Core Insights - The report analyzes three representative AI asset management products: AIEQ, ProPicks, and QRFT, assessing whether AI can deliver excess returns for investors [2] - Overall, while overseas AI asset management products have improved quality and efficiency, they should not be overly "mythologized" [2] - AI's more reliable value lies in enhancing information processing efficiency and standardizing investment research processes rather than consistently outperforming indices [2] Group 1: AI-Driven Asset Management: Progress and Cases - The evolution of global financial markets reflects a historical contest between computational power and data processing capabilities [3] - Traditional quantitative investment relies on linear regression and statistical arbitrage, while AI-driven asset management represents a fundamental paradigm shift [3][4] - New AI stock selection strategies utilize deep learning, reinforcement learning, and natural language processing, enabling the identification of non-linear market patterns [4] Group 2: Case Study 1: AIEQ ETF Introduction - AIEQ is the world's first actively managed ETF entirely driven by AI, launched on October 17, 2017 [5] - The fund's investment strategy involves high-frequency scanning and sentiment analysis of the entire market information environment [5] - AIEQ's model processes millions of unstructured texts daily, aiming to capture undervalued stocks before market sentiment changes [5] Group 3: AIEQ Performance Analysis - As of November 2025, AIEQ's performance shows it has underperformed the S&P 500 index, with a YTD return of approximately 9.38% compared to the S&P 500's 12.45% [10] - Over one year, AIEQ returned about +6.15%, while the S&P 500 returned +11.00% [13] - AIEQ's high turnover rate of 1159% significantly impacts its performance, leading to cost erosion [18] Group 4: Case Study 2: Investing ProPicks - ProPicks represents a different AI investment approach through a subscription model, providing users with monthly stock selection lists [21] - The strategy leverages a vast historical database and AI algorithms to evaluate stocks based on over 50 financial indicators [21] - The "Tech Titans" strategy under ProPicks has achieved a cumulative return of 98.7%, significantly outperforming the S&P 500 by 55% [25] Group 5: Case Study 3: QRFT - QRFT employs AI to optimize a traditional factor investment framework, focusing on quality, size, value, momentum, and low volatility [39] - The fund's performance has been slightly better than the S&P 500, with a year-to-date return of approximately +21% as of November 2025 [44] - QRFT's high turnover rate of 267% indicates a high-frequency rebalancing strategy, which poses challenges in terms of cost and performance [48]