Core Viewpoint - The AI Fund, Invesco Great Wall Dividend Quantitative Stock A (022344), reported a profit of 169,100 yuan for Q4 2025, with a weighted average profit per fund share of 0.0224 yuan. The fund's net asset value growth rate was 2.05%, and the fund size reached 8.1173 million yuan by the end of Q4 2025 [3][12]. Fund Performance - As of January 22, the unit net value was 1.136 yuan. The fund manager, Xu Yujun and Li Haiwei, currently manage five funds. The highest one-year cumulative net value growth rate among these funds was 58.62% for Invesco Great Wall SSE Sci-Tech Innovation Board 50 Index Enhanced A, while the lowest was 52.19% for Invesco Great Wall CSI 500 Index Enhanced A [3]. - The fund's net value growth rate over the last three months was 3.38%, ranking 94 out of 121 comparable funds, and over the last six months, it was 4.01%, ranking 105 out of 121 [3]. Investment Strategy - The fund is an actively managed quantitative fund primarily focused on high-dividend stocks. The investment portfolio emphasizes fundamental quantitative stock selection, maintaining a balance between value and growth styles, while focusing on companies with good cash flow and stable internal growth. The strategy aims to generate sustained excess returns through bottom-up stock selection amid market volatility [3]. Risk Metrics - As of December 31, the fund's Sharpe ratio since inception was 0.1449 [4]. - The maximum drawdown since inception was 6.63%, with the largest quarterly drawdown occurring in Q4 2025 at 5.46% [7]. Fund Holdings - As of Q4 2025, the fund's top ten holdings included China COSCO Shipping, Chongqing Bank, Yanzhou Coal Mining, Shaanxi Coal and Chemical Industry, Shanxi Coal International, China Shenhua Energy, Industrial Bank, Guiyang Bank, Haohua Energy, and Industrial and Commercial Bank of China [15]. Portfolio Allocation - The average stock position since inception was 85.84%, compared to the industry average of 88.34%. The fund reached a peak stock position of 91.95% at the end of Q3 2025 and a low of 79.57% at the end of Q4 2025 [11].

文 ｜ 上官鹏 王兆宇 赵文荣 2）单策略之间相关性不高，说明不同策略在不同市场环境中的适应性差异大，有利于形成收益互补。以预期改善组合来看， 其与均衡弹性、高质量经营、科技TMT和新能源组合相关性分别为0 . 2 9、0 . 1 3、0 . 3 7和0 . 5 3； 3）综合三大类全市场选股策略和两大类产业选股策略构建多策略组合，回测发现，相比单策略组合，多策略组合具有更加稳 健的收益表现。2 0 1 4年以来截至2 0 2 5年3月3 1日，多策略组合相对中证全指的年化超额收益分别为1 3 . 8%，信息比率为1 . 5。 ▍ 战胜宽基指数多策略框架历史收益稳健，相对基准偏离度低。 1）基于多策略组合历史持仓战胜沪深 3 0 0、中证 5 0 0 和中证 1 0 0 0 指数框架在指数权重方面的分配比例， 8 0%配置在指数成 分内， 2 0%配置在其他公司，并且超配多策略股票组合权重。 单一策略具有一定的风格倾向性，难以适应不同市场环境的变化，而多策略能够通过分散化利用不同策略在不同市场环境中的 适应性差异，提升整体投资组合收益的稳健性。因此，我们尝试从多策略角度战胜宽基指数，基于已经发布报告中的三大类 ...