星宸科技跌3.82%,成交额6.11亿元,后市是否有机会?
Xin Lang Cai Jing·2026-01-13 08:29

Core Viewpoint - Starshine Technology's stock experienced a decline of 3.82% on January 13, with a trading volume of 611 million yuan and a market capitalization of 26.42 billion yuan [1] Group 1: Company Overview - Starshine Technology Co., Ltd. is located at 16th Floor, No. 1, Houzhan Road, Tong'an District, Xiamen, Fujian Province, and was established on December 21, 2017, with its IPO on March 28, 2024 [3][7] - The company's main business involves the design, research, and sales of edge AI SoC chips, primarily for smart security, IoT, automotive applications, and other ICs [3][7] - As of December 31, the number of shareholders was 31,900, a decrease of 4.22%, with an average of 5,858 circulating shares per person, an increase of 4.41% [7] Group 2: Financial Performance - For the period from January to September 2025, Starshine Technology achieved a revenue of 2.166 billion yuan, representing a year-on-year growth of 19.50%, and a net profit attributable to shareholders of 202 million yuan, up 3.03% year-on-year [7] - The company has distributed a total of 126 million yuan in dividends since its A-share listing [8] Group 3: Market Activity - The stock has seen a net outflow of 60.31 million yuan from major investors today, with a continuous reduction in major funds over the past three days [4][5] - The average trading cost of the stock is 60.93 yuan, with the current price near a support level of 61.95 yuan, indicating potential for a rebound if it holds above this level [6] Group 4: Strategic Developments - The company has developed chips suitable for AI glasses and has begun shipping to end customers, while also engaging with various clients including mobile brands and startups [2] - Starshine Technology has invested 10 million yuan in Nanjing Qipao Electronic Technology Co., Ltd., acquiring a 4% stake, focusing on ultra-low power consumption chips for smart wearables [2] - The company is enhancing its AI processor IP capabilities to improve processing power and algorithm efficiency, which will support various customer-specific applications [3]