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Prysmian S.p.A (PRYMF) Fair Value & Analysis

Industrials · US · Market cap $51.8B

Price$172.36
Fair Value$95.47
Upside-44.6%
Quality94/100
Evidence: High Range $52.91 – $122.05

Analysis

Prysmian S.p.A (PRYMF) currently trades at $172.36, while our model-based Fair Value estimate is $95.47 — implying the stock looks roughly 44.6% overvalued today. We read business quality at 94/100 (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

Prysmian S.p.A., together with its subsidiaries, produces, distributes, and sells power and telecom cables and systems, and related accessories under the Prysmian, Draka, and General Cable brands worldwide. It operates through four segments: Transmission, Power Grid, Electrification, and Digital Solutions. The company offers high voltage direct current (HVDC), network component high voltage, submarine power, submarine telecom, offshore specialties, and EOSS high voltage units. It also provides power distribution, overhead lines, high voltage alternate current (HVAC), network component medium voltage/low voltage, EOSS medium voltage/low voltage units. In addition, it offers electrification products; and fiber optics, optical cables, connectivity components and accessories, optical ground wire cables, and copper cables. Further, it manufactures and sells thermoplastic and metal enclosures. Prysmian S.p.A. was founded in 1879 and is headquartered in Milan, Italy.

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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.