Indian Railway Catering & Tourism Corporation (IRCTC) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹423B
Analysis
Indian Railway Catering & Tourism Corporation (IRCTC) currently trades at ₹518.55, while our model-based Fair Value estimate is ₹307.34 — implying the stock looks roughly 40.7% overvalued today. We read business quality at 97/100 (high quality), in the Consumer Cyclical 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
Indian Railway Catering & Tourism Corporation Limited engages in the provision of catering and hospitality, Internet ticketing, travel and tourism, and packaged drinking water services in India. The company operates through four segments: Catering & Hospitality, Travel & Tourism, Internet Ticketing, and Packaged Drinking Water. It provides mobile catering services for Vande Bharat, Rajdhani, Shatabdi, Duronto, Gatiman, Tejas, and mail/express trains as well as engages in the side vending and e-catering activities; and operates and maintains food plazas, fast food units, food courts, refreshment rooms, mini stores, base kitchens, executive lounges, retiring rooms, Rail Yatri Niwas/BNR hotels, and non-railway catering units. The company also offers tourism products and services comprising domestic tour packages, inbound tourist targeted tours, mass tourism, outbound tour packages, and air ticket and corporate travel; and other tourism activities, such as event management, booking of c…
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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.