Scage Future, (SCAG) Fair Value & Analysis
Industrials · US · Market cap $27.3M
Fair value as of: Jun 24, 2026
Analysis
Scage Future, (SCAG) currently trades at $0.3536, while our model-based Fair Value estimate is $0.3200 — implying the stock looks roughly 9.5% overvalued today. We read business quality at 91/100 (high quality), in the Industrials 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
Scage Future, together with its subsidiaries, develops and commercializes heavy-duty new electric vehicle (NEV) trucks and e-fuel solutions in the People's Republic of China. The company offers Dragon King, a plug-in hybrid dump truck for mining, and other heavy-duty loading and offloading applications; Galaxy II, a plug-in hybrid truck for long-distance road transportation and logistics service applications; Q-truck, an autonomous tractor trailer for smart transportation; Andromeda, an all-electric semi-tractor truck for road and port transportation; Andromeda+, a hydrogen-electric hybrid semi-tractor truck for long-distance road and port transportation; and Sky Turtle, an unmanned plug-in hybrid dump truck for off-road mining. It also provides farm tractors, all-electric port tractors, long-endurance hybrid power tractors, and wide-body and high-power hybrid mining vehicles; vehicle parts and components, including flat wire motors, two-speed gearboxes, motor and integrated vehicle…
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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.