Group 1: Importance of Data and Factor Construction - The report emphasizes the significance of "high-frequency data + discretization construction methods" for future research on price-volume factors to obtain incremental information with low correlation to existing factors[1] - Continuous factor construction methods, based on a segment of continuous data, show limited incremental benefits when applied to portfolio levels, with excess annualized returns only improving by approximately 0.5%-0.6% when adding minute and tick data factors to daily frequency factors[2][3] - Discretization methods, which extract discrete time points from historical data, can provide significant incremental benefits at the portfolio level, with a constructed portfolio based on "continuous + tick discretization" achieving an excess annualized return of 8.15%[3] Group 2: Performance Metrics of Factors - The "tick discretization" factor shows a monthly IC mean of 0.073 and an annualized ICIR of 2.87, with a 10-group long-short hedge yielding an annualized return of 38.30% and a maximum drawdown of 11.87%[4] - The "minute continuous" factor has a monthly IC mean of 0.079 and an annualized ICIR of 3.57, resulting in an annualized return of 35.99% with a maximum drawdown of 8.10%[3][4] - The combined factor of "daily continuous + minute continuous + tick continuous" achieves a monthly IC mean of 0.087 and an annualized return of 43.08%, indicating the effectiveness of combining different data frequencies[3][4] Group 3: Risk and Limitations - The report warns that the conclusions drawn are based on historical data and statistical models, and significant changes in market conditions could lead to model failure[4] - Despite the apparent improvements in backtesting results when adding minute and tick factors, their contribution at the portfolio level is limited, suggesting that the incremental information they provide may not be substantial[3][4]