Aurizon Holdings (AZJ) Fair Value & Analysis
Industrials · AU · Market cap A$7.2B
Analysis
Aurizon Holdings (AZJ) currently trades at A$4.23, while our model-based Fair Value estimate is A$2.69 — implying the stock looks roughly 36.4% overvalued today. We read business quality at 95/100 (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: high).
About the company
Aurizon Holdings Limited, together with its subsidiaries, engages in the freight business in Australia. It operates through Network, Coal, Bulk, and Other segments. The company operates and manages the Central Queensland Coal Network that consists of 2,670 kilometers of track network; and the South Australia and Northern Territory Network that consists of 2,100 kilometers of track network. It also transports metallurgical and thermal coal; retail and supermarket essentials, refrigerated goods, vehicles, and machinery and equipment; and other commodities, such as iron ore, cement, bauxite, alumina, base metals, grain, fertiliser, and dangerous goods. In addition, the company provides network maintenance; supply chain services, including rail and road transportation, port services, and material handling; and landbridging and containerised freight solutions. It serves mining, metal, industrial, and agricultural customers. The company was formerly known as QR National Limited and change…
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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.