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Sands China Ltd (SCHYF) Fair Value & Analysis

Consumer Cyclical · US · Market cap $16.4B

Price$1.70
Fair Value$2.18
Upside+28.2%
Quality95/100
Evidence: High Range $1.46 – $2.90

Analysis

Sands China Ltd (SCHYF) currently trades at $1.70, while our model-based Fair Value estimate is $2.18 — implying the stock looks roughly 28.2% undervalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.

About the company

Sands China Ltd. develops, owns, and operates integrated resorts and casinos in Macao. The company owns and operates The Venetian Macao, The Londoner Macao, The Parisian Macao resort, The Plaza Macao, and The Sands Macao casino; the Cotai Expo, a convention and exhibition hall; and The Venetian and The Londoner Arena, an entertainment venues, as well as Cotai Water Jet ferry for leisure and business travelers. It offers ferry transportation and leasing services, and pontoon leasing; gaming and other related activities; travel and tourism agency services; security services; and human resources administration services, as well as outsourcing services, including information technology, accounting, hotel management, and marketing. The company was incorporated in 2009 and is headquartered in Macau. Sands China Ltd. operates as a subsidiary of Las Vegas Sands Corp.

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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.