Point to Point Methodics, Inc (PPMH) Fair Value & Analysis
Technology · US · Market cap $30.5K
Point to Point Methodics, Inc
PPMH · US
Fair value as of: Jun 26, 2026
From 6 valuation models · updated 7 days ago
Fair value updated Jun 26, 2026 — revised from $0.2500 to $0.0001 (−100.0%) since Jun 24, 2026.
Price vs Fair Value (12 months)
12‑month range $0.0001 – $0.0001 · the $0.0001 price screens below the $0.0001 fair value. As of Jun 26, 2026.
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Point to Point Methodics, Inc (PPMH) currently trades at $0.0001, while our model-based Fair Value estimate is $0.0001 — implying the stock looks roughly 0.0% undervalued today. We read business quality at 55/100 (solid 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.
About the company
Point to Point Methodics, Inc. engages in acquiring, managing, and operating technology based companies. The company offers Chosen app directory for developers; Smacktive, an app that helps to find people nearby to share activities together; FastMall, a consumer shopping app; various consumer applications, which directly interact with business software; NashPeeps for country music videos; and MapOs, a non GPS or Wi-Fi turn-by-turn navigation technology, as well as develops automotive app for consumers. It also provides digital sociology, and business intelligence and consulting services; and provides rugged outdoor fixed vehicle computers. The company was formerly known as Platinum Pari-Mutuel Holdings, Inc. and changed its name to Point to Point Methodics, Inc. in February 2017. Point to Point Methodics, Inc. is based in Memphis, Tennessee.
Revenue & earnings trend
FY2014 – FY2017 · reported fiscal years
Point to Point Methodics, Inc reported revenue of $298K in FY2017 versus $0 in FY2014. Reported net income was −$220K in FY2017.
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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.