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AGM Group (AGMH) Fair Value & Analysis

Technology · US · Market cap $2.7M

Price$1.04
Fair Value$1.07
Upside+3.0%
Quality92/100
Evidence: High Range $0.8037 – $1.34

Fair value as of: Jun 26, 2026

Analysis

AGM Group (AGMH) currently trades at $1.04, while our model-based Fair Value estimate is $1.07 — implying the stock looks roughly 3.0% undervalued today. We read business quality at 92/100 (high quality), in the Technology sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.

About the company

AGM Group Holdings Inc., a technology company, engages in the sale of cryptocurrency mining machine and standardized computing equipment in China, Hong Kong, and Singapore. It is also involved in the technology hardware research and development, manufacture, as well as assembling and sales of technology hardware. The company was incorporated in 2015 and is based in Wan Chai, Hong Kong.

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Frequently asked questions

Is AGM Group (AGMH) undervalued?
As of Jun 26, 2026, our model estimates a fair value of $1.07 versus a price of $1.04 — about +3% (undervalued). Model-based estimate, not financial advice.
What is the fair value of AGMH?
Our 21-model fair value for AGM Group is $1.07 (as of Jun 26, 2026), built from audited fundamentals. The current price is $1.04.
What is the quality score of AGMH?
AGM Group has a Quality Score of 92/100, 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.