bridges, and various construction-related projects, as well as tanks and heat exchangers. The company was formerly known as Korea Flange Co., Ltd. and changed its name to Korea Movenex Co., Ltd. in March 2023. Korea Movenex Co., Ltd. was founded in 1974 and is headquartered in Ulsan, South Korea.
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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.