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Telecom Italia S.p.A (TIAJF) Fair Value & Analysis

Communication Services · US · Market cap $20.5B

Price$0.9610
Fair Value$0.3500
Upside-63.6%
Quality90/100
Evidence: High Range $0.2000 – $0.3900

Analysis

Telecom Italia S.p.A (TIAJF) currently trades at $0.9610, while our model-based Fair Value estimate is $0.3500 — implying the stock looks roughly 63.6% overvalued today. We read business quality at 90/100 (high quality), in the Communication Services 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

Telecom Italia S.p.A., together with its subsidiaries, engages in the fixed and mobile telecommunications services and products for individuals, households, and supports small and medium-sized enterprises in Italy and internationally. It operates through Domestic, Brazil, and Other Operations segments. The company offers telephone and internet services, as well as products managed and developed in landline and mobile for individuals and families; voice, data, and internet services and products; and information and communications technology solutions for top, public sector and large account customers. It also provides connectivity services; mobile phone services and fiber optic data transmission using IP technology and residential broadband services; and internet of things services. Telecom Italia S.p.A. was incorporated in 1908 and is headquartered in Rome, 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.