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Sleeping Giant Capital Corp (SSX) Fair Value & Analysis

Energy · CA · Market cap C$640K

PriceC$0.0500
Fair ValueC$0.0300
Upside-40.0%
Quality95/100
Evidence: Low Range C$0.0300 – C$0.0350

Fair value as of: Jun 26, 2026

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Analysis

Sleeping Giant Capital Corp (SSX) currently trades at C$0.0500, while our model-based Fair Value estimate is C$0.0300 — implying the stock looks roughly 40.0% overvalued today. We read business quality at 95/100 (high quality), in the Energy 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

Sleeping Giant Capital Corp. operates as an oil and gas company. It holds interests in oil and gas assets in the Gilby, Niton, Rosebud, Prevo, and Sylvan Lake regions. The company was incorporated in 2021 and is based in Calgary, Canada.

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Frequently asked questions

Is Sleeping Giant Capital Corp (SSX) undervalued?
As of Jun 26, 2026, our model estimates a fair value of C$0.0300 versus a price of C$0.0500 — about −40% (overvalued). Model-based estimate, not financial advice.
What is the fair value of SSX?
Our 21-model fair value for Sleeping Giant Capital Corp is C$0.0300 (as of Jun 26, 2026), built from audited fundamentals. The current price is C$0.0500.
What is the quality score of SSX?
Sleeping Giant Capital Corp has a Quality Score of 95/100, 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.