Grupo Rotoplas S.A. (AGUA) Fair Value & Analysis
Industrials · MX · Market cap 6.2B MXN
Fair value as of: Jun 24, 2026
Analysis
Grupo Rotoplas S.A. (AGUA) currently trades at 13.19 MXN, while our model-based Fair Value estimate is 10.57 MXN — implying the stock looks roughly 19.9% 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
Grupo Rotoplas S.A.B. de C.V., together with its subsidiaries, manufactures, purchases, sells, and installs plastic containers and accessories for water storage, conduction, and improvement solutions in Mexico, Argentina, the United States and internationally. It operates through Individual Solutions and Comprehensive Solutions segments. The company offers storage solutions, water tanks, cisterns, rural rainwater collector, urban rain collector, rotoplas accessories, water conditioning device, tamboplas, reservoirs, rainwater collection system, tank accessories. It provides agroindustry solutions, such as storage tank, hoppers, mother tank, feeders and drinkers, closed vertical tank, indoor water tanks outdoor water tanks, horizontal water tanks, firefighting water tanks, banjo accessories, bilayer tank, wet nurses, feeders and drinkers, and closed vertical tanks. The company also provides hydraulic pipe tubes, connections and tools and hydraulic installation used in single-family, …
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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.