Core Viewpoint - The article highlights the performance and investment strategies of Hangzhou Oak Asset Management Co., Ltd., emphasizing its strong returns and focus on quantitative stock investment strategies [3][6]. Company Overview - Hangzhou Oak Asset Management was established in March 2018 and is registered with the Asset Management Association of China [3]. - As of the end of July, Oak Asset's products achieved an average return of ***%, ranking second among quantitative private equity funds with a scale of 20-50 billion in the first seven months [3]. - The "Oak Wangjiang No. 2" fund ranked first in excess returns among the CSI 1000 index in the same period, while "Oak Yongfu" ranked second in the CSI 500 index [3]. Investment Philosophy & Strategies - The company focuses on high-frequency quantitative investment, utilizing a dual-driven approach of "mathematical insight × engineering implementation" to build price-volume models that identify short-term price fluctuations and mispricing opportunities [11]. - The investment strategy is based on in-depth analysis of historical price-volume data to uncover factors with financial logic or explainability [11]. Core Team - The core team consists of 13 members, with a research team of 8 professionals, including PhDs from top universities and experienced IT experts, averaging 8.5 years of industry experience [8][19]. - The team has maintained a "zero core loss" stability, ensuring continuity and consistency in investment strategies [19]. Competitive Advantages - Oak Asset has a long-term focus on high-frequency price-volume stock selection, with an annualized turnover of approximately 120 times, demonstrating strong adaptability and long-term return potential [17]. - The quantitative models emphasize logical factors and explainability, showing excellent historical predictive capabilities [18]. Future Outlook - The company plans to continue refining its high-frequency price-volume strategies while maintaining the core framework, focusing on model detail enhancement and trading execution optimization to improve investment efficiency [21].