Group 1: ETF Rotation Strategy Performance - The ETF rotation strategy, constructed using GBDT+NN machine learning factors, has shown excellent out-of-sample performance with an IC value of 44.48% and a long position excess return of 0.73% last week [3][14] - The annualized excess return of the strategy is 11.88%, with a maximum drawdown of 17.31% [17][18] - Recent performance includes an excess return of 0.20% last week, 1.64% for the month, and 0.35% year-to-date [18][20] Group 2: High-Frequency Factor Overview - Various high-frequency factors have demonstrated strong overall performance, with the price range factor showing a long position excess return of 4.93% year-to-date, while the regret avoidance factor has underperformed with a return of 0.27% [4][22] - The price range factor measures the activity level of stocks within different price ranges, indicating investor expectations for future price movements [5][25] - The regret avoidance factor reflects the impact of investor emotions on stock price expectations, showing stable out-of-sample excess returns [5][37] Group 3: High-Frequency and Fundamental Factor Combination - A combined strategy of high-frequency and fundamental factors has been developed, yielding an annualized excess return of 14.76% with a maximum drawdown of 4.52% [6][59] - The strategy has shown stable out-of-sample performance, with a year-to-date excess return of 3.74% [60] - The integration of fundamental factors with high-frequency factors has improved the performance metrics of the strategy [57][59]