C.T.I. Traffic Industries Co (2230) Fair Value & Analysis
Consumer Cyclical · TW · Market cap 1.8B TWD
Fair value as of: Jun 25, 2026
Analysis
C.T.I. Traffic Industries Co (2230) currently trades at 26.20 TWD, while our model-based Fair Value estimate is 8.98 TWD — implying the stock looks roughly 65.7% overvalued today. We read business quality at 94/100 (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
C.T.I. Traffic Industries Co., Ltd. manufactures and sells engine parts in Taiwan and internationally. It offers starter batteries, energy storage systems, green power products, and jump starter products. The company also provides DLC piston rings, comprising black diamond piston rings; gasoline piston ring-oil rings; and chrome, nitriding, and phosphate diesel ring-oil rings. In addition, it offers timing kits and components, such as automotive timing kits, car timing guides, timing guides and chains, tensioners, and cam and crank gears; overhaul engine gaskets, including CYL heads, cylinder head gaskets, intake manifolds, exhaust manifolds, pipe manifolds, automotive oil seals, engine oil seals, oil seals, valve covers, oil pans, valve stem seals, and engine valve seals; liner and piston kits; and engine valves, which consist of auto engine valves, engine valve seats, engine bearings, and engine valve guides; and carburetor kits. Further, the company provides compression rings, in…
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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.