TNL Mediagene (TNMG) Fair Value & Analysis
Communication Services · US · Market cap $1.4M
Fair value as of: Jun 25, 2026
Analysis
TNL Mediagene (TNMG) currently trades at $0.4855, while our model-based Fair Value estimate is $0.2100 — implying the stock looks roughly 56.7% overvalued today. We read business quality at 91/100 (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
TNL Mediagene operates as a media company in Taiwan and Japan. The company operates The News Lens, a news site; Business Insider Japan and Business Insider Taiwan, a news site focused on developments inside and outside Japan and Taiwan in business, finance, politics, and technology; DIGIDAY JAPAN, a publication for Japanese and international digital marketing news; MASHING UP, a conference and event series; Modern Retail, a site for retail marketing; Becoming Aces, a site to promote young entrepreneurs; and GLOSSY JAPAN, a site for beauty and fashion industry. It also operates Gizmodo Japan, a weblog site that publishes news, reviews, and buying guides of latest technology and consumer gadgets; Cool3c, a gadget weblog site; Tech Insider, a site publishing stories on technology and business of technology; INSIDE, an online news publication focused on internet and software startups, blockchain, technology industry trends, digital life, and future technology. In addition, the company o…
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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.