SciDev Limited (SDV) Fair Value & Analysis
Basic Materials · AU · Market cap A$16.5M
Fair value as of: Jun 26, 2026
Analysis
SciDev Limited (SDV) currently trades at A$0.1250, while our model-based Fair Value estimate is A$0.0713 — implying the stock looks roughly 43.0% overvalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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: medium).
About the company
SciDev Limited engages in the provision of environmental solutions focused on water intensive industries in Australia, the United States, Asia, and internationally. The company operates in two segments, Chemical Services and Water Technologies. It develops, manufactures, and supplies proprietary chemicals, including natural and synthetic polymers for flocculation, filtration, sludge dewatering, friction reduction, shale inhibition, rheology control, and pipe-on-pipe lubrication applications; flocculants and coagulants; and provides services, such as design and engineering, process optimization, specialty chemical fluid formulations, and application equipment, as well as project management services. The company also offers water treatment technologies comprising water treatment for mobile, temporary, and permanent treatment systems; PFAS treatment solutions; onsite liquid waste treatment services; and water quality monitoring systems. It serves its products to mining and minerals pro…
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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.