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Skyline Investments Inc (SKLN) Fair Value & Analysis

Consumer Cyclical · Il · Market cap 40.1M ILA

Price2.27 ILA
Fair Value1.06 ILA
Upside-53.4%
Quality82/100
Evidence: Low Range 0.9700 ILA – 1.19 ILA

Fair value as of: Jun 26, 2026

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Analysis

Skyline Investments Inc (SKLN) currently trades at 2.27 ILA, while our model-based Fair Value estimate is 1.06 ILA — implying the stock looks roughly 53.4% overvalued today. We read business quality at 82/100 (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

Skyline Investments Inc. develops and operates real estate properties. The company was formerly known as Skyline International Development Inc. Skyline Investments Inc. was founded in 1998 and is based in Toronto, Canada with an additional office in Israel.

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Frequently asked questions

Is Skyline Investments Inc (SKLN) undervalued?
As of Jun 26, 2026, our model estimates a fair value of 1.06 ILA versus a price of 2.27 ILA — about −53% (overvalued). Model-based estimate, not financial advice.
What is the fair value of SKLN?
Our 21-model fair value for Skyline Investments Inc is 1.06 ILA (as of Jun 26, 2026), built from audited fundamentals. The current price is 2.27 ILA.
What is the quality score of SKLN?
Skyline Investments Inc has a Quality Score of 82/100, 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.