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Piippo Oyj (PIIPPO) Fair Value & Analysis

Consumer Cyclical · FI · Market cap €2.2M

Price€1.66
Fair Value€1.01
Upside-39.2%
Quality95/100
Evidence: Low Range €0.7500 – €1.50

Fair value as of: Jun 25, 2026

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Analysis

Piippo Oyj (PIIPPO) currently trades at €1.66, while our model-based Fair Value estimate is €1.01 — implying the stock looks roughly 39.2% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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

Piippo Oyj develops, manufactures, and sells baling net wraps and baling twines for farmers in Finland. The company offers bale netwraps, such as hybrid edge master and other net wraps; baler twine products, including big square, conventional, and round bailing, as well as slash bundler twines; and ropes and twines. Piippo Oyj was founded in 1942 and is based in Outokumpu, Finland.

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Frequently asked questions

Is Piippo Oyj (PIIPPO) undervalued?
As of Jun 25, 2026, our model estimates a fair value of €1.01 versus a price of €1.66 — about −39% (overvalued). Model-based estimate, not financial advice.
What is the fair value of PIIPPO?
Our 21-model fair value for Piippo Oyj is €1.01 (as of Jun 25, 2026), built from audited fundamentals. The current price is €1.66.
What is the quality score of PIIPPO?
Piippo Oyj has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.