Motonic Corporation (009680) Fair Value & Analysis
Consumer Cyclical · KR · Market cap 219B KRW
Fair value as of: Jun 25, 2026
Analysis
Motonic Corporation (009680) currently trades at 9,490 KRW, while our model-based Fair Value estimate is 19,092 KRW — implying the stock looks roughly 101.2% undervalued today. We read business quality at 95/100 (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
Motonic Corporation manufactures and sells automotive components worldwide. The company offers high pressure regulators, receptacle, and manifolds; LPDI high-pressure fuel pumps, and low-pressure fuel pumps and drivers; LPI systems comprising pump modules, injection modules, regulators, and drivers; oil pump control units and fuel pump controllers; and variable valve lifts. It also provides electronic-cylinder deactivation actuators and electronic-variable valve lifts; aluminum alloy, stainless steel, plastic, and high pressure rails; oil pumps; GDI high-pressure fuel pumps; EGR valves; and air induction components comprising intake manifolds, throttle bodies, and air control valves. In addition, the company offers LPG bi-fuel systems, including regulators, cut-off solenoids, ECUs, and injectors; rocker arms; and gas filters, switch and level gauges, waste gate actuators, control units, piston clutches, and LPG mixer systems. The company was formerly known as Changwon Carburetor Ind…
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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.