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申万宏源证券晨会报告-20250512
Shenwan Hongyuan Securities·2025-05-12 01:13

Group 1: Market Overview - The Shanghai Composite Index closed at 3342 points, with a 1-day decline of 0.3% and a 1-month increase of 1.92% [1] - The Shenzhen Composite Index closed at 1971 points, with a 1-day decline of 0.88% and a 1-month increase of 2.88% [1] - The large-cap index showed a 1-day decline of 0.15% but a 1-month increase of 4.65% [1] Group 2: Industry Performance - The personal care products industry saw a daily increase of 2.72% and a 1-month increase of 18.62% [1] - The banking sector, particularly joint-stock banks, experienced a daily increase of 1.64% and a 1-month increase of 7.68% [1] - The film and television industry faced a daily decline of 2.61% but had a 1-month increase of 2.12% [1] Group 3: Honey Snow Group (蜜雪集团) Insights - Honey Snow Group is the leading fresh beverage company in China, with a market share of 20.2% based on retail sales in 2023 [18] - The company operates 46,479 stores globally, making it the largest fresh beverage company by store count [18] - The fresh beverage market in China reached 517.5 billion yuan in 2023, with a projected compound annual growth rate of 22.2% from 2023 to 2028 [18][19] Group 4: Semiconductor Industry Insights - Semiconductor company SMIC reported a first-quarter utilization rate of 89.6%, with a year-on-year increase in wafer delivery volume of 27.7% [21] - The average selling price (ASP) for wafers decreased by 11.5% to 980 USD per piece due to production adjustments [21] - The company expects a slight revenue decline in the second quarter due to production fluctuations, while maintaining high capital expenditures [21] Group 5: Fund Performance Measurement - A new fund performance measurement method was developed, focusing on extracting similar fund samples and calculating their excess returns [15] - The model has shown a historical return of 112.96%, significantly outperforming the benchmark index [15][17] - The methodology aims to improve the efficiency of fund selection by addressing the limitations of traditional performance momentum strategies [15]