Advanced Braking Technology Limited (ABV) Fair Value & Analysis
Consumer Cyclical · AU · Market cap A$45.8M
Fair value as of: Jun 26, 2026
Analysis
Advanced Braking Technology Limited (ABV) currently trades at A$0.1050, while our model-based Fair Value estimate is A$0.0700 — implying the stock looks roughly 33.3% overvalued today. We read business quality at 95/100 (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: high).
About the company
Advanced Braking Technology Limited engages in the research, design, development, manufacture, distribution, and sale of braking solutions worldwide. The company offers brakes for light, medium, and heavy vehicles; and ABT failsafe brakes, ABT failsafe emergency driveline brakes, and associated braking systems. It also provides BrakeSAFE Wheel End SIBS Brakes, a sealed wet brakes with spring applied hydraulic release mechanism and optional interlocks that eliminates the risk of unintended vehicle movement; BrakeSAFE Driveline SIBS Brakes which act as a supplementary system for critical situations that provides rapid intervention, and preventing unintended vehicle movements during service break failure; and BRAKEiQ, an auto braking system designed to integrate with collision avoidance systems. The company serves mining, defense, civil construction, and waste management industries. Advanced Braking Technology Limited was founded in 1992 and is headquartered in Wangara, Australia.
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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.