Global Profit Technologies, Inc (GLPT) Fair Value & Analysis
Technology · US · Market cap $49.3K
Global Profit Technologies, Inc
GLPT · US
Fair value as of: Jun 26, 2026
From 2 valuation models · updated 7 days ago
Fair value updated Jun 26, 2026 — revised from $0.1300 to $0.0003 (−99.8%) since Jun 24, 2026.
Price vs Fair Value (12 months)
12‑month range $0.0001 – $0.0007 · the $0.0003 price screens below the $0.0003 fair value. As of Jun 26, 2026.
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Global Profit Technologies, Inc (GLPT) currently trades at $0.0003, while our model-based Fair Value estimate is $0.0003 — implying the stock looks roughly 0.0% undervalued today. We read business quality at 44/100 (below-average 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: low) — always confirm before acting.
Trailing-twelve-month revenue stands at $78.8K. Revenue declined 74.9% year over year. Fundamentals as of Jun 26, 2026
Key figures & financial health
More key figures
Figures from reported company fundamentals (EODHD) · as of Jun 26, 2026. TTM = trailing twelve months.
About the company
Global Profit Technologies, Inc., an e-commerce company, focuses on developing, marketing, and managing proprietary trading technologies in the FOREX markets. It offers 4X-Dynamic Automated Trader, a software application that is designed to facilitate trading in the over-the-counter foreign currency markets. The company was formerly known as Fantastic Fun, Inc. Global Profit Technologies, Inc. was incorporated in 1999 and is based in Scottsdale, Arizona.
Revenue & earnings trend
FY2017 – FY2021 · reported fiscal years
Global Profit Technologies, Inc reported revenue of $42.0K in FY2021 versus $104K in FY2017, a compound −20.3%/yr. Reported net income was −$1.0M in FY2021.
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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.