Orcoda Limited (ODA) Fair Value & Analysis
Industrials · AU · Market cap A$8.1M
Fair value as of: Jun 26, 2026
Analysis
Orcoda Limited (ODA) currently trades at A$0.1150, while our model-based Fair Value estimate is A$0.0500 — implying the stock looks roughly 56.5% 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: low).
About the company
Orcoda Limited, together with its subsidiaries, provides smart technology transport logistics and contracting services in Australia and internationally. The company operates through two segments, Transport Technology, and Resource and Infrastructure. It offers Orcoda Workforce Logistics System platform that manages people, places, and processes on infrastructure and resources projects for which visibility and control over the whole work team and assets; and a transportation management system. The company also provides fleet management and optimization via the Transport360 platform with a front-end booking platform for transport logistics and healthcare transport providers; Orcoda Community Transport for community transport providers; Orcoda Connect for carpooling; and Orcoda GO for turn-by-turn navigation. It serves mining, oil and gas, truck and transportation, bus and coach, and healthcare industries, as well as corporate and government. The company was formerly known as SmartTran…
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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.