CICC: Online Platform Valuations Corrected, Sector Attractiveness Rises

Stock News
12/22

Recent market sentiment has led to a broad correction in the online platform sector, with valuations now between the mean and 25th percentile. Fundamentally, the sector remains stable, with healthy growth in key segments like advertising and gaming. Major players such as TENCENT continue to demonstrate improved profit margins.

CICC highlights that AI development remains rapid, and compared to aggressive capital expenditures by overseas tech giants, domestic internet companies' investments are more pragmatic and sustainable. The firm believes AI will become a significant growth driver for select internet companies in the future.

Overall, with solid fundamentals, untapped AI potential, and lower valuations, the sector's attractiveness is increasing. CICC's top pick is TENCENT (00700), while also recommending attention on KUAISHOU-WR (01024), NetEase (09999), and others.

Key insights include: 1. Most companies now trade at "reasonable" 2026E P/E multiples of 15–20x, creating room for potential earnings and valuation upside if performance exceeds expectations. 2. Historically high-valuation names like Bilibili (20–25x) and KUAISHOU-WR (10–15x) contrast with TENCENT, NetEase, and others now at 15–20x. CICC views 20–25x as justifiable for firms with strong long-term prospects and near-term earnings beats.

Emerging long-term drivers worth noting: - NetEase’s innovative monetization model for "Where Winds Meet" (single-player narrative + social付费) shows broader global appeal. - Bilibili’s resilient non-gaming business and focused game strategy may deliver incremental growth. - KUAISHOU-WR’s大幅 improved marketing efficiency after optimizing user acquisition costs has boosted adjusted operating margins. - TENCENT maintains robust operational performance.

CICC maintains existing earnings forecasts, ratings, and price targets for covered companies. Risks include slower macro recovery, regulatory tightening in certain segments, external uncertainties, and AI execution delays.

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