Quantitative Models and Construction Methods 1. **Model Name**: "Regain Confidence 2.0" RCP Factor - **Model Construction Idea**: The model is based on the behavioral finance concept of overconfidence. It innovatively uses high-frequency minute sequence data to calculate the time gap between positive news surges and stock price corrections to construct the overconfidence factor CP. The second-generation RCP factor is derived by orthogonalizing the first-generation CP factor with intraday returns, considering the potential overcorrection after overconfidence.[1][6] - **Model Construction Process**: - Calculate the time gap between positive news surges and stock price corrections to construct the overconfidence factor CP. - Orthogonalize the CP factor with intraday returns to obtain the residuals, which form the second-generation RCP factor. - Use standardized factors instead of ranking values to retain factor information, improving the purified effect of the new RCP factor.[6][7] - **Model Evaluation**: The RCP factor-based portfolio significantly outperforms traditional portfolio methods.[6] Model Backtesting Results 1. **"Regain Confidence 2.0" RCP Factor**: - Annualized Return: 17.66%[1][7][10] - Annualized Volatility: 7.87%[1][7][10] - Information Ratio (IR): 2.24[1][7][10] - Monthly Win Rate: 77.14%[1][7][10] - Maximum Drawdown: 7.46%[1][7][10] - September Performance: Long portfolio return 1.00%, short portfolio return -0.97%, long-short hedged return 1.97%[1][10]