Cyber Media (India) Limited (CYBERMEDIA) Fair Value & Analysis
Communication Services · IN · Market cap ₹349M
Fair value as of: Jun 29, 2026
Analysis
Cyber Media (India) Limited (CYBERMEDIA) currently trades at ₹16.74, while our model-based Fair Value estimate is ₹1.98 — implying the stock looks roughly 88.2% overvalued today. We read business quality at 80/100 (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
Cyber Media (India) Limited, together with its subsidiaries, engages in the media business in India and internationally. It operates through Media Services and Digital Services segments. The company offers various services, such as digital; online and social media platforms; video focus; print publications for magazines; subscription services; bespoke and industry events; and business solutions, including conferences, lead generation, and influencer marketing, as well as advertising, subscriptions, event sponsorships, and custom content solutions. It also provides market research; and research-based insights and consulting services, such as market intelligence, market sizing, stakeholder satisfaction, growth opportunity identification, incubation advisory, and go-to-market services, as well as content syndication services. The company offers its services through the CYBER MEDIA SERVICES, CMR, DATAQUEST, VOICE&DATA, PCQUEST, TDA, CIOL, SAFE, THE DQ WEEK, DQ CHANNELS, GLOBAL 100 SERVI…
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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.