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American Nortel Communications, Inc (ARTM) Fair Value & Analysis

Communication Services · US · Market cap $5.0M

Price$0.0879
Fair Value$0.0100
Upside-88.6%
Quality95/100
Evidence: Low

Fair value as of: Jun 24, 2026

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Analysis

American Nortel Communications, Inc (ARTM) currently trades at $0.0879, while our model-based Fair Value estimate is $0.0100 — implying the stock looks roughly 88.6% 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: low).

About the company

American Nortel Communications, Inc. provides telecommunications services worldwide. It offers long distance telephone services to small business and residential customers. The company was founded in 1979 and is based in Scottsdale, Arizona.

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Frequently asked questions

Is American Nortel Communications, Inc (ARTM) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $0.0100 versus a price of $0.0879 — about −89% (overvalued). Model-based estimate, not financial advice.
What is the fair value of ARTM?
Our 21-model fair value for American Nortel Communications, Inc is $0.0100 (as of Jun 24, 2026), built from audited fundamentals. The current price is $0.0879.
What is the quality score of ARTM?
American Nortel Communications, Inc 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.