Wuling Motors Holdings (WLMTF) Fair Value & Analysis
Consumer Cyclical · US · Market cap $195M
Fair value as of: Jun 26, 2026
Analysis
Wuling Motors Holdings (WLMTF) currently trades at $0.0502, while our model-based Fair Value estimate is $0.0652 — implying the stock looks roughly 29.8% undervalued today. We read business quality at 80/100 (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: medium) — always confirm before acting.
About the company
Wuling Motors Holdings Limited, an investment holding company, engages in trading and manufacturing of automotive components, vehicles' power supply systems,engines, and specialized vehicles in the People's Republic of China and internationally. It operates through Vehicles' Power Supply Systems; Automotive Components and Other Industrial Services; Commercial Vehicles Assembly; and Others segments. It offers specialized vehicles, which includes new energy, specialized vehicles, and non-road vehicles; and powertrain systems including plug-in hybrid electric drive system, range-extender, driving motor, and motor controllers. It also provides a range of auto parts comprising chassis products, such as gear, rear torsion beam and independent suspension assembly, muffler exhaust assembly, three-way catalytic converter package, front and rear sub-frame, micro commercial electric drive bridge, integrated bridge, rear axle final drive, coaxial powertrain, and integral coaxial bridge; and int…
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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.