Television Broadcasts Limited (TVBCF) Fair Value & Analysis
Communication Services · US · Market cap $187M
Fair value as of: Jun 25, 2026
Analysis
Television Broadcasts Limited (TVBCF) currently trades at $0.3900, while our model-based Fair Value estimate is $0.3600 — implying the stock looks roughly 7.7% overvalued today. We read business quality at 92/100 (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: high).
About the company
Television Broadcasts Limited, together with its subsidiaries, engages in terrestrial television broadcasting, digital media services, and other television-related activities. It operates through TV Broadcasting; Digital Media; Chinese Mainland Operations; and International Operations segments. The TV Broadcasting segment is involved in the broadcasting of television programmes and commercials on terrestrial TV platforms; production of programmes; music entertainment, and operation of e-Commerce business. The Digital Media segment operates myTV SUPER OTT service, online social media platform, digital marketing, and other digital-related businesses in Hong Kong. The Chinese Mainland Operations segment co-produces dramas; and distributes television programmes and channels to telecast, video, and media operators in Mainland China. The International Operations segment offers pay television and OTT services to subscribers; and distributes television programmes and channels to telecast, v…
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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.