AI赋能资产配置（二十六）：AI“添翼”：大模型增强投资组合回报

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." AIEQ, a sentiment-driven active ETF, has underperformed SPY due to high market sentiment volatility and cost erosion from high fees and turnover [2] - ProPicks, a subscription-based product, has shown strong returns during tech uptrends but is highly sensitive to execution discipline and slippage, making actual replication challenging [2] - QRFT, an AI-enhanced ETF, has shown performance close to the S&P 500, with significant variations in performance over different periods, focusing more on narrow enhancements rather than stable high alpha [2] - The report concludes that AI's more reliable value lies in enhancing information processing efficiency and standardizing research processes rather than guaranteeing consistent outperformance against 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, marking a paradigm shift in investment decision-making mechanisms [3] - Traditional quantitative investment relies on linear regression and statistical arbitrage, while the new generation of AI-driven strategies utilizes deep learning, reinforcement learning, and natural language processing to identify nonlinear market patterns [4] Group 2: Case Study 1: AIEQ ETF Introduction - AIEQ ETF, launched on October 17, 2017, is the world's first actively managed ETF entirely by AI, utilizing IBM Watson's cognitive computing platform for its investment strategy [5] - AIEQ's investment approach involves high-frequency scanning and sentiment interpretation of the entire market information environment, processing millions of unstructured texts daily [5] Group 3: AIEQ Performance Analysis - As of November 2025, AIEQ's performance shows a cumulative return of 107.34% since inception, but it has underperformed the S&P 500 significantly over various time frames [8][13] - AIEQ's annual turnover rate is an astonishing 1159%, reflecting its sensitivity to short-term market sentiment, which has led to significant cost erosion [18] - The fund's asset management scale has stagnated between $114 million and $117 million, indicating disappointment among investors due to its long-term underperformance [20] Group 4: Case Study 2: Investing ProPicks - ProPicks represents a different AI investment path through a subscription model, providing users with monthly stock picks based on a vast historical database and AI algorithms [21] - The "Tech Titans" strategy under ProPicks has achieved a cumulative return of 98.7% since its launch, significantly outperforming the S&P 500 by 55% [25] Group 5: Case Study 3: QRFT - QRFT, launched in May 2019, employs AI to optimize a traditional factor investment framework, focusing on quality, size, value, momentum, and low volatility [39] - As of November 2025, QRFT's performance has been slightly better than the S&P 500, with a five-year annualized return of approximately 14.9% [44] - QRFT's turnover rate is 267%, indicating a high-frequency rebalancing strategy, which poses challenges in terms of cost and performance relative to low-cost index funds [48]