高频因子多数维持正收益，多粒度因子持续稳健表现。AI增强组合超额走势出现分化

• The report highlights the strong performance of high-frequency factors, with notable multi-granularity factor returns and differentiated excess returns in AI-enhanced portfolios [6][10][11] - High-frequency factors such as intraday skewness, downside volatility proportion, and opening buy intention proportion recorded significant multi-long-short returns and excess returns across weekly, monthly, and YTD periods [6][10][11] - Multi-granularity models (5-day and 10-day labels) achieved robust multi-long-short returns, with the 5-day label model yielding 0.91% (weekly), 2.6% (monthly), and 10.22% (YTD), while the 10-day label model delivered 0.71% (weekly), 3.06% (monthly), and 8.9% (YTD) [6][10][11] - AI-enhanced portfolios, including the Air Index Increment and CSI 500/1000 AI Enhanced portfolios, demonstrated varying excess and absolute returns under both wide and strict constraints, with weekly and daily rebalancing strategies [6][15][73] - The optimization objective for AI-enhanced portfolios is to maximize expected returns, represented by the function: $max\sum\mu_{i}w_{i}$ where $w_i$ is the weight of stock $i$ in the portfolio, and $\mu_i$ is the expected excess return of stock $i$ [75][76]