Interpump Group (IPGLF) Fair Value & Analysis
Industrials · US · Market cap $5.4B
Analysis
Interpump Group (IPGLF) currently trades at $51.00, while our model-based Fair Value estimate is $45.47 — implying the stock looks roughly 10.8% 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
Interpump Group S.p.A., together with its subsidiaries, engages in the manufacturing and selling of high-pressure pumps in Italy, rest of Europe, North America, the Far East and the Pacific Area, and internationally. The company is involved in the design and distribution of volumetric pumps; production, sale, and distribution of pressure systems and pumps; production of mechanical sifters; production and sale of equipment for the food processing, chemicals, cosmetics, and pharmaceuticals industries; galvanic treatment of metals; and sale of centrifugal separators. It also engages in drawing, shearing, and pressing sheet metal; design, production, and sale of mechanized milking systems; production and sale of power take-offs, hydraulic pumps, hydraulic cylinders, valves, rotary unions, hydraulic hoses, and fittings, as well as rubber mixtures, rigid and flexible hydraulic lines, and directional controls; sale of ancillary products for industrial vehicles; surface treatments; and smel…
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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.