打卡一家主观多资产的黑马私募，数据赋能的全球资产捕手

Company Overview - Ningbo Shufa Private Fund Management Co., Ltd. was established in December 2017 and is registered with the China Securities Investment Fund Industry Association under code P1073748 [5][6] - The company emphasizes detailed, timely, and in-depth research methods while focusing on sustainable operations to balance returns and risks [5][9] - As of the end of January 2026, the management scale of the company is nearly 1 billion [6] Investment Philosophy and Strategies - The investment philosophy is centered on global allocation and forward-looking predictions of industry development cycles, focusing on core sectors with a strategy of "core dominance + auxiliary adaptation" [10] - The core strategy is driven by industry foresight, supplemented by in-depth exploration of the industrial chain, selection of quality targets, and dynamic optimization of portfolios [11] - The company aims to maximize returns by leveraging scientific data to reduce subjective decision-making bias while maintaining a focus on risk control [13][15] Core Advantages and Highlights - The company differentiates itself by adhering to a "scientific data-supported subjective investment" philosophy, ensuring that all industry forecasts and target selections are based on comprehensive data [20] - It has established a robust data-driven research methodology, integrating macro, industry, and individual asset data for real-time updates and precise analysis [21] - The company has mechanisms in place for continuous data system upgrades, team building, research optimization, and global asset tracking to enhance its research capabilities and investment decision-making [22][23][25][26] Expected Management Scale and Profit Sources - The ideal management scale is projected to be between 3 billion to 5 billion, allowing for sufficient allocation of quality targets while ensuring flexibility in fund adjustments [17] - Core profits are expected to derive from capturing overall growth in core industries, benefiting from premium quality targets, and optimizing portfolio returns [18]