Core Viewpoint - BlackRock's Systematic Active Equity (SAE) strategy is increasingly playing a significant role in local investments in China, leveraging advanced data analysis techniques to enhance investment decision-making and performance [1][2]. Group 1: SAE Strategy Overview - As of June 2025, BlackRock's assets under management reached $12.5 trillion, making it one of the largest asset management companies globally [1]. - The SAE strategy utilizes machine learning and natural language processing to capture valuable investment signals, having evolved to its sixth generation language model with $336 billion in assets under management [1]. - The performance of BlackRock's funds utilizing the SAE strategy, such as the CSI 300 Index Enhanced A and the CSI 500 Index Enhanced A, has shown impressive net value growth rates of 18.35% and 18.02% respectively since their inception [1]. Group 2: Implementation and Team Structure - BlackRock plans to fully integrate the SAE strategy into its active equity investments, utilizing over 1,000 proprietary signals and alternative databases to enhance investment breadth and success rates [2]. - The SAE investment team consists of over 120 members with diverse backgrounds in fields such as accounting, engineering, economics, computer science, finance, and physics, including experience from tech companies and NASA [2]. Group 3: Local Adaptation and Machine Learning - The SAE strategy is being localized by deploying global models on China's vast data sets, continuously optimizing the approach based on local market conditions [3]. - The weight of machine learning signals in the SAE model has increased from 15% in 2019 to 30% currently, with expectations for further growth [3]. - The Augmented Investment Management (AIM) system dynamically adjusts and optimizes signal weights based on historical market conditions and fund performance, ensuring adaptability to market changes [3]. Group 4: Investment Strategy and Risk Management - The combination of AI-driven signals and the AIM tool enhances the intelligence, speed, and precision of investment processes [4]. - The SAE strategy focuses on individual stock selection while minimizing exposure to industry and style factors, allowing for a more stable alpha generation across hundreds of stocks [4]. - The systematic strategy aims to maximize excess returns while maintaining control over overall portfolio volatility, drawdown, and active risk [4].