Altshuler Shaham Finance Ltd (ALTF) Fair Value & Analysis
Financial Services · Il · Market cap 1.4B ILA
Fair value as of: Jun 26, 2026
Analysis
Altshuler Shaham Finance Ltd (ALTF) currently trades at 6.80 ILA, while our model-based Fair Value estimate is 4.20 ILA — implying the stock looks roughly 38.2% overvalued today. We read business quality at 93/100 (high quality), in the Financial 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
Altshuler Shaham Finance Ltd engages in the provident and pension funds management activities in Israel. The company manages savings provident funds, central severance pay provident funds, central provident funds for budgetary pension participation, as well as investment provident funds, which include children savings plan, and comprehensive pension funds and general pension funds. It is involved in the management of alternative real estate investments. The company was formerly known as A.S. Matrat Hanpaka Ltd and changed its name to Altshuler Shaham Finance Ltd in March 2022. Altshuler Shaham Finance Ltd was incorporated in 2001 and is based in Tel Aviv-Yafo, Israel. Altshuler Shaham Finance Ltd operates as a subsidiary of Altshuler Shaham Ltd.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is Altshuler Shaham Finance Ltd (ALTF) undervalued?
What is the fair value of ALTF?
What is the quality score of ALTF?
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.