Sea Limited (SE) Fair Value & Analysis
Consumer Cyclical · US · Market cap $54.5B
Analysis
Sea Limited (SE) currently trades at $91.79, while our model-based Fair Value estimate is $57.97 — implying the stock looks roughly 36.8% overvalued today. We read business quality at 95/100 (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
Sea Limited, through its subsidiaries, operates as a technology company in Southeast Asia, Latin America, the rest of Asia, and internationally. The company operates through E-commerce, Digital Financial Services, and Digital Entertainment segments. It offers Garena, a digital entertainment platform for users to access mobile and PC online games, as well as promotes eSports operations and develops games. The company also operates the Shopee e-commerce platform, a mobile-centric marketplace that provides integrated payments, logistics and fulfillment infrastructure, and other value-added services. In addition, it offers Monee digital financial services comprising consumer, and small and medium-sized enterprises (SME) credit, e- wallets, payment processing, banking, Insurtech, and wealth services; and acts as an underwriter for various life and non-life insurance products under the MoneeInsure tradename, as well as insurance agency services. It serves buyers, such as individuals and h…
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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.