Avicanna Inc (AVCNF) Fair Value & Analysis
Healthcare · US · Market cap $12.1M
Fair value as of: Jun 26, 2026
Analysis
Avicanna Inc (AVCNF) currently trades at $0.0870, while our model-based Fair Value estimate is $0.0200 — implying the stock looks roughly 77.0% overvalued today. We read business quality at 80/100 (high quality), in the Healthcare 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
Avicanna Inc., a commercial-stage biopharmaceutical company, engages in the research, development, advancement, and commercialization of evidence-based cannabinoid-based products and formulations for medical and pharmaceutical markets in Canada and internationally. It provides medical cannabis formulary products, including oral, sublingual, topical, and transdermal deliveries with various ratios of cannabinoids under the RHO Phyto brand; and indication-specific cannabinoid-based candidates to address unmet medical needs in the areas of dermatology, chronic pain, and various neurological disorders, as well as Trunerox, an indication-specific drug treatment for seizure associated with Lennox-Gastaut Syndrome and Dravet Syndrome. The company also offers active pharmaceutical ingredients comprising various cannabidiol, tetrahydrocannabinol, and cannabigerol for use in the development and production of food, cosmetics, medical, and pharmaceutical products under the Aureus Santa Marta bra…
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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.