Gilat Telecom Global Ltd (GLTL) Fair Value & Analysis
Communication Services · Il · Market cap 317M ILA
Fair value as of: Jun 24, 2026
Analysis
Gilat Telecom Global Ltd (GLTL) currently trades at 2.38 ILA, while our model-based Fair Value estimate is 1.20 ILA — implying the stock looks roughly 49.6% overvalued today. We read business quality at 95/100 (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
Gilat Telecom Global Ltd provides communication services through satellite and fiber optic infrastructures, and radio systems in Israel and internationally. It operates through Global business market, Government and security market, and Communication and Internet in Israel segments. The company offers data communication services including connection and infrastructure services for the Internet network, establishment and operation of internal corporate data communication networks, and management of the communication infrastructure of Internet providers and cellular operators; and consulting and characterization of networks and communication solutions on the fiber and satellite infrastructure, including the sale of equipment, installation, routine maintenance, and operation. It also provides mobile satellite communication services comprises, supply of equipment, data communication and telephony services, and related services. In addition, the company offers broadband connectivity and …
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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.