Quantitative Models and Construction Methods 1. **Model Name**: "Rediscover Confidence 2.0" RCP Factor - **Model Construction Idea**: The model is based on a common expectation bias in behavioral finance—overconfidence. It innovatively uses high-frequency minute sequence data to construct the overconfidence factor CP by calculating the time gap between favorable price surges and price corrections. The second-generation Rediscover Confidence Factor (RCP) is derived by orthogonalizing the first-generation CP factor with intraday returns and using the residuals as the RCP factor[1][6]. - **Model Construction Process**: - **Step 1**: Calculate the time gap between favorable price surges and price corrections to construct the overconfidence factor CP. - **Step 2**: Orthogonalize the CP factor with intraday returns. - **Step 3**: Use the residuals from the orthogonalization process as the second-generation Rediscover Confidence Factor (RCP)[6]. - **Model Evaluation**: The RCP factor constructed based on the Rediscover Confidence idea performs significantly better than traditional combination methods[6]. Model Backtesting Results 1. **"Rediscover Confidence 2.0" RCP Factor**: - Annualized Return: 17.68%[1][7][12] - Annualized Volatility: 7.83%[1][7][12] - Information Ratio (IR): 2.26[1][7][12] - Monthly Win Rate: 77.46%[1][7][12] - Maximum Drawdown: 7.46%[1][7][12] Quantitative Factors and Construction Methods 1. **Factor Name**: Overconfidence CP Factor - **Factor Construction Idea**: The factor is based on the degree of investor overconfidence affecting stock prices, using the time difference between rapid price increases and decreases as a proxy variable[6]. - **Factor Construction Process**: - **Step 1**: Calculate the time difference between rapid price increases and decreases to construct the overconfidence factor CP[6]. - **Factor Evaluation**: The CP factor innovatively captures the overconfidence bias in investor behavior[6]. 2. **Factor Name**: Rediscover Confidence RCP Factor - **Factor Construction Idea**: Considering that investors may become overly pessimistic during price corrections, leading to excessive corrections, but due to favorable news, such stocks will eventually rebound. The RCP factor is derived by orthogonalizing the CP factor with intraday returns and using the residuals[6]. - **Factor Construction Process**: - **Step 1**: Orthogonalize the CP factor with intraday returns. - **Step 2**: Use the residuals from the orthogonalization process as the Rediscover Confidence Factor (RCP)[6]. - **Factor Evaluation**: The RCP factor, after purification, shows significantly improved performance[7]. Factor Backtesting Results 1. **Rediscover Confidence RCP Factor**: - IC Mean: 0.04[1] - Annualized ICIR: 3.27[1] - Annualized Return: 20.69%[1] - Information Ratio (IR): 2.91[1] - Monthly Win Rate: 81.55%[1]

- The "Rediscover Confidence 2.0" RCP factor is constructed based on behavioral finance principles, specifically addressing the common expectation bias of overconfidence. The CP factor is initially created using the time gap between rapid price increases and decreases as a proxy variable. Subsequently, the RCP factor is derived by orthogonalizing the CP factor with intraday returns, using the residuals to represent the second-generation factor[6][7] - The RCP factor is further refined by replacing ranking values with standardized factor values to preserve factor information, resulting in improved performance. This adjustment enhances the purity and effectiveness of the RCP factor[7] - The RCP factor demonstrates strong performance metrics during the backtesting period from February 2014 to October 2025. The annualized return is 17.55%, annualized volatility is 7.85%, IR is 2.24, monthly win rate is 77.30%, and maximum monthly drawdown is 7.46%[7][12] - During October 2025, the RCP factor's 10-group long portfolio achieved a return of 2.40%, the short portfolio achieved a return of 1.97%, and the long-short hedged portfolio achieved a return of 0.43%[1][10] - The RCP factor's backtesting results from January 2014 to August 2022 show an IC mean of 0.04, annualized ICIR of 3.27, annualized return of 20.69%, IR of 2.91, and a monthly win rate of 81.55%[1][6]