Tasmea Limited (TEA) Fair Value & Analysis
Industrials · AU · Market cap A$2.2B
Analysis
Tasmea Limited (TEA) currently trades at A$9.03, while our model-based Fair Value estimate is A$4.01 — implying the stock looks roughly 55.6% 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
Tasmea Limited provides shutdown, maintenance, emergency breakdown, and capital upgrade services in Australia. It operates through four segments: Electrical, Mechanical, Civil, and Water & Fluid. The Electrical segment offers remote area specialist services in industrial and commercial electrical and instrumentation services, maintenance and compliance of electrical assets, and indigenous trade services. The Mechanical segment provides remote area specialist services in industrial and commercial refurbishment and repairs, shutdown, and mechanical maintenance. The Civil segment offers remote area specialists in commercial earthworks, waste management, and civil maintenance. The Water & Fluid segment provides remote area specialist services in industrial and commercial geomembrane solutions, lubrication solutions and maintenance, and drainage solutions. It serves mining and resources, oil and gas, power and renewables, defense and infrastructure, and water industries. Tasmea Limited w…
Open the full interactive analysis →
Similar stocks
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.