Austin Engineering Limited (ANG) Fair Value & Analysis
Industrials · AU · Market cap A$109M
Fair value as of: Jun 26, 2026
Analysis
Austin Engineering Limited (ANG) currently trades at A$0.1400, while our model-based Fair Value estimate is A$0.5500 — implying the stock looks roughly 292.9% undervalued today. We read business quality at 95/100 (high quality), in the Industrials 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
Austin Engineering Limited, together with its subsidiaries, manufactures, repairs, overhauls, and supplies mining attachment products, and other related products and services for the industrial and resources-related business sectors. The company offers buckets, such as back hoe, wheel loader, hydraulic loading shovels, rope shovel dipper, and underground LHD; and dump bodies, underground dump bodies, tyre handlers, ancillary products, and water tanks. It also provides on and off site repair and maintenance services, including specialized site machining, specialized fabrication and welding, specialized machining, on-site machining of ball and crusher mill tyre, metal spraying, NDT testing, service and exchange parts, and heavy equipment reclamation services, as well as manufacturing and supply of pins and bushes. It operates in Australia, Chile, the United States, Canada, Indonesia, and internationally. The company was founded in 1982 and is headquartered in Kewdale, 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.